diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml index 7efee124df9..e2922f32c41 100644 --- a/.github/workflows/build.yml +++ b/.github/workflows/build.yml @@ -49,18 +49,47 @@ jobs: https://oss.sonatype.org/service/local/staging/profiles/$STAGING_PROFILE_ID/start export STAGING_REPOSITORY_ID=`awk -F'[<>]' '/stagedRepositoryId/{print $3}' response.xml` echo "Staging repository created: $STAGING_REPOSITORY_ID" + echo "::set-output name=stagingRepositoryId::$STAGING_REPOSITORY_ID" - name: Checkout repository uses: actions/checkout@v1 - name: Extract distribution repository URL id: repository run: | if [[ "${{ env.DEPLOY_RELEASE }}" = "true" ]]; then - export REPOSITORY_URL=`mvn exec:exec -q -N -Dexec.executable='echo' -Dexec.args="\\${project.distributionManagement.repository.url}" -DstagingRepositoryId=$STAGING_REPOSITORY_ID` + export REPOSITORY_URL=`mvn exec:exec -q -N -Dexec.executable='echo' -Dexec.args="\\${project.distributionManagement.repository.url}" -DstagingRepositoryId=${{ steps.staging.outputs.stagingRepositoryId }}` else export REPOSITORY_URL=`mvn exec:exec -q -N -Dexec.executable='echo' -Dexec.args="\\${project.distributionManagement.snapshotRepository.url}"` fi echo "Repository URL: $REPOSITORY_URL" echo "::set-output name=repositoryUrl::$REPOSITORY_URL" + linux-arm64: + runs-on: ubuntu-2204-arm64-2c + needs: prepare + strategy: + matrix: + ext: [""] + steps: + - name: Install environment + run: | + sudo apt update + sudo apt install -y curl wget unzip tar git gcc g++ + - name: Configure Java + uses: actions/setup-java@v2 + with: + distribution: 'zulu' + java-version: '17' + architecture: 'aarch64' + - name: Checkout repository + uses: actions/checkout@v1 + - name: Build project + run: | + gcc --version + mvn -version + echo "ossrh${{ secrets.CI_DEPLOY_USERNAME }}${{ secrets.CI_DEPLOY_PASSWORD }}" > $HOME/.m2/settings.xml + mvn clean install -pl '!tensorflow-framework' -B -U -e -Djavacpp.platform=${{ github.job }} -Djavacpp.platform.extension=${{ matrix.ext }} + - name: Deploy native artifact + if: env.DEPLOY_RELEASE == 'true' || env.DEPLOY_SNAPSHOT == 'true' + run: mvn -f tensorflow-core/tensorflow-core-native/pom.xml deploy:deploy-file@native-only -B -e -Djavacpp.platform=${{ github.job }} -Djavacpp.platform.extension=${{ matrix.ext }} -Durl=${{ needs.prepare.outputs.repositoryUrl }} linux-x86_64: runs-on: ubuntu-20.04 needs: prepare @@ -109,7 +138,7 @@ jobs: if: env.DEPLOY_RELEASE == 'true' || env.DEPLOY_SNAPSHOT == 'true' run: mvn -f tensorflow-core/tensorflow-core-native/pom.xml deploy:deploy-file@native-only -B -e -Djavacpp.platform=${{ github.job }} -Djavacpp.platform.extension=${{ matrix.ext }} -Durl=${{ needs.prepare.outputs.repositoryUrl }} macosx-x86_64: - runs-on: macos-11 + runs-on: macos-13 needs: prepare strategy: matrix: @@ -177,10 +206,9 @@ jobs: run: | call mvn -f tensorflow-core/tensorflow-core-native/pom.xml deploy:deploy-file@native-only -B -e -Djavacpp.platform=${{ github.job }} -Djavacpp.platform.extension=${{ matrix.ext }} -Durl=${{ needs.prepare.outputs.repositoryUrl }} if ERRORLEVEL 1 exit /b - deploy: if: ${{ github.event_name == 'push' && (github.ref == 'refs/heads/master' || github.ref == 'refs/heads/staging') }} # DEPLOY_SNAPSHOT (releases should be signed and deployed manually from local machine) - needs: [linux-x86_64, macosx-x86_64, windows-x86_64, macosx-arm64] + needs: [linux-x86_64, macosx-x86_64, windows-x86_64, macosx-arm64, linux-arm64] runs-on: ubuntu-20.04 steps: - name: Configure Java diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 2e4871f89c1..874bdddaf52 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -15,8 +15,7 @@ For dependencies, we can use anything compliant with [this list](https://opensou ## Building -To build all the artifacts locally, simply invoke the command `mvn install` at the root of this repository (or the Maven command of your choice). It is also -possible to build artifacts with support for CUDA® by adding the `-Djavacpp.platform.extension=-gpu` argument to the Maven command. +To build all the artifacts locally, simply invoke the command `mvn install` at the root of this repository (or the Maven command of your choice). ### JDK 16+ @@ -35,7 +34,7 @@ This can be done in `.mvn/jvm.config` or `MAVEN_OPTS`. ### Native Builds By default, the build will attempt to download the existing TensorFlow binaries from the web for the platform it is running on (so you need to have an active internet connection). -If such binaries are not available for your platform, you will need to build the TensorFlow runtime library from sources, by appending the `-Dnative.build` argument to your Maven +If such binaries are not available for your platform, you will need to build the TensorFlow runtime library from sources, by appending the `-Pnative-build` argument to your Maven command. This requires a valid environment for building TensorFlow, including the [bazel](https://bazel.build/) build tool and a few Python dependencies (please read [TensorFlow documentation](https://www.tensorflow.org/install/source) for more details). Note that building from sources can take multiple hours on a regular laptop. @@ -79,7 +78,7 @@ To upgrade the version of TensorFlow that is embedded within TensorFlow Java, pl ### Upgrading TensorFlow Native Library 1. Download locally the archive of the tensorflow release at https://github.com/tensorflow/tensorflow/archive/refs/tags/vX.X.X.tar.gz -2. Compute the SHA sum using the shell command `sha256sum ` +2. Compute the SHA sum using the shell command `shasum -a 256 ` 3. Update `urls`, `sha256` and `strip_prefix` fields of the `org_tensorflow` archive rule in Bazel [workspace](https://github.com/tensorflow/java/blob/master/tensorflow-core/tensorflow-core-native/WORKSPACE#L19) 4. Extract the archive in a temporary folder 5. Copy the content of `tensorflow-x.x.x/.bazelrc` file to `tensorflow-core/tensorflow-core-native/tensorflow.bazelrc` under TensorFlow Java source tree diff --git a/MIGRATING.md b/MIGRATING.md index 542f3a25e0d..44a1924a512 100644 --- a/MIGRATING.md +++ b/MIGRATING.md @@ -3,6 +3,82 @@ TensorFlow Java is still in an alpha stage, therefore is subject to contain breaking changes between the different releases. This guide explain in detail how to migrate your code from a previous version to a new one that includes some changes that are not backward compatible. +## Migrating to 1.0.0 + +TensorFlow-Java 1.0.0 requires Java 11 or later. + +### Native Artifact Renaming + +The native artifacts, that used to be distributed as `tensorflow-core-api`, are now distributed under `tensorflow-core-native`. If you still add +`tensorflow-core-platform` in your project, that won't affect you. But if you were adding dependencies to specific native runtimes, you need to update +them to reflect the new artifact name. + +For example, +```xml + + org.tensorflow + tensorflow-core-api + 0.5.0 + + + org.tensorflow + tensorflow-core-api + 0.5.0 + linux-x86_64 + +``` +will now be +```xml + + org.tensorflow + tensorflow-core-api + 1.0.0 + + + org.tensorflow + tensorflow-core-native + 1.0.0 + linux-x86_64 + +``` +### Java Module Renaming + +The Java Module (jigsaw) names has been updated to drop the leading `org.`, as follow: +- `tensorflow-core-api` : `tensorflow` (was `org.tensorflow` before) +- `tensorflow-core-generator` : `tensorflow.generator` (was `org.tensorflow-generator` before) +- `tensorflow-core-native` : `tensorflow.nativelib` +- `tensorflow-framework` : `tensorflow.framework` (was `org.tensorflow.framework` before) + +### GPU Support + +Previous versions of TF Java were building a `tensorflow-core-platform-gpu` artifact upon which application could depend +on to include any TensorFlow native library that GPU support enabled. Since TensorFlow has removed its support of GPU +on all platforms other that Linux, we removed our platform JAR in favour of simply adding a dependency on the +`linux-x86_64-gpu` native artifact. +```xml + + org.tensorflow + tensorflow-core-native + 1.0.0 + linux-x86_64-gpu + +``` +Please note that including this dependency won't work if your application also depends on `tensorflow-core-platform`. If +you need to support more platforms that Linux, you should include the other `tensorflow-core-native` dependencies +separately (see the [README](README.md) file). + +### Session Run Result + +In versions before 0.4.0 `Session.Runner.run` and `TensorFunction.call` returned a `List`. In newer versions +they return a `Result` class which is `AutoCloseable` to make management of the tensor lifetime simpler. To migrate +users should wrap the `run` invocation in a try-with-resources statement rather than closing the output tensors +individually. + +### Proto Definitions Moved + +Some proto definitions under `org.tensorflow.proto` have been moved to a different location under the same package. You will need to reimport these +proto bindings to match the new location. Your IDE should easily be able to do this for you. + ## Migrating to 0.3.0 ### Non-parameterized Typed Tensors diff --git a/README.md b/README.md index ff5d158d748..1df21073340 100644 --- a/README.md +++ b/README.md @@ -56,11 +56,12 @@ restrictive. While TensorFlow Java can be compiled for [multiple platforms](https://github.com/tensorflow/java/blob/master/tensorflow-core/pom.xml#L54), only binaries for the followings are being **supported and distributed** by this project: -- `linux-x86_64`: Linux platforms on Intel chips -- `linux-x86_64-gpu`: Linux platforms on Intel chips with Cuda GPU support -- `macosx-x86_64`: MacOS X platforms on Intel chips +- `linux-x86_64`: Linux platforms on Intel/AMD chips +- `linux-x86_64-gpu`: Linux platforms on Intel/AMD chips with Cuda GPU support +- `linux-arm64`: Linux platforms on Arm chips +- `macosx-x86_64`: MacOS X platforms on Intel/AMD chips - `macosx-arm64`: MacOS X platforms on Apple Silicon chips -- `windows-x86_64`: Windows platforms on Intel chips +- `windows-x86_64`: Windows platforms on Intel/AMD chips For example, for building a JAR that uses TensorFlow and is targeted to be deployed only on Linux systems with no GPU support, you should add the following dependencies: @@ -68,12 +69,12 @@ systems with no GPU support, you should add the following dependencies: org.tensorflow tensorflow-core-api - 0.5.0 + 1.0.0 org.tensorflow tensorflow-core-native - 0.5.0 + 1.0.0 linux-x86_64 ``` @@ -84,24 +85,24 @@ native dependencies as follows: org.tensorflow tensorflow-core-api - 0.5.0 + 1.0.0 org.tensorflow tensorflow-core-native - 0.5.0 + 1.0.0 linux-x86_64-gpu org.tensorflow tensorflow-core-native - 0.5.0 + 1.0.0 macosx-arm64 org.tensorflow tensorflow-core-native - 0.5.0 + 1.0.0 windows-x86_64 ``` @@ -114,15 +115,15 @@ Only one dependency can be added per platform, meaning that you cannot add nativ In some cases, it might be preferable to add a single dependency that includes transitively all the artifacts required to run TensorFlow Java on any [supported platforms](README.md#individual-dependencies) -- `tensorflow-core-platform`: Includes `tensorflow-core-api`, plus native artifacts for `linux-x86_64`, `macosx-arm64`, `macosx-x86_64` and `windows-x86_64` +- `tensorflow-core-platform`: Includes `tensorflow-core-api`, plus native artifacts for `linux-x86_64`, `linux-x86_64-arm64`, `macosx-arm64`, `macosx-x86_64` and `windows-x86_64` -For example, to run TensorFlow Java on any platform for which a binary is being distributed by this project, you can +For example, to run TensorFlow Java on any CPU platform for which a binary is being distributed by this project, you can simply add this dependency to your application: ```xml org.tensorflow tensorflow-core-platform - 0.5.0 + 1.0.0 ``` @@ -152,7 +153,7 @@ to add Sonatype OSS repository in your pom.xml, like the following org.tensorflow tensorflow-core-platform - 1.0.0-SNAPSHOT + 1.1.0-SNAPSHOT ``` @@ -172,8 +173,10 @@ This table shows the mapping between TensorFlow, TensorFlow Java and minimum sup | 0.4.1 | 2.7.1 | 8 | | 0.4.2 | 2.7.4 | 8 | | 0.5.0 | 2.10.1 | 11 | -| 0.6.0-SNAPSHOT | 2.10.1 | 11 | -| 1.0.0-SNAPSHOT | 2.16.1 | 11 | +| 1.0.0-rc.1 | 2.16.1 | 11 | +| 1.0.0-rc.2 | 2.16.2 | 11 | +| 1.0.0 | 2.16.2 | 11 | +| 1.1.0-SNAPSHOT | 2.16.2 | 11 | ## How to Contribute? diff --git a/docs/install.md b/docs/install.md index 091bd1b4c01..3c969c433dc 100644 --- a/docs/install.md +++ b/docs/install.md @@ -13,19 +13,21 @@ Caution: The TensorFlow Java API is *not* covered by the TensorFlow ## Requirements -TensorFlow Java runs on Java 8 and above, and supports out-of-the-box the +TensorFlow Java runs on Java 11 and above, and supports out-of-the-box the following platforms: -* Ubuntu 16.04 or higher; 64-bit, x86 -* macOS 10.12.6 (Sierra) or higher; 64-bit, x86 -* Windows 7 or higher; 64-bit, x86 +* Ubuntu 20.04 or higher; 64-bit, x86 +* Ubuntu 22.04 or higher; 64-bit, arm +* macOS 12 or higher; 64-bit, x86 +* macOS 14 or higher; 64-bit, arm +* Windows 10 or higher; 64-bit, x86 *Note: To use TensorFlow on Android, see [TensorFlow Lite](https://tensorflow.org/lite)* ## Versions -TensorFlow Java has its own release cycle, independent from the +TensorFlow Java has its own release cycle, independent of the [TensorFlow runtime](https://github.com/tensorflow/tensorflow). Consequently, its version does not match the version of TensorFlow runtime it runs on. Consult the TensorFlow Java @@ -41,8 +43,7 @@ TensorFlow Java to your project. The easiest one is to add a dependency on the Core API and the native dependencies it requires to run on all supported platforms. -You can also select the `tensorflow-core-platform-gpu` extension instead, which -supports CUDA® on Linux and Windows platforms. +To include CUDA® support for Linux x86, select the `tensorflow-core-native:linux-x86_64-gpu` artifact. In addition, a separate dependency on the `tensorflow-framework` library can be added to benefit from a rich set of utilities for TensorFlow-based machine @@ -58,7 +59,7 @@ For example, org.tensorflow tensorflow-core-platform - 0.5.0 + 1.0.0 ``` @@ -101,7 +102,7 @@ snapshots repository in your `pom.xml`. org.tensorflow tensorflow-core-platform - 1.0.0-SNAPSHOT + 1.1.0-SNAPSHOT ``` @@ -118,7 +119,7 @@ repositories { } dependencies { - compile group: 'org.tensorflow', name: 'tensorflow-core-platform', version: '0.5.0' + compile group: 'org.tensorflow', name: 'tensorflow-core-platform', version: '1.0.0' } ``` @@ -164,7 +165,7 @@ add the TensorFlow dependency to the project's `pom.xml` file: org.tensorflow tensorflow-core-platform - 0.5.0 + 1.0.0 diff --git a/pom.xml b/pom.xml index 41d80cf24fa..9beb6963034 100644 --- a/pom.xml +++ b/pom.xml @@ -7,7 +7,7 @@ org.tensorflow tensorflow-java - 1.0.0-SNAPSHOT + 1.0.0 pom TensorFlow Java Parent @@ -26,7 +26,7 @@ https://github.com/tensorflow/java.git - git@github.com:tensorflow/java.git + scm:git@github.com:tensorflow/java.git scm:git:https://github.com/tensorflow/java.git @@ -329,6 +329,18 @@ + + linux-arm64 + + + linux + aarch64 + + + !javacpp.platform.extension + + + macosx diff --git a/release.sh b/release.sh index 01f99386a71..6ed2fa51754 100755 --- a/release.sh +++ b/release.sh @@ -34,7 +34,7 @@ fi # To get a shell to poke around the maven artifacts with. if [[ -z "${CMD}" ]] then - CMD="mvn clean deploy -B -e --settings ./settings.xml -Pdeploying -Preleasing -DstagingRepositoryId=${STAGING_SEQ}" + CMD="mvn clean deploy -B -e --settings ./settings.xml -Pdeploying -Preleasing -DstagingRepositoryId=orgtensorflow-${STAGING_SEQ}" fi export GPG_TTY=$(tty) @@ -45,6 +45,12 @@ then cp -f ~/.m2/settings.xml . fi +docker build \ + -f tools/Dockerfile.release \ + -t tensorflow-java:latest \ + --platform linux/amd64 \ + . + docker run \ -e GPG_TTY="${GPG_TTY}" \ -v ${PWD}:/tensorflow-java \ @@ -52,7 +58,7 @@ docker run \ -w /tensorflow-java \ -it \ --platform linux/amd64 \ - maven:3.8.6-jdk-11 \ + tensorflow-java:latest \ ${CMD} echo diff --git a/tensorflow-core/pom.xml b/tensorflow-core/pom.xml index d0ea8480f95..26ed6786798 100644 --- a/tensorflow-core/pom.xml +++ b/tensorflow-core/pom.xml @@ -22,7 +22,7 @@ org.tensorflow tensorflow-java - 1.0.0-SNAPSHOT + 1.0.0 tensorflow-core pom diff --git a/tensorflow-core/tensorflow-core-api/pom.xml b/tensorflow-core/tensorflow-core-api/pom.xml index 1d43bd43454..1f1303aa03a 100644 --- a/tensorflow-core/tensorflow-core-api/pom.xml +++ b/tensorflow-core/tensorflow-core-api/pom.xml @@ -6,7 +6,7 @@ org.tensorflow tensorflow-core - 1.0.0-SNAPSHOT + 1.0.0 tensorflow-core-api jar @@ -15,7 +15,7 @@ Platform-dependent native code and pure-Java code for the TensorFlow machine intelligence library. - 1.0.0-rc.1 + 1.0.0 1.1.5 false ${project.build.directory}/tf-text-download/ @@ -230,6 +230,12 @@ jar + + -Xmaxerrs + 65536 + -Xmaxwarns + 65536 + false 256m 2048m diff --git a/tensorflow-core/tensorflow-core-api/scripts/test_download.sh b/tensorflow-core/tensorflow-core-api/scripts/test_download.sh index 03e4c854285..5f47ee00115 100755 --- a/tensorflow-core/tensorflow-core-api/scripts/test_download.sh +++ b/tensorflow-core/tensorflow-core-api/scripts/test_download.sh @@ -5,10 +5,10 @@ DOWNLOAD_FOLDER="$1" case ${PLATFORM:-} in 'linux-x86_64') - TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/c5/ef/5b8270e5665923bda4222f56382d9fbcb7fd6efd5fb8557ad0776848cdff/tensorflow_text-2.16.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl' + TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/43/dd/8f03331107b76e63313d2089ddfbd13f15e51fb8ed73517cdd0ab3341928/tensorflow-2.16.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl' ;; 'macosx-x86_64') - TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/ed/5d/b55f48cdf98a164d293f660748c2501ea828e148250a4cadbb5b0d988735/tensorflow_text-2.16.1-cp311-cp311-macosx_10_9_x86_64.whl' + TEXT_WHEEL_URL='https://files.pythonhosted.org/packages/6d/69/9999c2d9e8a3b08dfcfc7e9259a05fb1da5f700936091d2eb4a7985c2776/tensorflow-2.16.2-cp311-cp311-macosx_10_15_x86_64.whl' ;; *) echo "TensorFlow Text distribution for ${PLATFORM} is not supported for download" diff --git a/tensorflow-core/tensorflow-core-api/src/api/api_def_SegmentSumV2.pbtxt b/tensorflow-core/tensorflow-core-api/src/api/api_def_SegmentSumV2.pbtxt index 0895c391f2b..4478e3a5fb8 100644 --- a/tensorflow-core/tensorflow-core-api/src/api/api_def_SegmentSumV2.pbtxt +++ b/tensorflow-core/tensorflow-core-api/src/api/api_def_SegmentSumV2.pbtxt @@ -4,4 +4,18 @@ op { endpoint { name: "math.SegmentSum" } + description: < * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code BitwiseAnd} output and operands @@ -91,7 +90,6 @@ public BitwiseAnd bitwiseAnd(Operand x, Operand y) * tf.assert_equal(tf.cast(res, tf.float32), exp) # TRUE * * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code BitwiseOr} output and operands @@ -121,7 +119,6 @@ public BitwiseOr bitwiseOr(Operand x, Operand y) { * tf.assert_equal(tf.cast(res, tf.float32), exp) # TRUE * * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code BitwiseXor} output and operands @@ -172,7 +169,6 @@ public BitwiseXor bitwiseXor(Operand x, Operand y) * tf.assert_equal(tf.cast(inverted, tf.float32), tf.cast(expected, tf.float32)) * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Invert} output and operands * @return a new instance of Invert @@ -212,7 +208,6 @@ public Invert invert(Operand x) { * # <tf.Tensor: shape=(4,), dtype=int8, numpy=array([ -2, 64, 101, 32], dtype=int8)> * * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code LeftShift} output and operands @@ -255,7 +250,6 @@ public LeftShift leftShift(Operand x, Operand y) { * # <tf.Tensor: shape=(4,), dtype=int8, numpy=array([ -2, 64, 101, 32], dtype=int8)> * * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code RightShift} output and operands diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ClusterOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ClusterOps.java index 869fb25f23a..e59e86f23ed 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ClusterOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ClusterOps.java @@ -26,7 +26,7 @@ /** * An API for building {@code cluster} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class ClusterOps { private final Scope scope; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/CollectiveOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/CollectiveOps.java index e5b580bd068..de786dc95fe 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/CollectiveOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/CollectiveOps.java @@ -34,7 +34,7 @@ /** * An API for building {@code collective} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class CollectiveOps { private final Scope scope; @@ -49,7 +49,6 @@ public final class CollectiveOps { /** * Mutually exchanges multiple tensors of identical type and shape. * - * @param data type for {@code data} output * @param input The input value * @param communicator The communicator value * @param groupAssignment The groupAssignment value @@ -79,7 +78,6 @@ public CollectiveAssignGroup collectiveAssignGroup(Operand groupAssignme /** * Receives a tensor value broadcast from another device. * - * @param data type for {@code data} output * @param groupSize The groupSize value * @param groupKey The groupKey value * @param instanceKey The instanceKey value @@ -98,7 +96,6 @@ public CollectiveBcastRecv collectiveBcastRecv(Operand data type for {@code data} output * @param input The input value * @param groupSize The groupSize value * @param groupKey The groupKey value @@ -119,7 +116,6 @@ public CollectiveBcastSend collectiveBcastSend(Operand i * collective ops. In this case, keys that are unique at runtime * (e.g. {@code instance_key}) should be used to distinguish collective groups. * - * @param data type for {@code data} output * @param input The input value * @param groupSize The groupSize value * @param groupKey The groupKey value @@ -157,7 +153,6 @@ public CollectiveInitializeCommunicator collectiveInitializeCommunicator(Operand * source_target_pairs={@code [[0,1],[1,2],[2,3],[3,0]]} gets the outputs: * {@code [D, A, B, C]}. * - * @param data type for {@code output} output * @param input The local input to be permuted. Currently only supports float and * bfloat16. * @param sourceTargetPairs A tensor with shape [num_pairs, 2]. @@ -172,7 +167,6 @@ public CollectivePermute collectivePermute(Operand input /** * Mutually reduces multiple tensors of identical type and shape. * - * @param data type for {@code data} output * @param input The input value * @param communicator The communicator value * @param groupAssignment The groupAssignment value @@ -193,7 +187,6 @@ public CollectiveReduce collectiveReduce(Operand input * collective ops. In this case, keys that are unique at runtime * (e.g. {@code instance_key}) should be used to distinguish collective groups. * - * @param data type for {@code data} output * @param input The input value * @param groupSize The groupSize value * @param groupKey The groupKey value diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataExperimentalOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataExperimentalOps.java index 4644599e7f1..4fa8e60e295 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataExperimentalOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataExperimentalOps.java @@ -66,7 +66,7 @@ /** * An API for building {@code data.experimental} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class DataExperimentalOps { private final Scope scope; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java index 77b0a424cae..8047510d2c2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DataOps.java @@ -155,7 +155,7 @@ /** * An API for building {@code data} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class DataOps { public final DataExperimentalOps experimental; @@ -987,7 +987,6 @@ public LatencyStatsDataset latencyStatsDataset(Operand inputDat /** * Computes rectified linear gradients for a LeakyRelu operation. * - * @param data type for {@code backprops} output * @param gradients The backpropagated gradients to the corresponding LeakyRelu operation. * @param features The features passed as input to the corresponding LeakyRelu operation, * OR the outputs of that operation (both work equivalently). diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DebuggingOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DebuggingOps.java index 289a355dea3..4ea1efd10db 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DebuggingOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DebuggingOps.java @@ -24,7 +24,7 @@ /** * An API for building {@code debugging} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class DebuggingOps { private final Scope scope; @@ -43,7 +43,6 @@ public final class DebuggingOps { * tensor. Unlike CheckNumerics (V1), CheckNumericsV2 distinguishes -Inf and +Inf * in the errors it throws. * - * @param data type for {@code output} output * @param tensor The tensor value * @param message Prefix of the error message. * @param data type for {@code CheckNumericsV2} output and operands diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DistributeOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DistributeOps.java index 50f5a2aa63f..4f30df6352d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DistributeOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DistributeOps.java @@ -27,7 +27,7 @@ /** * An API for building {@code distribute} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class DistributeOps { private final Scope scope; @@ -52,7 +52,6 @@ public final class DistributeOps { * num_devices: The number of devices participating in this reduction. * shared_name: Identifier that shared between ops of the same reduction. * - * @param data type for {@code data} output * @param input The input value * @param reduction The value of the reduction attribute * @param numDevices The value of the numDevices attribute @@ -74,7 +73,6 @@ public NcclAllReduce ncclAllReduce(Operand input, Stri * output: The same as input. * shape: The shape of the input tensor. * - * @param data type for {@code output} output * @param input The input value * @param shape The value of the shape attribute * @param data type for {@code NcclBroadcast} output and operands @@ -93,7 +91,6 @@ public NcclBroadcast ncclBroadcast(Operand input, Shap * data: the value of the reduction across all {@code num_devices} devices. * reduction: the reduction operation to perform. * - * @param data type for {@code data} output * @param input The input value * @param reduction The value of the reduction attribute * @param data type for {@code NcclReduce} output and operands diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java index 8304e333023..42f59c161d7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/DtypesOps.java @@ -28,7 +28,7 @@ /** * An API for building {@code dtypes} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class DtypesOps { private final Scope scope; @@ -69,7 +69,6 @@ public AsString asString(Operand input, AsString.Options... opt /** * Cast x of type SrcT to y of DstT. * - * @param data type for {@code y} output * @param x The x value * @param DstT The value of the DstT attribute * @param options carries optional attribute values @@ -95,7 +94,6 @@ public Cast cast(Operand x, Class DstT, * tf.complex(real, imag) ==> [[2.25 + 4.75j], [3.25 + 5.75j]] * * - * @param data type for {@code out} output * @param real The real value * @param imag The imag value * @param Tout The value of the Tout attribute diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java index 801e020d814..f3fa3e6bbc0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ImageOps.java @@ -71,7 +71,7 @@ /** * An API for building {@code image} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class ImageOps { private final Scope scope; @@ -93,7 +93,6 @@ public final class ImageOps { * channel and then adjusts each component of each pixel to * {@code (x - mean) * contrast_factor + mean}. * - * @param data type for {@code output} output * @param images Images to adjust. At least 3-D. * @param contrastFactor A float multiplier for adjusting contrast. * @param data type for {@code AdjustContrastv2} output and operands @@ -112,7 +111,6 @@ public AdjustContrast adjustContrast(Operand images, * colors are first mapped into HSV. A delta is then applied all the hue values, * and then remapped back to RGB colorspace. * - * @param data type for {@code output} output * @param images Images to adjust. At least 3-D. * @param delta A float delta to add to the hue. * @param data type for {@code AdjustHue} output and operands @@ -130,7 +128,6 @@ public AdjustHue adjustHue(Operand images, Operand data type for {@code output} output * @param images Images to adjust. At least 3-D. * @param scale A float scale to add to the saturation. * @param data type for {@code AdjustSaturation} output and operands @@ -250,7 +247,6 @@ public CropAndResizeGradBoxes cropAndResizeGradBoxes(Operand grads, /** * Computes the gradient of the crop_and_resize op wrt the input image tensor. * - * @param data type for {@code output} output * @param grads A 4-D tensor of shape {@code [num_boxes, crop_height, crop_width, depth]}. * @param boxes A 2-D tensor of shape {@code [num_boxes, 4]}. The {@code i}-th row of the tensor * specifies the coordinates of a box in the {@code box_ind[i]} image and is specified @@ -357,7 +353,6 @@ public DecodeGif decodeGif(Operand contents) { * first frame that does not occupy the entire canvas, it uses the previous * frame to fill the unoccupied areas. * - * @param data type for {@code image} output * @param contents 0-D. The encoded image bytes. * @param options carries optional attribute values * @return a new instance of DecodeImage, with default output types @@ -384,7 +379,6 @@ public DecodeImage decodeImage(Operand contents, DecodeImage.Op * first frame that does not occupy the entire canvas, it uses the previous * frame to fill the unoccupied areas. * - * @param data type for {@code image} output * @param contents 0-D. The encoded image bytes. * @param dtype The desired DType of the returned Tensor. * @param options carries optional attribute values @@ -438,7 +432,6 @@ public DecodeJpeg decodeJpeg(Operand contents, DecodeJpeg.Options... op *

This op also supports decoding JPEGs and non-animated GIFs since the interface * is the same, though it is cleaner to use {@code tf.io.decode_image}. * - * @param data type for {@code image} output * @param contents 0-D. The PNG-encoded image. * @param options carries optional attribute values * @return a new instance of DecodePng, with default output types @@ -463,7 +456,6 @@ public DecodePng decodePng(Operand contents, DecodePng.Options[ *

This op also supports decoding JPEGs and non-animated GIFs since the interface * is the same, though it is cleaner to use {@code tf.io.decode_image}. * - * @param data type for {@code image} output * @param contents 0-D. The PNG-encoded image. * @param dtype The value of the dtype attribute * @param options carries optional attribute values @@ -487,7 +479,6 @@ public DecodePng decodePng(Operand contents, Cla * the bounding box will be {@code (40, 10)} to {@code (100, 50)} (in (x,y) coordinates). *

Parts of the bounding box may fall outside the image. * - * @param data type for {@code output} output * @param images 4-D with shape {@code [batch, height, width, depth]}. A batch of images. * @param boxes 3-D with shape {@code [batch, num_bounding_boxes, 4]} containing bounding * boxes. @@ -602,7 +593,6 @@ public ExtractGlimpse extractGlimpse(Operand input, Operand si /** * Extract {@code patches} from {@code images} and put them in the "depth" output dimension. * - * @param data type for {@code patches} output * @param images 4-D Tensor with shape {@code [batch, in_rows, in_cols, depth]}. * @param ksizes The size of the sliding window for each dimension of {@code images}. * @param strides How far the centers of two consecutive patches are in @@ -626,7 +616,6 @@ public ExtractImagePatches extractImagePatches(Operand i * Extract the shape information of a JPEG-encoded image. * This op only parses the image header, so it is much faster than DecodeJpeg. * - * @param data type for {@code image_shape} output * @param contents 0-D. The JPEG-encoded image. * @return a new instance of ExtractJpegShape, with default output types */ @@ -638,7 +627,6 @@ public ExtractJpegShape extractJpegShape(Operand contents) { * Extract the shape information of a JPEG-encoded image. * This op only parses the image header, so it is much faster than DecodeJpeg. * - * @param data type for {@code image_shape} output * @param contents 0-D. The JPEG-encoded image. * @param outputType (Optional) The output type of the operation (int32 or int64). * Defaults to int32. @@ -691,7 +679,6 @@ public GenerateBoundingBoxProposals generateBoundingBoxProposals(OperandSee {@code rgb_to_hsv} for a description of the HSV encoding. * - * @param data type for {@code output} output * @param images 1-D or higher rank. HSV data to convert. Last dimension must be size 3. * @param data type for {@code HSVToRGB} output and operands * @return a new instance of HsvToRgb @@ -708,7 +695,6 @@ public HsvToRgb hsvToRgb(Operand images) { * {@code k = c0 x + c1 y + 1}. If the transformed point lays outside of the input * image, the output pixel is set to 0. * - * @param data type for {@code transformed_images} output * @param images 4-D with shape {@code [batch, height, width, channels]}. * @param transforms 2-D Tensor, {@code [batch, 8]} or {@code [1, 8]} matrix, where each row corresponds to a 3 x 3 * projective transformation matrix, with the last entry assumed to be 1. If there @@ -733,7 +719,6 @@ public ImageProjectiveTransformV2 imageProjectiveTransfor * {@code k = c0 x + c1 y + 1}. If the transformed point lays outside of the input * image, the output pixel is set to fill_value. * - * @param data type for {@code transformed_images} output * @param images 4-D with shape {@code [batch, height, width, channels]}. * @param transforms 2-D Tensor, {@code [batch, 8]} or {@code [1, 8]} matrix, where each row corresponds to a 3 x 3 * projective transformation matrix, with the last entry assumed to be 1. If there @@ -794,7 +779,6 @@ public NearestNeighbors nearestNeighbors(Operand points, Operand data type for {@code selected_scores} output * @param boxes A 2-D float tensor of shape {@code [num_boxes, 4]}. * @param scores A 1-D float tensor of shape {@code [num_boxes]} representing a single * score corresponding to each box (each row of boxes). @@ -854,7 +838,6 @@ public NonMaxSuppressionWithOverlaps nonMaxSuppressionWithOverlaps(Operand data type for {@code resized_images} output * @param images 4-D with shape {@code [batch, height, width, channels]}. * @param sizeOutput = A 1-D int32 Tensor of 2 elements: {@code new_height, new_width}. The * new size for the images. @@ -878,7 +861,6 @@ public QuantizedResizeBilinear quantizedResizeBilinear(Op * rectangle from that location. The random location is picked so the cropped * area will fit inside the original image. * - * @param data type for {@code output} output * @param image 3-D of shape {@code [height, width, channels]}. * @param sizeOutput 1-D of length 2 containing: {@code crop_height}, {@code crop_width}.. * @param options carries optional attribute values @@ -931,7 +913,6 @@ public ResizeBicubic resizeBicubic(Operand images, Operand data type for {@code output} output * @param grads 4-D with shape {@code [batch, height, width, channels]}. * @param originalImage 4-D with shape {@code [batch, orig_height, orig_width, channels]}, * The image tensor that was resized. @@ -962,7 +943,6 @@ public ResizeBilinear resizeBilinear(Operand images, /** * Computes the gradient of bilinear interpolation. * - * @param data type for {@code output} output * @param grads 4-D with shape {@code [batch, height, width, channels]}. * @param originalImage 4-D with shape {@code [batch, orig_height, orig_width, channels]}, * The image tensor that was resized. @@ -978,7 +958,6 @@ public ResizeBilinearGrad resizeBilinearGrad(Operand data type for {@code resized_images} output * @param images 4-D with shape {@code [batch, height, width, channels]}. * @param sizeOutput = A 1-D int32 Tensor of 2 elements: {@code new_height, new_width}. The * new size for the images. @@ -994,7 +973,6 @@ public ResizeNearestNeighbor resizeNearestNeighbor(Operan /** * Computes the gradient of nearest neighbor interpolation. * - * @param data type for {@code output} output * @param grads 4-D with shape {@code [batch, height, width, channels]}. * @param sizeOutput = A 1-D int32 Tensor of 2 elements: {@code orig_height, orig_width}. The * original input size. @@ -1031,7 +1009,6 @@ public ResizeNearestNeighborGrad resizeNearestNeighborGra * * * - * @param data type for {@code output} output * @param images 1-D or higher rank. RGB data to convert. Last dimension must be size 3. * @param data type for {@code RGBToHSV} output and operands * @return a new instance of RgbToHsv @@ -1076,7 +1053,6 @@ public RgbToHsv rgbToHsv(Operand images) { * bounding box covering the whole image. If {@code use_image_if_no_bounding_boxes} is * false and no bounding boxes are supplied, an error is raised. * - * @param data type for {@code begin} output * @param imageSize 1-D, containing {@code [height, width, channels]}. * @param boundingBoxes 3-D with shape {@code [batch, N, 4]} describing the N bounding boxes * associated with the image. @@ -1113,7 +1089,6 @@ public ScaleAndTranslate scaleAndTranslate(Operand images, /** * The ScaleAndTranslateGrad operation * - * @param data type for {@code output} output * @param grads The grads value * @param originalImage The originalImage value * @param scale The scale value @@ -1189,7 +1164,6 @@ public ScaleAndTranslateGrad scaleAndTranslateGrad(Operan * bounding box covering the whole image. If {@code use_image_if_no_bounding_boxes} is * false and no bounding boxes are supplied, an error is raised. * - * @param data type for {@code begin} output * @param imageSize 1-D, containing {@code [height, width, channels]}. * @param boundingBoxes 3-D with shape {@code [batch, N, 4]} describing the N bounding boxes * associated with the image. diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java index 4f33bea6a52..5c33c56e962 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/IoOps.java @@ -78,7 +78,7 @@ /** * An API for building {@code io} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class IoOps { private final Scope scope; @@ -160,7 +160,6 @@ public DecodeJsonExample decodeJsonExample(Operand jsonExamples) { /** * Reinterpret the bytes of a string as a vector of numbers. * - * @param data type for {@code output} output * @param inputBytes Tensor of string to be decoded. * @param fixedLength Length in bytes for each element of the decoded output. Must be a multiple * of the size of the output type. @@ -177,7 +176,6 @@ public DecodePaddedRaw decodePaddedRaw(Operand i /** * Reinterpret the bytes of a string as a vector of numbers. * - * @param data type for {@code output} output * @param bytes All the elements must have the same length. * @param outType The value of the outType attribute * @param options carries optional attribute values @@ -231,7 +229,6 @@ public DecodeRaw decodeRaw(Operand bytes, Class * shape = [2 50] * * - * @param data type for {@code sparse_values} output * @param serializedSparse 2-D, The {@code N} serialized {@code SparseTensor} objects. * Must have 3 columns. * @param dtype The {@code dtype} of the serialized {@code SparseTensor} objects. @@ -581,7 +578,6 @@ public ParseSingleSequenceExample parseSingleSequenceExample(Operand se /** * Transforms a serialized tensorflow.TensorProto proto into a Tensor. * - * @param data type for {@code output} output * @param serialized A scalar string containing a serialized TensorProto proto. * @param outType The type of the serialized tensor. The provided type must match the * type of the serialized tensor and no implicit conversion will take place. @@ -883,7 +879,6 @@ public ReaderSerializeState readerSerializeState(Operand reader * rank {@code R-1}. *

The minibatch size {@code N} is extracted from {@code sparse_shape[0]}. * - * @param data type for {@code serialized_sparse} output * @param sparseIndices 2-D. The {@code indices} of the minibatch {@code SparseTensor}. * @param sparseValues 1-D. The {@code values} of the minibatch {@code SparseTensor}. * @param sparseShape 1-D. The {@code shape} of the minibatch {@code SparseTensor}. @@ -903,7 +898,6 @@ public SerializeManySparse serializeManySparse(Operand sparseIn * rank {@code R-1}. *

The minibatch size {@code N} is extracted from {@code sparse_shape[0]}. * - * @param data type for {@code serialized_sparse} output * @param sparseIndices 2-D. The {@code indices} of the minibatch {@code SparseTensor}. * @param sparseValues 1-D. The {@code values} of the minibatch {@code SparseTensor}. * @param sparseShape 1-D. The {@code shape} of the minibatch {@code SparseTensor}. @@ -920,7 +914,6 @@ public SerializeManySparse serializeManySparse(Operand data type for {@code serialized_sparse} output * @param sparseIndices 2-D. The {@code indices} of the {@code SparseTensor}. * @param sparseValues 1-D. The {@code values} of the {@code SparseTensor}. * @param sparseShape 1-D. The {@code shape} of the {@code SparseTensor}. @@ -934,7 +927,6 @@ public SerializeSparse serializeSparse(Operand sparseIndices, /** * Serialize a {@code SparseTensor} into a {@code [3]} {@code Tensor} object. * - * @param data type for {@code serialized_sparse} output * @param sparseIndices 2-D. The {@code indices} of the {@code SparseTensor}. * @param sparseValues 1-D. The {@code values} of the {@code SparseTensor}. * @param sparseShape 1-D. The {@code shape} of the {@code SparseTensor}. diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java index 9a6e88ddcef..b83771a2930 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgOps.java @@ -80,7 +80,7 @@ /** * An API for building {@code linalg} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class LinalgOps { public final LinalgSparseOps sparse; @@ -127,7 +127,6 @@ public final class LinalgOps { * tf.linalg.band_part(input, 0, 0) ==> Diagonal. * * - * @param data type for {@code band} output * @param input Rank {@code k} tensor. * @param numLower 0-D tensor. Number of subdiagonals to keep. If negative, keep entire * lower triangle. @@ -145,7 +144,6 @@ public BandPart bandPart(Operand inpu /** * The BandedTriangularSolve operation * - * @param data type for {@code output} output * @param matrix The matrix value * @param rhs The rhs value * @param options carries optional attribute values @@ -160,7 +158,6 @@ public BandedTriangularSolve bandedTriangularSolve(Operand< /** * The BatchCholesky operation * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code BatchCholesky} output and operands * @return a new instance of BatchCholesky @@ -172,7 +169,6 @@ public BatchCholesky batchCholesky(Operand input) { /** * The BatchCholeskyGrad operation * - * @param data type for {@code output} output * @param l The l value * @param grad The grad value * @param data type for {@code BatchCholeskyGrad} output and operands @@ -185,7 +181,6 @@ public BatchCholeskyGrad batchCholeskyGrad(Operand l, /** * The BatchMatrixBandPart operation * - * @param data type for {@code band} output * @param input The input value * @param numLower The numLower value * @param numUpper The numUpper value @@ -200,7 +195,6 @@ public BatchMatrixBandPart batchMatrixBandPart(Operand i /** * The BatchMatrixDeterminant operation * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code BatchMatrixDeterminant} output and operands * @return a new instance of BatchMatrixDeterminant @@ -212,7 +206,6 @@ public BatchMatrixDeterminant batchMatrixDeterminant(Operan /** * The BatchMatrixDiag operation * - * @param data type for {@code output} output * @param diagonal The diagonal value * @param data type for {@code BatchMatrixDiag} output and operands * @return a new instance of BatchMatrixDiag @@ -224,7 +217,6 @@ public BatchMatrixDiag batchMatrixDiag(Operand diagonal) /** * The BatchMatrixDiagPart operation * - * @param data type for {@code diagonal} output * @param input The input value * @param data type for {@code BatchMatrixDiagPart} output and operands * @return a new instance of BatchMatrixDiagPart @@ -236,7 +228,6 @@ public BatchMatrixDiagPart batchMatrixDiagPart(Operand i /** * The BatchMatrixInverse operation * - * @param data type for {@code output} output * @param input The input value * @param options carries optional attribute values * @param data type for {@code BatchMatrixInverse} output and operands @@ -250,7 +241,6 @@ public BatchMatrixInverse batchMatrixInverse(Operand i /** * The BatchMatrixSetDiag operation * - * @param data type for {@code output} output * @param input The input value * @param diagonal The diagonal value * @param data type for {@code BatchMatrixSetDiag} output and operands @@ -264,7 +254,6 @@ public BatchMatrixSetDiag batchMatrixSetDiag(Operand inp /** * The BatchMatrixSolve operation * - * @param data type for {@code output} output * @param matrix The matrix value * @param rhs The rhs value * @param options carries optional attribute values @@ -279,7 +268,6 @@ public BatchMatrixSolve batchMatrixSolve(Operand matri /** * The BatchMatrixSolveLs operation * - * @param data type for {@code output} output * @param matrix The matrix value * @param rhs The rhs value * @param l2Regularizer The l2Regularizer value @@ -295,7 +283,6 @@ public BatchMatrixSolveLs batchMatrixSolveLs(Operand m /** * The BatchMatrixTriangularSolve operation * - * @param data type for {@code output} output * @param matrix The matrix value * @param rhs The rhs value * @param options carries optional attribute values @@ -310,7 +297,6 @@ public BatchMatrixTriangularSolve batchMatrixTriangularSo /** * The BatchSelfAdjointEigV2 operation * - * @param data type for {@code e} output * @param input The input value * @param options carries optional attribute values * @param data type for {@code BatchSelfAdjointEigV2} output and operands @@ -324,7 +310,6 @@ public BatchSelfAdjointEig batchSelfAdjointEig(Operand /** * The BatchSvd operation * - * @param data type for {@code s} output * @param input The input value * @param options carries optional attribute values * @param data type for {@code BatchSvd} output and operands @@ -347,7 +332,6 @@ public BatchSvd batchSvd(Operand input, BatchSvd.Options * not for large batch dimensions when the submatrices are small. In this * case it might be faster to use the CPU. * - * @param data type for {@code output} output * @param input Shape is {@code [..., M, M]}. * @param data type for {@code Cholesky} output and operands * @return a new instance of Cholesky @@ -361,7 +345,6 @@ public Cholesky cholesky(Operand input) { * For an explanation see "Differentiation of the Cholesky algorithm" by * Iain Murray http://arxiv.org/abs/1602.07527. * - * @param data type for {@code output} output * @param l Output of batch Cholesky algorithm l = cholesky(A). Shape is {@code [..., M, M]}. * Algorithm depends only on lower triangular part of the innermost matrices of * this tensor. @@ -381,7 +364,6 @@ public CholeskyGrad choleskyGrad(Operand l, Operand * {@code y.shape[i] == x.shape[perm[i]] for i in [0, 1, ..., rank(x) - 1]} * {@code y[i,j,k,...,s,t,u] == conj(x[perm[i], perm[j], perm[k],...,perm[s], perm[t], perm[u]])} * - * @param data type for {@code y} output * @param x The x value * @param perm The perm value * @param data type for {@code ConjugateTranspose} output and operands @@ -398,7 +380,6 @@ public ConjugateTranspose conjugateTranspose(Operand x, * or any shape where the innermost dimension is 3. In the latter case, each pair * of corresponding 3-element vectors is cross-multiplied independently. * - * @param data type for {@code product} output * @param a A tensor containing 3-element vectors. * @param b Another tensor, of same type and shape as {@code a}. * @param data type for {@code Cross} output and operands @@ -414,7 +395,6 @@ public Cross cross(Operand a, Operand b) { * form square matrices. The output is a tensor containing the determinants * for all input submatrices {@code [..., :, :]}. * - * @param data type for {@code output} output * @param input Shape is {@code [..., M, M]}. * @param data type for {@code MatrixDeterminant} output and operands * @return a new instance of Det @@ -436,7 +416,6 @@ public Det det(Operand input) { * e = eig(a, compute_v=False) * * - * @param data type for {@code e} output * @param input {@code Tensor} input of shape {@code [N, N]}. * @param Tout The value of the Tout attribute * @param options carries optional attribute values @@ -514,7 +493,6 @@ public Eig eig(Operand input, Class Tou *
{@literal @}end_compatibility * * - * @param data type for {@code output} output * @param inputs List of 1 or 2 Tensors. * @param equation String describing the Einstein Summation operation; in the format of np.einsum. * @param data type for {@code Einsum} output and operands @@ -531,7 +509,6 @@ public Einsum einsum(Iterable> inputs, String eq * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -554,7 +531,6 @@ public EuclideanNorm euclideanNorm(Operand input, * may detect the condition and raise an exception or it may simply return a * garbage result. * - * @param data type for {@code output} output * @param input Shape is {@code [..., M, M]}. * @param options carries optional attribute values * @param data type for {@code MatrixInverse} output and operands @@ -632,7 +608,6 @@ public LoadAndRemapMatrix loadAndRemapMatrix(Operand ckptPath, * is the {@code LU} decomposition of the input and {@code P} is the corresponding * permutation matrix. * - * @param data type for {@code sign} output * @param input Shape is {@code [N, M, M]}. * @param data type for {@code LogMatrixDeterminant} output and operands * @return a new instance of LogMatrixDeterminant @@ -657,8 +632,6 @@ public LogMatrixDeterminant logMatrixDeterminant(Operand * and {@code M-1}, inclusive. If P_mat denotes the permutation matrix corresponding to * P, then the L, U and P satisfies P_mat * input = L * U. * - * @param data type for {@code lu} output - * @param data type for {@code p} output * @param input A tensor of shape {@code [..., M, M]} whose inner-most 2 dimensions form matrices of * size {@code [M, M]}. * @param data type for {@code Lu} output and operands @@ -684,8 +657,6 @@ public Lu lu(Operand input) { * and {@code M-1}, inclusive. If P_mat denotes the permutation matrix corresponding to * P, then the L, U and P satisfies P_mat * input = L * U. * - * @param data type for {@code lu} output - * @param data type for {@code p} output * @param input A tensor of shape {@code [..., M, M]} whose inner-most 2 dimensions form matrices of * size {@code [M, M]}. * @param outputIdxType The value of the outputIdxType attribute @@ -707,7 +678,6 @@ public Lu lu(Operand input, *

Note: The default kernel implementation for MatMul on GPUs uses * cublas. * - * @param data type for {@code product} output * @param a The a value * @param b The b value * @param options carries optional attribute values @@ -801,7 +771,6 @@ public MatMul matMul(Operand a, Operand b, MatMul.Opt * [9, 2]] * * - * @param data type for {@code output} output * @param diagonal Rank {@code r}, where {@code r >= 1} * @param k Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main * diagonal, and negative value means subdiagonals. {@code k} can be a single integer @@ -886,7 +855,6 @@ public MatrixDiag matrixDiag(Operand diagonal, Operand * - * @param data type for {@code diagonal} output * @param input Rank {@code r} tensor where {@code r >= 2}. * @param k Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main * diagonal, and negative value means subdiagonals. {@code k} can be a single integer @@ -995,7 +963,6 @@ public MatrixDiagPart matrixDiagPart(Operand input, Oper * * * - * @param data type for {@code diagonal} output * @param input Rank {@code r} tensor where {@code r >= 2}. * @param k Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main * diagonal, and negative value means subdiagonals. {@code k} can be a single integer @@ -1123,7 +1090,6 @@ public MatrixDiagPartV3 matrixDiagPartV3(Operand input, * * * - * @param data type for {@code output} output * @param diagonal Rank {@code r}, where {@code r >= 1} * @param k Diagonal offset(s). Positive value means superdiagonal, 0 refers to the main * diagonal, and negative value means subdiagonals. {@code k} can be a single integer @@ -1150,7 +1116,6 @@ public MatrixDiagV3 matrixDiagV3(Operand diagonal, Opera /** * Deprecated, use python implementation tf.linalg.matrix_exponential. * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code MatrixExponential} output and operands * @return a new instance of MatrixExponential @@ -1173,7 +1138,6 @@ public MatrixExponential matrixExponential(Operand input * form square matrices. The output is a tensor of the same shape as the input * containing the exponential for all input submatrices {@code [..., :, :]}. * - * @param data type for {@code output} output * @param input Shape is {@code [..., M, M]}. * @param data type for {@code MatrixLogarithm} output and operands * @return a new instance of MatrixLogarithm @@ -1281,7 +1245,6 @@ public MatrixLogarithm matrixLogarithm(Operand input) { * * * - * @param data type for {@code output} output * @param input Rank {@code r+1}, where {@code r >= 1}. * @param diagonal Rank {@code r} when {@code k} is an integer or {@code k[0] == k[1]}. Otherwise, it has rank {@code r+1}. * {@code k >= 1}. @@ -1331,7 +1294,6 @@ public MatrixSetDiag matrixSetDiag(Operand input, Operan * typically 6-7 times slower than the fast path. If {@code fast} is {@code False} then * {@code l2_regularizer} is ignored. * - * @param data type for {@code output} output * @param matrix Shape is {@code [..., M, N]}. * @param rhs Shape is {@code [..., M, K]}. * @param l2Regularizer Scalar tensor. @@ -1362,7 +1324,6 @@ public MatrixSolveLs matrixSolveLs(Operand matrix, Opera * q_full, r_full = qr(a, full_matrices=True) * * - * @param data type for {@code q} output * @param input A tensor of shape {@code [..., M, N]} whose inner-most 2 dimensions * form matrices of size {@code [M, N]}. Let {@code P} be the minimum of {@code M} and {@code N}. * @param options carries optional attribute values @@ -1380,7 +1341,6 @@ public Qr qr(Operand input, Qr.Options... options) { * outer dimension of {@code b} (after being transposed if {@code transposed_b} is * non-zero). * - * @param data type for {@code out} output * @param a Must be a two-dimensional tensor. * @param b Must be a two-dimensional tensor. * @param minA The float value that the lowest quantized {@code a} value represents. @@ -1411,7 +1371,6 @@ public QuantizedMatMul quantizedMatMul * non-zero). Then do broadcast add operation with bias values on the matrix * multiplication result. The bias size must match inner dimension of {@code b}. * - * @param data type for {@code out} output * @param a A matrix to be multiplied. Must be a two-dimensional tensor of type {@code quint8}. * @param b A matrix to be multiplied and must be a two-dimensional tensor of type {@code qint8}. * @param bias A 1D bias tensor with size matching inner dimension of {@code b} (after being @@ -1442,7 +1401,6 @@ public QuantizedMatMulWithBias quantizedMatMulWithBias( * multiplication result. The bias size must match inner dimension of {@code b}. Then do * relu activation to get non-negative result. * - * @param data type for {@code out} output * @param a A matrix to be multiplied. Must be a two-dimensional tensor of type {@code quint8}. * @param b A matrix to be multiplied and must be a two-dimensional tensor of type {@code qint8}. * @param bias A 1D bias tensor with size matching with inner dimension of {@code b} (after being @@ -1474,7 +1432,6 @@ public QuantizedMatMulWithBiasAndRelu quantizedMatMulWith * relu activation to get non-negative result. Then do requantize operation to get * final uint8 result. * - * @param data type for {@code out} output * @param a A matrix to be multiplied. Must be a two-dimensional tensor of type {@code quint8}. * @param b A matrix to be multiplied and must be a two-dimensional tensor of type {@code qint8}. * @param bias A 1D bias tensor with size matching with inner dimension of {@code b} (after being @@ -1512,7 +1469,6 @@ public QuantizedMatMulWithBiasAndReluAndRequantize quanti * e = self_adjoint_eig(a, compute_v=False) * * - * @param data type for {@code e} output * @param input {@code Tensor} input of shape {@code [N, N]}. * @param options carries optional attribute values * @param data type for {@code SelfAdjointEigV2} output and operands @@ -1532,7 +1488,6 @@ public SelfAdjointEig selfAdjointEig(Operand input, * If {@code adjoint} is {@code True} then each output matrix satisfies * {@code adjoint(matrix[..., :, :]) * output[..., :, :] = rhs[..., :, :]}. * - * @param data type for {@code output} output * @param matrix Shape is {@code [..., M, M]}. * @param rhs Shape is {@code [..., M, K]}. * @param options carries optional attribute values @@ -1559,7 +1514,6 @@ public Solve solve(Operand matrix, Operand rhs, * form square matrices. The output is a tensor of the same shape as the input * containing the matrix square root for all input submatrices {@code [..., :, :]}. * - * @param data type for {@code output} output * @param input Shape is {@code [..., M, M]}. * @param data type for {@code MatrixSquareRoot} output and operands * @return a new instance of Sqrtm @@ -1581,7 +1535,6 @@ public Sqrtm sqrtm(Operand input) { * s, _, _ = svd(a, compute_uv=False) * * - * @param data type for {@code s} output * @param input A tensor of shape {@code [..., M, N]} whose inner-most 2 dimensions * form matrices of size {@code [M, N]}. Let {@code P} be the minimum of {@code M} and {@code N}. * @param options carries optional attribute values @@ -1608,7 +1561,6 @@ public Svd svd(Operand input, Svd.Options... options) { * [0, 0, 0, 4]] * * - * @param data type for {@code output} output * @param diagonal Rank k tensor where k is at most 1. * @param data type for {@code Diag} output and operands * @return a new instance of TensorDiag @@ -1634,7 +1586,6 @@ public TensorDiag tensorDiag(Operand diagonal) { * tf.diag_part(input) ==> [1, 2, 3, 4] * * - * @param data type for {@code diagonal} output * @param input Rank k tensor where k is even and not zero. * @param data type for {@code DiagPart} output and operands * @return a new instance of TensorDiagPart @@ -1648,7 +1599,6 @@ public TensorDiagPart tensorDiagPart(Operand input) { * The output {@code y} has the same rank as {@code x}. The shapes of {@code x} and {@code y} satisfy: * {@code y.shape[i] == x.shape[perm[i]] for i in [0, 1, ..., rank(x) - 1]} * - * @param data type for {@code y} output * @param x The x value * @param perm The perm value * @param data type for {@code Transpose} output and operands @@ -1703,7 +1653,6 @@ public Transpose transpose(Operand x, Operand * - * @param data type for {@code output} output * @param matrix Shape is {@code [..., M, M]}. * @param rhs Shape is {@code [..., M, K]}. * @param options carries optional attribute values @@ -1719,7 +1668,6 @@ public TriangularSolve triangularSolve(Operand matrix, O * Calculate product with tridiagonal matrix. * Calculates product of two matrices, where left matrix is a tridiagonal matrix. * - * @param data type for {@code output} output * @param superdiag Tensor of shape {@code [..., 1, M]}, representing superdiagonals of * tri-diagonal matrices to the left of multiplication. Last element is ignored. * @param maindiag Tensor of shape {@code [..., 1, M]}, representing main diagonals of tri-diagonal @@ -1746,7 +1694,6 @@ public TridiagonalMatMul tridiagonalMatMul(Operand super * library is used: https://docs.nvidia.com/cuda/cusparse/index.html#gtsv * Partial pivoting is not yet supported by XLA backends. * - * @param data type for {@code output} output * @param diagonals Tensor of shape {@code [..., 3, M]} whose innermost 2 dimensions represent the * tridiagonal matrices with three rows being the superdiagonal, diagonals, and * subdiagonals, in order. The last element of the superdiagonal and the first diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgSparseOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgSparseOps.java index 0e0e2f25664..7210249ba1f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgSparseOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/LinalgSparseOps.java @@ -42,7 +42,7 @@ /** * An API for building {@code linalg.sparse} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class LinalgSparseOps { private final Scope scope; @@ -59,7 +59,6 @@ public final class LinalgSparseOps { * This op is meant only for debugging / testing, and its interface is not expected * to be stable. * - * @param data type for {@code values} output * @param csrSparseMatrix A batched CSRSparseMatrix. * @param index The index in {@code csr_sparse_matrix}'s batch. * @param type The value of the type attribute @@ -74,7 +73,6 @@ public CSRSparseMatrixComponents cSRSparseMatrixComponents( /** * Convert a (possibly batched) CSRSparseMatrix to dense. * - * @param data type for {@code dense_output} output * @param sparseInput A batched CSRSparseMatrix. * @param type The value of the type attribute * @param data type for {@code CSRSparseMatrixToDense} output and operands @@ -88,7 +86,6 @@ public CSRSparseMatrixToDense cSRSparseMatrixToDense( /** * Converts a (possibly batched) CSRSparesMatrix to a SparseTensor. * - * @param data type for {@code values} output * @param sparseMatrix A (possibly batched) CSRSparseMatrix. * @param type The value of the type attribute * @param data type for {@code CSRSparseMatrixToSparseTensor} output and operands @@ -152,7 +149,6 @@ public SparseMatrixAdd sparseMatrixAdd(Operand * - * @param data type for {@code output} output * @param a A CSRSparseMatrix. * @param b A dense tensor. * @param options carries optional attribute values diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java index b9002b321d9..d3dcfc686ad 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathOps.java @@ -147,7 +147,7 @@ /** * An API for building {@code math} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class MathOps { public final MathSpecialOps special; @@ -168,7 +168,6 @@ public final class MathOps { * value of each element in {@code x}. For example, if x is an input element and y is * an output element, this operation computes \(y = |x|\). * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Abs} output and operands * @return a new instance of Abs @@ -186,7 +185,6 @@ public Abs abs(Operand x) { *

Unlike the original {@code accumulate_n}, {@code accumulate_n_v2} is differentiable. *

Returns a {@code Tensor} of same shape and type as the elements of {@code inputs}. * - * @param data type for {@code sum} output * @param inputs A list of {@code Tensor} objects, each with same shape and type. * @param shape Shape of elements of {@code inputs}. * @param data type for {@code AccumulateNV2} output and operands @@ -201,7 +199,6 @@ public AccumulateN accumulateN(Iterable> inputs, * Provided an input tensor, the {@code tf.math.acos} operation returns the inverse cosine of each element of the tensor. If {@code y = tf.math.cos(x)} then, {@code x = tf.math.acos(y)}. *

Input range is {@code [-1, 1]} and the output has a range of {@code [0, pi]}. * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Acos} output and operands * @return a new instance of Acos @@ -219,7 +216,6 @@ public Acos acos(Operand x) { * tf.math.acosh(x) ==> [nan nan 0. 0.62236255 5.9914584 9.903487 inf] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Acosh} output and operands * @return a new instance of Acosh @@ -235,7 +231,6 @@ public Acosh acosh(Operand x) { *

Given two input tensors, the {@code tf.add} operation computes the sum for every element in the tensor. *

Both input and output have a range {@code (-inf, inf)}. * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Add} output and operands @@ -253,7 +248,6 @@ public Add add(Operand x, Operand y) { * tf.math.add_n(x) ==> 26 * * - * @param data type for {@code sum} output * @param inputs The inputs value * @param data type for {@code AddN} output and operands * @return a new instance of AddN @@ -278,7 +272,6 @@ public AddN addN(Iterable> inputs) { * Equivalent to np.angle. *
{@literal @}end_compatibility * - * @param data type for {@code output} output * @param input The input value * @return a new instance of Angle, with default output types */ @@ -302,7 +295,6 @@ public Angle angle(Operand input) { * Equivalent to np.angle. *
{@literal @}end_compatibility * - * @param data type for {@code output} output * @param input The input value * @param Tout The value of the Tout attribute * @param data type for {@code Angle} output and operands @@ -339,7 +331,6 @@ public ApproximateEqual approximateEqual(Operand x, Operand * # here a[4] = 166.32 which is the largest element of a across axis 0 * * - * @param data type for {@code output} output * @param input The input value * @param dimension int16, int32 or int64, must be in the range {@code [-rank(input), rank(input))}. * Describes which dimension of the input Tensor to reduce across. For vectors, @@ -364,7 +355,6 @@ public ArgMax argMax(Operand input, * # here a[4] = 166.32 which is the largest element of a across axis 0 * * - * @param data type for {@code output} output * @param input The input value * @param dimension int16, int32 or int64, must be in the range {@code [-rank(input), rank(input))}. * Describes which dimension of the input Tensor to reduce across. For vectors, @@ -391,7 +381,6 @@ public ArgMax argMax(Operand input, * # here a[0] = 1 which is the smallest element of a across axis 0 * * - * @param data type for {@code output} output * @param input The input value * @param dimension int32 or int64, must be in the range {@code [-rank(input), rank(input))}. * Describes which dimension of the input Tensor to reduce across. For vectors, @@ -416,7 +405,6 @@ public ArgMin argMin(Operand input, * # here a[0] = 1 which is the smallest element of a across axis 0 * * - * @param data type for {@code output} output * @param input The input value * @param dimension int32 or int64, must be in the range {@code [-rank(input), rank(input))}. * Describes which dimension of the input Tensor to reduce across. For vectors, @@ -445,7 +433,6 @@ public ArgMin argMin(Operand input, * tf.math.asin(y) # [1.047, 0.785] = x * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Asin} output and operands * @return a new instance of Asin @@ -464,7 +451,6 @@ public Asin asin(Operand x) { * tf.math.asinh(x) ==> [-inf -1.4436355 -0.4812118 0.8813736 1.0159732 5.991471 9.903487 inf] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Asinh} output and operands * @return a new instance of Asinh @@ -488,7 +474,6 @@ public Asinh asinh(Operand x) { * tf.math.atan(y) # [1.047, 0.785] = x * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Atan} output and operands * @return a new instance of Atan @@ -516,7 +501,6 @@ public Atan atan(Operand x) { * * * - * @param data type for {@code z} output * @param y The y value * @param x The x value * @param data type for {@code Atan2} output and operands @@ -538,7 +522,6 @@ public Atan2 atan2(Operand y, Operand x) { * tf.math.atanh(x) ==> [nan -inf -0.54930615 inf 0. 0.54930615 nan nan] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Atanh} output and operands * @return a new instance of Atanh @@ -550,7 +533,6 @@ public Atanh atanh(Operand x) { /** * The BesselI0 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselI0} output and operands * @return a new instance of BesselI0 @@ -562,7 +544,6 @@ public BesselI0 besselI0(Operand x) { /** * The BesselI0e operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselI0e} output and operands * @return a new instance of BesselI0e @@ -574,7 +555,6 @@ public BesselI0e besselI0e(Operand x) { /** * The BesselI1 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselI1} output and operands * @return a new instance of BesselI1 @@ -586,7 +566,6 @@ public BesselI1 besselI1(Operand x) { /** * The BesselI1e operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselI1e} output and operands * @return a new instance of BesselI1e @@ -604,7 +583,6 @@ public BesselI1e besselI1e(Operand x) { *

is the incomplete beta function and \(B(a, b)\) is the complete * beta function. * - * @param data type for {@code z} output * @param a The a value * @param b The b value * @param x The x value @@ -624,7 +602,6 @@ public Betainc betainc(Operand a, Operand b, Operan * {@code i}. *

Values in {@code arr} outside of the range [0, size) are ignored. * - * @param data type for {@code bins} output * @param arr int32 {@code Tensor}. * @param sizeOutput non-negative int32 scalar {@code Tensor}. * @param weights is an int32, int64, float32, or float64 {@code Tensor} with the same @@ -641,7 +618,6 @@ public Bincount bincount(Operand arr, Operand data type for {@code y} output * @param x The x value * @param data type for {@code Ceil} output and operands * @return a new instance of Ceil @@ -667,7 +643,6 @@ public Ceil ceil(Operand x) { * * * - * @param data type for {@code y} output * @param x The x value * @return a new instance of ComplexAbs, with default output types */ @@ -692,7 +667,6 @@ public ComplexAbs complexAbs(Operand x) { * * * - * @param data type for {@code y} output * @param x The x value * @param Tout The value of the Tout attribute * @param data type for {@code ComplexAbs} output and operands @@ -715,7 +689,6 @@ public ComplexAbs complexAbs(Operand x, * tf.conj(input) ==> [-2.25 - 4.75j, 3.25 - 5.75j] * * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code Conj} output and operands * @return a new instance of Conj @@ -735,7 +708,6 @@ public Conj conj(Operand input) { * tf.math.cos(x) ==> [nan -0.91113025 0.87758255 0.5403023 0.36235774 0.48718765 -0.95215535 nan] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Cos} output and operands * @return a new instance of Cos @@ -754,7 +726,6 @@ public Cos cos(Operand x) { * tf.math.cosh(x) ==> [inf 4.0515420e+03 1.1276259e+00 1.5430807e+00 1.8106556e+00 3.7621956e+00 1.1013233e+04 inf] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Cosh} output and operands * @return a new instance of Cosh @@ -786,7 +757,6 @@ public Cosh cosh(Operand x) { * tf.cumprod([a, b, c], exclusive=True, reverse=True) # => [b * c, c, 1] * * - * @param data type for {@code out} output * @param x A {@code Tensor}. Must be one of the following types: {@code float32}, {@code float64}, * {@code int64}, {@code int32}, {@code uint8}, {@code uint16}, {@code int16}, {@code int8}, {@code complex64}, * {@code complex128}, {@code qint8}, {@code quint8}, {@code qint32}, {@code half}. @@ -824,7 +794,6 @@ public Cumprod cumprod(Operand x, Operand * - * @param data type for {@code out} output * @param x A {@code Tensor}. Must be one of the following types: {@code float32}, {@code float64}, * {@code int64}, {@code int32}, {@code uint8}, {@code uint16}, {@code int16}, {@code int8}, {@code complex64}, * {@code complex128}, {@code qint8}, {@code quint8}, {@code qint32}, {@code half}. @@ -858,7 +827,6 @@ public Cumsum cumsum(Operand x, OperandBy setting the {@code reverse} kwarg to {@code True}, the cumulative log-sum-exp is performed in the * opposite direction. * - * @param data type for {@code out} output * @param x A {@code Tensor}. Must be one of the following types: {@code float16}, {@code float32}, {@code float64}. * @param axis A {@code Tensor} of type {@code int32} (default: 0). Must be in the range * {@code [-rank(x), rank(x))}. @@ -880,7 +848,6 @@ public CumulativeLogsumexp cumulativeLogsumexp(Operand * {@code i}. *

Values in {@code arr} outside of the range [0, size) are ignored. * - * @param data type for {@code output} output * @param input 1D or 2D int {@code Tensor}. * @param sizeOutput non-negative int scalar {@code Tensor}. * @param weights is an int32, int64, float32, or float64 {@code Tensor} with the same @@ -900,7 +867,6 @@ public DenseBincount denseBincount(Ope * Computes Psi, the derivative of Lgamma (the log of the absolute value of * {@code Gamma(x)}), element-wise. * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Digamma} output and operands * @return a new instance of Digamma @@ -914,7 +880,6 @@ public Digamma digamma(Operand x) { * NOTE: {@code math.Div} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Div} output and operands @@ -929,7 +894,6 @@ public Div div(Operand x, Operand y) { * NOTE: {@code math.DivNoNan} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code DivNoNan} output and operands @@ -966,7 +930,6 @@ public Equal equal(Operand x, Operand y, Equal.Options.. /** * Computes the Gauss error function of {@code x} element-wise. In statistics, for non-negative values of $x$, the error function has the following interpretation: for a random variable $Y$ that is normally distributed with mean 0 and variance $1/\sqrt{2}$, $erf(x)$ is the probability that $Y$ falls in the range $[−x, x]$. * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Erf} output and operands * @return a new instance of Erf @@ -978,7 +941,6 @@ public Erf erf(Operand x) { /** * Computes the complementary error function of {@code x} element-wise. * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Erfc} output and operands * @return a new instance of Erfc @@ -990,7 +952,6 @@ public Erfc erfc(Operand x) { /** * The Erfinv operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Erfinv} output and operands * @return a new instance of erfinv @@ -1023,7 +984,6 @@ public erfinv erfinv(Operand x) { * tf.math.exp(x) ==> 1.4686939399158851+2.2873552871788423j * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Exp} output and operands * @return a new instance of Exp @@ -1047,7 +1007,6 @@ public Exp exp(Operand x) { * tf.math.expm1(x) ==> (0.46869393991588515+2.2873552871788423j) * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Expm1} output and operands * @return a new instance of Expm1 @@ -1068,7 +1027,6 @@ public Fact fact() { /** * Returns element-wise largest integer not greater than x. * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Floor} output and operands * @return a new instance of Floor @@ -1082,7 +1040,6 @@ public Floor floor(Operand x) { * NOTE: {@code math.FloorDiv} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code FloorDiv} output and operands @@ -1100,7 +1057,6 @@ public FloorDiv floorDiv(Operand x, Operand y) { *

NOTE: {@code math.FloorMod} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code FloorMod} output and operands @@ -1168,7 +1124,6 @@ public GreaterEqual greaterEqual(Operand x, Operand y) *

Note, above {@code Q(a, x)} ({@code Igammac}) is the upper regularized complete * Gamma function. * - * @param data type for {@code z} output * @param a The a value * @param x The x value * @param data type for {@code Igamma} output and operands @@ -1181,7 +1136,6 @@ public Igamma igamma(Operand a, Operand x) { /** * Computes the gradient of {@code igamma(a, x)} wrt {@code a}. * - * @param data type for {@code z} output * @param a The a value * @param x The x value * @param data type for {@code IgammaGradA} output and operands @@ -1201,7 +1155,6 @@ public IgammaGradA igammaGradA(Operand a, Operand x *

Note, above {@code P(a, x)} ({@code Igamma}) is the lower regularized complete * Gamma function. * - * @param data type for {@code z} output * @param a The a value * @param x The x value * @param data type for {@code Igammac} output and operands @@ -1223,7 +1176,6 @@ public Igammac igammac(Operand a, Operand x) { * tf.imag(input) ==> [4.75, 5.75] * * - * @param data type for {@code output} output * @param input The input value * @return a new instance of Imag, with default output types */ @@ -1243,7 +1195,6 @@ public Imag imag(Operand input) { * tf.imag(input) ==> [4.75, 5.75] * * - * @param data type for {@code output} output * @param input The input value * @param Tout The value of the Tout attribute * @param data type for {@code Imag} output and operands @@ -1267,7 +1218,6 @@ public Imag imag(Operand input, Class * invert_permutation(x) ==> [2, 4, 3, 0, 1] * * - * @param data type for {@code y} output * @param x 1-D. * @param data type for {@code InvertPermutation} output and operands * @return a new instance of InvertPermutation @@ -1388,7 +1338,6 @@ public LessEqual lessEqual(Operand x, Operand y) { * tf.math.lgamma(x) ==> [inf, 0.5723649, 0., 2.4537368, inf, -4.6477685] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Lgamma} output and operands * @return a new instance of Lgamma @@ -1406,7 +1355,6 @@ public Lgamma lgamma(Operand x) { * tf.math.log(x) ==> [-inf, -0.6931472, 0. , 1.609438] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Log} output and operands * @return a new instance of Log @@ -1424,7 +1372,6 @@ public Log log(Operand x) { * tf.math.log1p(x) ==> [0., 0.4054651, 0.6931472, 1.7917595] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Log1p} output and operands * @return a new instance of Log1p @@ -1474,7 +1421,6 @@ public LogicalOr logicalOr(Operand x, Operand y) { * NOTE: {@code math.Maximum} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Maximum} output and operands @@ -1491,7 +1437,6 @@ public Maximum maximum(Operand x, Operand y) { * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -1509,7 +1454,6 @@ public Mean mean(Operand input, OperandNOTE: {@code math.Minimum} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Minimum} output and operands @@ -1526,7 +1470,6 @@ public Minimum minimum(Operand x, Operand y) { *

NOTE: {@code math.Mod} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Mod} output and operands @@ -1541,7 +1484,6 @@ public Mod mod(Operand x, Operand y) { * NOTE: {@code math.Mul} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Mul} output and operands @@ -1556,7 +1498,6 @@ public Mul mul(Operand x, Operand y) { * NOTE: {@code math.MulNoNan} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code MulNoNan} output and operands @@ -1569,7 +1510,6 @@ public MulNoNan mulNoNan(Operand x, Operand y) { /** * The Ndtri operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Ndtri} output and operands * @return a new instance of Ndtri @@ -1582,7 +1522,6 @@ public Ndtri ndtri(Operand x) { * Computes numerical negative value element-wise. * I.e., \(y = -x\). * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Neg} output and operands * @return a new instance of Neg @@ -1599,7 +1538,6 @@ public Neg neg(Operand x) { * Equivalent to C++ std::nextafter function. *
{@literal @}end_compatibility * - * @param data type for {@code output} output * @param x1 The x1 value * @param x2 The x2 value * @param data type for {@code NextAfter} output and operands @@ -1632,7 +1570,6 @@ public NotEqual notEqual(Operand x, Operand y, *

where \(\psi(x)\) is the digamma function. * The polygamma function is defined only for non-negative integer orders \a\. * - * @param data type for {@code z} output * @param a The a value * @param x The x value * @param data type for {@code Polygamma} output and operands @@ -1667,7 +1604,6 @@ public PopulationCount populationCount(Operand x) { * tf.pow(x, y) ==> [[256, 65536], [9, 27]] * * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Pow} output and operands @@ -1680,7 +1616,6 @@ public Pow pow(Operand x, Operand y) { /** * Returns x + y element-wise, working on quantized buffers. * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param minX The float value that the lowest quantized {@code x} value represents. @@ -1700,7 +1635,6 @@ public QuantizedAdd quantizedAdd(Operand data type for {@code z} output * @param x The x value * @param y The y value * @param minX The float value that the lowest quantized {@code x} value represents. @@ -1729,7 +1663,6 @@ public QuantizedMul quantizedMul(Operand * - * @param data type for {@code output} output * @param input The input value * @return a new instance of Real, with default output types */ @@ -1749,7 +1682,6 @@ public Real real(Operand input) { * tf.real(input) ==> [-2.25, 3.25] * * - * @param data type for {@code output} output * @param input The input value * @param Tout The value of the Tout attribute * @param data type for {@code Real} output and operands @@ -1765,7 +1697,6 @@ public Real real(Operand input, Class *

NOTE: {@code Div} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code RealDiv} output and operands @@ -1779,7 +1710,6 @@ public RealDiv realDiv(Operand x, Operand y) { * Computes the reciprocal of x element-wise. * I.e., \(y = 1 / x\). * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Reciprocal} output and operands * @return a new instance of Reciprocal @@ -1793,7 +1723,6 @@ public Reciprocal reciprocal(Operand x) { * Specifically, {@code grad = -dy * y*y}, where {@code y = 1/x}, and {@code dy} * is the corresponding input gradient. * - * @param data type for {@code z} output * @param y The y value * @param dy The dy value * @param data type for {@code ReciprocalGrad} output and operands @@ -1822,7 +1751,6 @@ public RequantizationRangePerChannel requantizationRangePerChannel( /** * Requantizes input with min and max values known per channel. * - * @param data type for {@code output} output * @param input The original input tensor. * @param inputMin The minimum value of the input tensor * @param inputMax The maximum value of the input tensor. @@ -1850,7 +1778,6 @@ public RequantizePerChannel requantizePerChannel( * rint([-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0]) ==> [-2., -2., -0., 0., 2., 2., 2.] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Rint} output and operands * @return a new instance of Rint @@ -1864,7 +1791,6 @@ public Rint rint(Operand x) { * Rounds half to even. Also known as bankers rounding. If you want to round * according to the current system rounding mode use std::cint. * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Round} output and operands * @return a new instance of Round @@ -1877,7 +1803,6 @@ public Round round(Operand x) { * Computes reciprocal of square root of x element-wise. * I.e., \(y = 1 / \sqrt{x}\). * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Rsqrt} output and operands * @return a new instance of Rsqrt @@ -1891,7 +1816,6 @@ public Rsqrt rsqrt(Operand x) { * Specifically, {@code grad = dy * -0.5 * y^3}, where {@code y = rsqrt(x)}, and {@code dy} * is the corresponding input gradient. * - * @param data type for {@code z} output * @param y The y value * @param dy The dy value * @param data type for {@code RsqrtGrad} output and operands @@ -1942,7 +1866,6 @@ public RsqrtGrad rsqrtGrad(Operand y, Operand dy) { * * * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s * first dimension. Values should be sorted and can be repeated. @@ -1989,7 +1912,6 @@ public SegmentMax segmentMax(Operand data, * * * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s * first dimension. Values should be sorted and can be repeated. @@ -2044,7 +1966,6 @@ public SegmentMean segmentMean(Operand data, * * * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s * first dimension. Values should be sorted and can be repeated. @@ -2093,7 +2014,6 @@ public SegmentMin segmentMin(Operand data, * * * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s * first dimension. Values should be sorted and can be repeated. @@ -2119,9 +2039,7 @@ public SegmentProd segmentProd(Operand data, * that {@code segment_ids[j] == i}. *

If the sum is empty for a given segment ID {@code i}, {@code output[i] = 0}. *

Note that this op is currently only supported with jit_compile=True. - * * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A 1-D tensor whose size is equal to the size of {@code data}'s * first dimension. Values should be sorted and can be repeated. @@ -2141,7 +2059,6 @@ public SegmentSum segmentSum(Operand data, * Computes sigmoid of {@code x} element-wise. * Specifically, {@code y = 1 / (1 + exp(-x))}. * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Sigmoid} output and operands * @return a new instance of Sigmoid @@ -2155,7 +2072,6 @@ public Sigmoid sigmoid(Operand x) { * Specifically, {@code grad = dy * y * (1 - y)}, where {@code y = sigmoid(x)}, and * {@code dy} is the corresponding input gradient. * - * @param data type for {@code z} output * @param y The y value * @param dy The dy value * @param data type for {@code SigmoidGrad} output and operands @@ -2179,7 +2095,6 @@ public SigmoidGrad sigmoidGrad(Operand y, Operand dy) * * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Sign} output and operands * @return a new instance of Sign @@ -2198,7 +2113,6 @@ public Sign sign(Operand x) { * tf.math.sin(x) ==> [nan -0.4121185 -0.47942555 0.84147096 0.9320391 -0.87329733 -0.54402107 nan] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Sin} output and operands * @return a new instance of Sin @@ -2217,7 +2131,6 @@ public Sin sin(Operand x) { * tf.math.sinh(x) ==> [-inf -4.0515420e+03 -5.2109528e-01 1.1752012e+00 1.5094614e+00 3.6268604e+00 1.1013232e+04 inf] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Sinh} output and operands * @return a new instance of Sinh @@ -2231,7 +2144,6 @@ public Sinh sinh(Operand x) { * Creates a Sobol sequence with {@code num_results} samples. Each sample has dimension * {@code dim}. Skips the first {@code skip} samples. * - * @param data type for {@code samples} output * @param dim Positive scalar {@code Tensor} representing each sample's dimension. * @param numResults Positive scalar {@code Tensor} of dtype int32. The number of Sobol points to return * in the output. @@ -2249,7 +2161,6 @@ public SobolSample sobolSample(Operand dim, Operand nu * Creates a Sobol sequence with {@code num_results} samples. Each sample has dimension * {@code dim}. Skips the first {@code skip} samples. * - * @param data type for {@code samples} output * @param dim Positive scalar {@code Tensor} representing each sample's dimension. * @param numResults Positive scalar {@code Tensor} of dtype int32. The number of Sobol points to return * in the output. @@ -2267,7 +2178,6 @@ public SobolSample sobolSample(Operand dim, /** * The Softplus operation * - * @param data type for {@code activations} output * @param features The features value * @param data type for {@code Softplus} output and operands * @return a new instance of Softplus @@ -2279,7 +2189,6 @@ public Softplus softplus(Operand features) { /** * Computes softplus gradients for a softplus operation. * - * @param data type for {@code backprops} output * @param gradients The backpropagated gradients to the corresponding softplus operation. * @param features The features passed as input to the corresponding softplus operation. * @param data type for {@code SoftplusGrad} output and operands @@ -2294,7 +2203,6 @@ public SoftplusGrad softplusGrad(Operand gradients, * Computes square root of x element-wise. * I.e., \(y = \sqrt{x} = x^{1/2}\). * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Sqrt} output and operands * @return a new instance of Sqrt @@ -2308,7 +2216,6 @@ public Sqrt sqrt(Operand x) { * Specifically, {@code grad = dy * 0.5 / y}, where {@code y = sqrt(x)}, and {@code dy} * is the corresponding input gradient. * - * @param data type for {@code z} output * @param y The y value * @param dy The dy value * @param data type for {@code SqrtGrad} output and operands @@ -2322,7 +2229,6 @@ public SqrtGrad sqrtGrad(Operand y, Operand dy) { * Computes square of x element-wise. * I.e., \(y = x * x = x^2\). * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Square} output and operands * @return a new instance of Square @@ -2336,7 +2242,6 @@ public Square square(Operand x) { * NOTE: {@code math.SquaredDifference} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code SquaredDifference} output and operands @@ -2351,7 +2256,6 @@ public SquaredDifference squaredDifference(Operand x, Op * NOTE: {@code math.Sub} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Sub} output and operands @@ -2372,7 +2276,6 @@ public Sub sub(Operand x, Operand y) { * tf.math.tan(x) ==> [nan 0.45231566 -0.5463025 1.5574077 2.572152 -1.7925274 0.32097113 nan] * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Tan} output and operands * @return a new instance of Tan @@ -2398,7 +2301,6 @@ public Tan tan(Operand x) { * * * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Tanh} output and operands * @return a new instance of Tanh @@ -2412,7 +2314,6 @@ public Tanh tanh(Operand x) { * Specifically, {@code grad = dy * (1 - y*y)}, where {@code y = tanh(x)}, and {@code dy} * is the corresponding input gradient. * - * @param data type for {@code z} output * @param y The y value * @param dy The dy value * @param data type for {@code TanhGrad} output and operands @@ -2431,7 +2332,6 @@ public TanhGrad tanhGrad(Operand y, Operand dy) { *

NOTE: {@code math.TruncateDiv} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code TruncateDiv} output and operands @@ -2447,7 +2347,6 @@ public TruncateDiv truncateDiv(Operand x, Operand y) *

NOTE: {@code math.TruncateMod} supports broadcasting. More about broadcasting * here * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code TruncateMod} output and operands @@ -2475,7 +2374,6 @@ public TruncateMod truncateMod(Operand x, Operand y * if {@code operand.quantization_axis} >= 0 and {@code output.quantization_axis} >= 0, * {@code operand.dims} - {@code operand.quantization_axis} must be equal to {@code output.dims} - {@code output.quantization_axis}. * - * @param data type for {@code output} output * @param lhs Must be a quantized tensor. * @param rhs Must be a quantized tensor. * @param lhsScales The float value(s) used as scale factors when quantizing the original data that {@code lhs} represents. @@ -2547,7 +2445,6 @@ public UniformQuantizedAdd uniformQuantizedAdd(Operand * * * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}. * The values must be less than {@code num_segments}. @@ -2594,7 +2491,6 @@ public UnsortedSegmentMax unsortedSegmentMax(Operand d * out-of-bound indices or outputting a tensor with a 0 stored in the first * dimension of its shape if {@code num_segments} is 0. * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}. * The values must be less than {@code num_segments}. @@ -2640,7 +2536,6 @@ public UnsortedSegmentMin unsortedSegmentMin(Operand d * out-of-bound indices or outputting a tensor with a 0 stored in the first * dimension of its shape if {@code num_segments} is 0. * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}. * The values must be less than {@code num_segments}. @@ -2689,7 +2584,6 @@ public UnsortedSegmentProd unsortedSegmentProd(Operand d * * * - * @param data type for {@code output} output * @param data The data value * @param segmentIds A tensor whose shape is a prefix of {@code data.shape}. * The values must be less than {@code num_segments}. @@ -2707,7 +2601,6 @@ public UnsortedSegmentSum unsortedSegmentSum(Operand dat /** * Returns 0 if x == 0, and x / y otherwise, elementwise. * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Xdivy} output and operands @@ -2720,7 +2613,6 @@ public Xdivy xdivy(Operand x, Operand y) { /** * Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise. * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Xlog1py} output and operands @@ -2733,7 +2625,6 @@ public Xlog1py xlog1py(Operand x, Operand y) { /** * Returns 0 if x == 0, and x * log(y) otherwise, elementwise. * - * @param data type for {@code z} output * @param x The x value * @param y The y value * @param data type for {@code Xlogy} output and operands @@ -2748,7 +2639,6 @@ public Xlogy xlogy(Operand x, Operand y) { * The Hurwitz zeta function is defined as: *

\(\zeta(x, q) = \sum_{n=0}^{\infty} (q + n)^{-x}\) * - * @param data type for {@code z} output * @param x The x value * @param q The q value * @param data type for {@code Zeta} output and operands diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathSpecialOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathSpecialOps.java index 569c20e2c02..e486615af1b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathSpecialOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/MathSpecialOps.java @@ -36,7 +36,7 @@ /** * An API for building {@code math.special} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class MathSpecialOps { private final Scope scope; @@ -51,7 +51,6 @@ public final class MathSpecialOps { /** * The BesselJ0 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselJ0} output and operands * @return a new instance of BesselJ0 @@ -63,7 +62,6 @@ public BesselJ0 besselJ0(Operand x) { /** * The BesselJ1 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselJ1} output and operands * @return a new instance of BesselJ1 @@ -75,7 +73,6 @@ public BesselJ1 besselJ1(Operand x) { /** * The BesselK0 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselK0} output and operands * @return a new instance of BesselK0 @@ -87,7 +84,6 @@ public BesselK0 besselK0(Operand x) { /** * The BesselK0e operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselK0e} output and operands * @return a new instance of BesselK0e @@ -99,7 +95,6 @@ public BesselK0e besselK0e(Operand x) { /** * The BesselK1 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselK1} output and operands * @return a new instance of BesselK1 @@ -111,7 +106,6 @@ public BesselK1 besselK1(Operand x) { /** * The BesselK1e operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselK1e} output and operands * @return a new instance of BesselK1e @@ -123,7 +117,6 @@ public BesselK1e besselK1e(Operand x) { /** * The BesselY0 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselY0} output and operands * @return a new instance of BesselY0 @@ -135,7 +128,6 @@ public BesselY0 besselY0(Operand x) { /** * The BesselY1 operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code BesselY1} output and operands * @return a new instance of BesselY1 @@ -147,7 +139,6 @@ public BesselY1 besselY1(Operand x) { /** * The Dawsn operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Dawsn} output and operands * @return a new instance of Dawsn @@ -159,7 +150,6 @@ public Dawsn dawsn(Operand x) { /** * The Expint operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Expint} output and operands * @return a new instance of Expint @@ -171,7 +161,6 @@ public Expint expint(Operand x) { /** * The FresnelCos operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code FresnelCos} output and operands * @return a new instance of FresnelCos @@ -183,7 +172,6 @@ public FresnelCos fresnelCos(Operand x) { /** * The FresnelSin operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code FresnelSin} output and operands * @return a new instance of FresnelSin @@ -195,7 +183,6 @@ public FresnelSin fresnelSin(Operand x) { /** * The Spence operation * - * @param data type for {@code y} output * @param x The x value * @param data type for {@code Spence} output and operands * @return a new instance of Spence diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java index c4838b02a39..9859a308562 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/NnOps.java @@ -138,7 +138,7 @@ /** * An API for building {@code nn} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class NnOps { private final Scope scope; @@ -155,7 +155,6 @@ public final class NnOps { * Each entry in {@code output} is the mean of the corresponding size {@code ksize} * window in {@code value}. * - * @param data type for {@code output} output * @param value 4-D with shape {@code [batch, height, width, channels]}. * @param ksize The size of the sliding window for each dimension of {@code value}. * @param strides The stride of the sliding window for each dimension of {@code value}. @@ -174,7 +173,6 @@ public AvgPool avgPool(Operand value, List ksize * Each entry in {@code output} is the mean of the corresponding size {@code ksize} window in * {@code value}. * - * @param data type for {@code output} output * @param input Shape {@code [batch, depth, rows, cols, channels]} tensor to pool over. * @param ksize 1-D tensor of length 5. The size of the window for each dimension of * the input tensor. Must have {@code ksize[0] = ksize[4] = 1}. @@ -193,7 +191,6 @@ public AvgPool3d avgPool3d(Operand input, List k /** * Computes gradients of average pooling function. * - * @param data type for {@code output} output * @param origInputShape The original input dimensions. * @param grad Output backprop of shape {@code [batch, depth, rows, cols, channels]}. * @param ksize 1-D tensor of length 5. The size of the window for each dimension of @@ -214,7 +211,6 @@ public AvgPool3dGrad avgPool3dGrad(Operand origIn /** * Computes gradients of the average pooling function. * - * @param data type for {@code output} output * @param origInputShape 1-D. Shape of the original input to {@code avg_pool}. * @param grad 4-D with shape {@code [batch, height, width, channels]}. Gradients w.r.t. * the output of {@code avg_pool}. @@ -235,7 +231,6 @@ public AvgPoolGrad avgPoolGrad(Operand origInputS * Batch normalization. * This op is deprecated. Prefer {@code tf.nn.batch_normalization}. * - * @param data type for {@code result} output * @param t A 4D input Tensor. * @param m A 1D mean Tensor with size matching the last dimension of t. * This is the first output from tf.nn.moments, @@ -264,7 +259,6 @@ public BatchNormWithGlobalNormalization batchNormWithGlobal * Gradients for batch normalization. * This op is deprecated. See {@code tf.nn.batch_normalization}. * - * @param data type for {@code dx} output * @param t A 4D input Tensor. * @param m A 1D mean Tensor with size matching the last dimension of t. * This is the first output from tf.nn.moments, @@ -293,7 +287,6 @@ public BatchNormWithGlobalNormalizationGrad batchNormWithGl * This is a special case of {@code tf.add} where {@code bias} is restricted to be 1-D. * Broadcasting is supported, so {@code value} may have any number of dimensions. * - * @param data type for {@code output} output * @param value Any number of dimensions. * @param bias 1-D with size the last dimension of {@code value}. * @param options carries optional attribute values @@ -311,7 +304,6 @@ public BiasAdd biasAdd(Operand value, Operand bias, * For NHWC data format, the feature dimension is the last. For NCHW data format, * the feature dimension is the third-to-last. * - * @param data type for {@code output} output * @param outBackprop Any number of dimensions. * @param options carries optional attribute values * @param data type for {@code BiasAddGrad} output and operands @@ -345,7 +337,6 @@ public BiasAddGrad biasAddGrad(Operand outBackprop, * all gate-related outputs should be reordered. * * - * @param data type for {@code i} output * @param seqLenMax Maximum time length actually used by this input. Outputs are padded * with zeros beyond this length. * @param x The sequence input to the LSTM, shape (timelen, batch_size, num_inputs). @@ -370,7 +361,6 @@ public BlockLSTM blockLSTM(Operand seqLenMax, Ope * Computes the LSTM cell backward propagation for the entire time sequence. * This implementation is to be used in conjunction of BlockLSTMV2. * - * @param data type for {@code x_grad} output * @param seqLenMax Maximum time length actually used by this input. Outputs are padded * with zeros beyond this length. * @param x The sequence input to the LSTM, shape (timelen, batch_size, num_inputs). @@ -445,7 +435,6 @@ public ComputeAccidentalHits computeAccidentalHits(Operand trueClasses, * General function for computing a N-D convolution. It is required that * {@code 1 <= N <= 3}. * - * @param data type for {@code output} output * @param input Tensor of type T and shape {@code batch_shape + spatial_shape + [in_channels]} in the * case that {@code channels_last_format = true} or shape * {@code batch_shape + [in_channels] + spatial_shape} if {@code channels_last_format = false}. @@ -490,7 +479,6 @@ public Conv conv(Operand input, Operand filter, Lis *

Must have {@code strides[0] = strides[3] = 1}. For the most common case of the same * horizontal and vertices strides, {@code strides = [1, stride, stride, 1]}. * - * @param data type for {@code output} output * @param input A 4-D tensor. The dimension order is interpreted according to the value * of {@code data_format}, see below for details. * @param filter A 4-D tensor of shape @@ -511,7 +499,6 @@ public Conv2d conv2d(Operand input, Operand filter, /** * Computes the gradients of convolution with respect to the filter. * - * @param data type for {@code output} output * @param input 4-D with shape {@code [batch, in_height, in_width, in_channels]}. * @param filterSizes An integer vector representing the tensor shape of {@code filter}, * where {@code filter} is a 4-D @@ -535,7 +522,6 @@ public Conv2dBackpropFilter conv2dBackpropFilter(Operand< /** * Computes the gradients of convolution with respect to the input. * - * @param data type for {@code output} output * @param inputSizes An integer vector representing the shape of {@code input}, * where {@code input} is a 4-D {@code [batch, height, width, channels]} tensor. * @param filter 4-D with shape @@ -563,7 +549,6 @@ public Conv2dBackpropInput conv2dBackpropInput(OperandOur Conv3D implements a form of cross-correlation. * - * @param data type for {@code output} output * @param input Shape {@code [batch, in_depth, in_height, in_width, in_channels]}. * @param filter Shape {@code [filter_depth, filter_height, filter_width, in_channels, out_channels]}. {@code in_channels} must match between {@code input} and {@code filter}. * @param strides 1-D tensor of length 5. The stride of the sliding window for each @@ -581,7 +566,6 @@ public Conv3d conv3d(Operand input, Operand filter, /** * Computes the gradients of 3-D convolution with respect to the filter. * - * @param data type for {@code output} output * @param input Shape {@code [batch, depth, rows, cols, in_channels]}. * @param filterSizes An integer vector representing the tensor shape of {@code filter}, * where {@code filter} is a 5-D @@ -604,7 +588,6 @@ public Conv3dBackpropFilter conv3dBackpropFilter(Operand< /** * Computes the gradients of 3-D convolution with respect to the input. * - * @param data type for {@code output} output * @param inputSizes An integer vector representing the tensor shape of {@code input}, * where {@code input} is a 5-D * {@code [batch, depth, rows, cols, in_channels]} tensor. @@ -632,7 +615,6 @@ public Conv3dBackpropInput conv3dBackpropInput( * "A B" is returned if merge_repeated = True but "A B B B B" is * returned if merge_repeated = False. * - * @param data type for {@code log_probability} output * @param inputs 3-D, shape: {@code (max_time x batch_size x num_classes)}, the logits. * @param sequenceLength A vector containing sequence lengths, size {@code (batch)}. * @param beamWidth A scalar >= 0 (beam search beam width). @@ -658,7 +640,6 @@ public CtcBeamSearchDecoder ctcBeamSearchDecoder(Operand< * time and batch corresponds to the blank, index {@code (num_classes - 1)}, no new * element is emitted. * - * @param data type for {@code log_probability} output * @param inputs 3-D, shape: {@code (max_time x batch_size x num_classes)}, the logits. * @param sequenceLength A vector containing sequence lengths, size {@code (batch_size)}. * @param options carries optional attribute values @@ -675,7 +656,6 @@ public CtcGreedyDecoder ctcGreedyDecoder(Operand input * the gradient. This class performs the softmax operation for you, so inputs * should be e.g. linear projections of outputs by an LSTM. * - * @param data type for {@code loss} output * @param inputs 3-D, shape: {@code (max_time x batch_size x num_classes)}, the logits. * @param labelsIndices The indices of a {@code SparseTensor}. * {@code labels_indices(i, :) == [b, t]} means {@code labels_values(i)} stores the id for @@ -730,7 +710,6 @@ public CtcLoss ctcLoss(Operand inputs, Operand * reserve_space: An opaque tensor that can be used in backprop calculation. It * is only produced if is_training is true. * - * @param data type for {@code output} output * @param input The input value * @param inputH The inputH value * @param inputC The inputC value @@ -795,7 +774,6 @@ public CudnnRNN cudnnRNN(Operand input, Operand inp * params_backprop: The backprop to the params buffer in the forward pass. Has the * same shape as params. * - * @param data type for {@code input_backprop} output * @param input The input value * @param inputH The inputH value * @param inputC The inputC value @@ -852,7 +830,6 @@ public CudnnRNNBackprop cudnnRNNBackprop(Operand input * num_proj: The output dimensionality for the projection matrices. If None or 0, * no projection is performed. * - * @param data type for {@code params} output * @param numLayers The numLayers value * @param numUnits The numUnits value * @param inputSize The inputSize value @@ -900,7 +877,6 @@ public CudnnRNNCanonicalToParams cudnnRNNCanonicalToParam * num_proj: The output dimensionality for the projection matrices. If None or 0, * no projection is performed. * - * @param data type for {@code weights} output * @param numLayers The numLayers value * @param numUnits The numUnits value * @param inputSize The inputSize value @@ -941,7 +917,6 @@ public CudnnRNNParamsToCanonical cudnnRNNParamsToCanonica * CudnnRNNParamsBiases to save and restore them in a way that is compatible * across different runs. * - * @param data type for {@code params_size} output * @param numLayers The numLayers value * @param numUnits The numUnits value * @param inputSize The inputSize value @@ -962,7 +937,6 @@ public CudnnRnnParamsSize cudnnRnnPara * Returns the dimension index in the destination data format given the one in * the source data format. * - * @param data type for {@code y} output * @param x A Tensor with each element as a dimension index in source data format. * Must be in the range [-4, 4). * @param options carries optional attribute values @@ -1006,7 +980,6 @@ public DataFormatDimMap dataFormatDimMap(Operand x, * [1, 2] * * - * @param data type for {@code y} output * @param x Tensor of rank 1 or 2 in source data format. * @param options carries optional attribute values * @param data type for {@code DataFormatVecPermute} output and operands @@ -1094,7 +1067,6 @@ public DataFormatVecPermute dataFormatVecPermute(Operand< * * * - * @param data type for {@code output} output * @param input The input value * @param blockSize The size of the spatial block, same as in Space2Depth. * @param options carries optional attribute values @@ -1125,7 +1097,6 @@ public DepthToSpace depthToSpace(Operand input, Long blo *

Must have {@code strides[0] = strides[3] = 1}. For the most common case of the same * horizontal and vertices strides, {@code strides = [1, stride, stride, 1]}. * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param strides 1-D of length 4. The stride of the sliding window for each dimension @@ -1144,7 +1115,6 @@ public DepthwiseConv2dNative depthwiseConv2dNative(Operan /** * Computes the gradients of depthwise convolution with respect to the filter. * - * @param data type for {@code output} output * @param input 4-D with shape based on {@code data_format}. For example, if * {@code data_format} is 'NHWC' then {@code input} is a 4-D {@code [batch, in_height, in_width, in_channels]} tensor. * @param filterSizes An integer vector representing the tensor shape of {@code filter}, @@ -1170,7 +1140,6 @@ public DepthwiseConv2dNativeBackpropFilter depthwiseConv2 /** * Computes the gradients of depthwise convolution with respect to the input. * - * @param data type for {@code output} output * @param inputSizes An integer vector representing the shape of {@code input}, based * on {@code data_format}. For example, if {@code data_format} is 'NHWC' then * {@code input} is a 4-D {@code [batch, height, width, channels]} tensor. @@ -1217,7 +1186,6 @@ public DepthwiseConv2dNativeBackpropInput depthwiseConv2d *

Note on duality: The dilation of {@code input} by the {@code filter} is equal to the * negation of the erosion of {@code -input} by the reflected {@code filter}. * - * @param data type for {@code output} output * @param input 4-D with shape {@code [batch, in_height, in_width, depth]}. * @param filter 3-D with shape {@code [filter_height, filter_width, depth]}. * @param strides The stride of the sliding window for each dimension of the input @@ -1236,7 +1204,6 @@ public Dilation2d dilation2d(Operand input, Operand /** * Computes the gradient of morphological 2-D dilation with respect to the filter. * - * @param data type for {@code filter_backprop} output * @param input 4-D with shape {@code [batch, in_height, in_width, depth]}. * @param filter 3-D with shape {@code [filter_height, filter_width, depth]}. * @param outBackprop 4-D with shape {@code [batch, out_height, out_width, depth]}. @@ -1257,7 +1224,6 @@ public Dilation2dBackpropFilter dilation2dBackpropFilter( /** * Computes the gradient of morphological 2-D dilation with respect to the input. * - * @param data type for {@code in_backprop} output * @param input 4-D with shape {@code [batch, in_height, in_width, depth]}. * @param filter 3-D with shape {@code [filter_height, filter_width, depth]}. * @param outBackprop 4-D with shape {@code [batch, out_height, out_width, depth]}. @@ -1298,7 +1264,6 @@ public Dilation2dBackpropInput dilation2dBackpropInput(Op *

See Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) * * - * @param data type for {@code activations} output * @param features The features value * @param data type for {@code Elu} output and operands * @return a new instance of Elu @@ -1310,7 +1275,6 @@ public Elu elu(Operand features) { /** * Computes gradients for the exponential linear (Elu) operation. * - * @param data type for {@code backprops} output * @param gradients The backpropagated gradients to the corresponding Elu operation. * @param outputs The outputs of the corresponding Elu operation. * @param data type for {@code EluGrad} output and operands @@ -1358,7 +1322,6 @@ public FixedUnigramCandidateSampler fixedUnigramCandidateSampler(Operand * generated, a mean operation is performed instead of a max operation in each * pooling region. * - * @param data type for {@code output} output * @param value 4-D with shape {@code [batch, height, width, channels]}. * @param poolingRatio Pooling ratio for each dimension of {@code value}, currently only * supports row and col dimension and should be >= 1.0. For example, a valid @@ -1383,7 +1346,6 @@ public FractionalAvgPool fractionalAvgPool(Operand val * just need to know the shape of original input tensor, instead of the whole * tensor. * - * @param data type for {@code output} output * @param origInputTensorShape Original input tensor shape for {@code fractional_avg_pool} * @param outBackprop 4-D with shape {@code [batch, height, width, channels]}. Gradients * w.r.t. the output of {@code fractional_avg_pool}. @@ -1431,7 +1393,6 @@ public FractionalAvgPoolGrad fractionalAvgPoolGrad( *

For more details on fractional max pooling, see this paper: * Benjamin Graham, Fractional Max-Pooling * - * @param data type for {@code output} output * @param value 4-D with shape {@code [batch, height, width, channels]}. * @param poolingRatio Pooling ratio for each dimension of {@code value}, currently only * supports row and col dimension and should be >= 1.0. For example, a valid @@ -1451,7 +1412,6 @@ public FractionalMaxPool fractionalMaxPool(Operand val /** * Computes gradient of the FractionalMaxPool function. * - * @param data type for {@code output} output * @param origInput Original input for {@code fractional_max_pool} * @param origOutput Original output for {@code fractional_max_pool} * @param outBackprop 4-D with shape {@code [batch, height, width, channels]}. Gradients @@ -1475,8 +1435,6 @@ public FractionalMaxPoolGrad fractionalMaxPoolGrad(Operan * Note that the size of 4D Tensors are defined by either "NHWC" or "NCHW". * The size of 1D Tensors matches the dimension C of the 4D Tensors. * - * @param data type for {@code y} output - * @param data type for {@code batch_mean} output * @param x A 4D Tensor for input data. * @param scale A 1D Tensor for scaling factor, to scale the normalized x. * @param offset A 1D Tensor for offset, to shift to the normalized x. @@ -1500,8 +1458,6 @@ public FusedBatchNorm fusedBatchNor * Note that the size of 4D Tensors are defined by either "NHWC" or "NCHW". * The size of 1D Tensors matches the dimension C of the 4D Tensors. * - * @param data type for {@code x_backprop} output - * @param data type for {@code scale_backprop} output * @param yBackprop A 4D Tensor for the gradient with respect to y. * @param x A 4D Tensor for input data. * @param scale A 1D Tensor for scaling factor, to scale the normalized x. @@ -1542,7 +1498,6 @@ public FusedBatchNormGrad fusedBatc * will block if multiple versions are being run in parallel. This is because this * operator is primarily an optimization to minimize memory usage. * - * @param data type for {@code output} output * @param input 4-D with shape {@code [batch, in_height, in_width, in_channels]}. * @param paddings A two-column matrix specifying the padding sizes. The number of * rows must be the same as the rank of {@code input}. @@ -1574,7 +1529,6 @@ public FusedPadConv2d fusedPadConv2d(Operand input, * will block if multiple versions are being run in parallel. This is because this * operator is primarily an optimization to minimize memory usage. * - * @param data type for {@code output} output * @param input 4-D with shape {@code [batch, in_height, in_width, in_channels]}. * @param sizeOutput A 1-D int32 Tensor of 2 elements: {@code new_height, new_width}. The * new size for the images. @@ -1637,7 +1591,6 @@ public FusedResizeAndPadConv2d fusedResizeAndPadConv2d(Op * h = (1-u) \circ c + u \circ h_prev * * - * @param data type for {@code r} output * @param x The x value * @param hPrev The hPrev value * @param wRu The wRu value @@ -1728,7 +1681,6 @@ public GRUBlockCell gRUBlockCell(Operand x, Operand * d_b_c = sum of d_c_bar along axis = 0 * * - * @param data type for {@code d_x} output * @param x The x value * @param hPrev The hPrev value * @param wRu The wRu value @@ -1778,7 +1730,6 @@ public InTopK inTopK(Operand predictions, Operand< * Specifically, {@code grad = -dy * y*y}, where {@code y = 1/x}, and {@code dy} * is the corresponding input gradient. * - * @param data type for {@code z} output * @param y The y value * @param dy The dy value * @param data type for {@code InvGrad} output and operands @@ -1791,7 +1742,6 @@ public InvGrad invGrad(Operand y, Operand dy) { /** * Solves a batch of isotonic regression problems. * - * @param data type for {@code output} output * @param input A (batch_size, dim)-tensor holding a batch of inputs. * @return a new instance of IsotonicRegression, with default output types */ @@ -1802,7 +1752,6 @@ public IsotonicRegression isotonicRegression(Operand data type for {@code output} output * @param input A (batch_size, dim)-tensor holding a batch of inputs. * @param outputDtype Dtype of output. * @param data type for {@code IsotonicRegression} output and operands @@ -1820,7 +1769,6 @@ public IsotonicRegression isotonicRegression( * output = sum(t ** 2) / 2 * * - * @param data type for {@code output} output * @param t Typically 2-D, but may have any dimensions. * @param data type for {@code L2Loss} output and operands * @return a new instance of L2Loss @@ -1854,7 +1802,6 @@ public L2Loss l2Loss(Operand t) { * h = co .* o * * - * @param data type for {@code i} output * @param x The input to the LSTM cell, shape (batch_size, num_inputs). * @param csPrev Value of the cell state at previous time step. * @param hPrev Output of the previous cell at previous time step. @@ -1877,7 +1824,6 @@ public LSTMBlockCell lSTMBlockCell(Operand x, Operand< * Computes the LSTM cell backward propagation for 1 timestep. * This implementation is to be used in conjunction of LSTMBlockCell. * - * @param data type for {@code cs_prev_grad} output * @param x The input to the LSTM cell, shape (batch_size, num_inputs). * @param csPrev The previous cell state. * @param hPrev The previous h state. @@ -1908,7 +1854,6 @@ public LSTMBlockCellGrad lSTMBlockCellGrad(Operand x, /** * Computes rectified linear: {@code max(features, features * alpha)}. * - * @param data type for {@code activations} output * @param features The features value * @param options carries optional attribute values * @param data type for {@code LeakyRelu} output and operands @@ -1960,7 +1905,6 @@ public LearnedUnigramCandidateSampler learnedUnigramCandidateSampler(OperandFor details, see Krizhevsky et al., ImageNet classification with deep * convolutional neural networks (NIPS 2012) . * - * @param data type for {@code output} output * @param input 4-D. * @param options carries optional attribute values * @param data type for {@code LRN} output and operands @@ -1974,7 +1918,6 @@ public LocalResponseNormalization localResponseNormalizat /** * Gradients for Local Response Normalization. * - * @param data type for {@code output} output * @param inputGrads 4-D with shape {@code [batch, height, width, channels]}. * @param inputImage 4-D with shape {@code [batch, height, width, channels]}. * @param outputImage 4-D with shape {@code [batch, height, width, channels]}. @@ -1995,7 +1938,6 @@ public LocalResponseNormalizationGrad localResponseNormal * logsoftmax[i, j] = logits[i, j] - log(sum(exp(logits[i]))) * * - * @param data type for {@code logsoftmax} output * @param logits 2-D with shape {@code [batch_size, num_classes]}. * @param data type for {@code LogSoftmax} output and operands * @return a new instance of LogSoftmax @@ -2007,7 +1949,6 @@ public LogSoftmax logSoftmax(Operand logits) { /** * Performs max pooling on the input. * - * @param data type for {@code output} output * @param input 4-D input to pool over. * @param ksize The size of the window for each dimension of the input tensor. * @param strides The stride of the sliding window for each dimension of the @@ -2025,7 +1966,6 @@ public MaxPool maxPool(Operand input, Operand /** * Performs 3D max pooling on the input. * - * @param data type for {@code output} output * @param input Shape {@code [batch, depth, rows, cols, channels]} tensor to pool over. * @param ksize 1-D tensor of length 5. The size of the window for each dimension of * the input tensor. Must have {@code ksize[0] = ksize[4] = 1}. @@ -2044,7 +1984,6 @@ public MaxPool3d maxPool3d(Operand input, List k /** * Computes gradients of 3D max pooling function. * - * @param data type for {@code output} output * @param origInput The original input tensor. * @param origOutput The original output tensor. * @param grad Output backprop of shape {@code [batch, depth, rows, cols, channels]}. @@ -2067,7 +2006,6 @@ public MaxPool3dGrad maxPool3dGrad(Ope /** * Computes second-order gradients of the maxpooling function. * - * @param data type for {@code output} output * @param origInput The original input tensor. * @param origOutput The original output tensor. * @param grad Output backprop of shape {@code [batch, depth, rows, cols, channels]}. @@ -2089,7 +2027,6 @@ public MaxPool3dGradGrad maxPool3dGradGrad(Operand ori /** * Computes gradients of the maxpooling function. * - * @param data type for {@code output} output * @param origInput The original input tensor. * @param origOutput The original output tensor. * @param grad 4-D. Gradients w.r.t. the output of {@code max_pool}. @@ -2110,7 +2047,6 @@ public MaxPoolGrad maxPoolGrad(Operand origInput, Oper /** * Computes second-order gradients of the maxpooling function. * - * @param data type for {@code output} output * @param origInput The original input tensor. * @param origOutput The original output tensor. * @param grad 4-D. Gradients of gradients w.r.t. the input of {@code max_pool}. @@ -2131,7 +2067,6 @@ public MaxPoolGradGrad maxPoolGradGrad(Operand origInp /** * Computes second-order gradients of the maxpooling function. * - * @param data type for {@code output} output * @param input The original input. * @param grad 4-D with shape {@code [batch, height, width, channels]}. Gradients w.r.t. the * input of {@code max_pool}. @@ -2153,7 +2088,6 @@ public MaxPoolGradGradWithArgmax maxPoolGradGradWithArgma /** * Computes gradients of the maxpooling function. * - * @param data type for {@code output} output * @param input The original input. * @param grad 4-D with shape {@code [batch, height, width, channels]}. Gradients w.r.t. the * output of {@code max_pool}. @@ -2183,8 +2117,6 @@ public MaxPoolGradWithArgmax maxPoolGradWithArgmax(Operan * (either negative or too large). This is a bug, but fixing it is difficult to do * in a safe backwards compatible way, especially due to flattening. * - * @param data type for {@code output} output - * @param data type for {@code argmax} output * @param input 4-D with shape {@code [batch, height, width, channels]}. Input to pool over. * @param ksize The size of the window for each dimension of the input tensor. * @param strides The stride of the sliding window for each dimension of the @@ -2210,8 +2142,6 @@ public MaxPoolWithArgmax maxPoolWithArgmax(Operan * (either negative or too large). This is a bug, but fixing it is difficult to do * in a safe backwards compatible way, especially due to flattening. * - * @param data type for {@code output} output - * @param data type for {@code argmax} output * @param input 4-D with shape {@code [batch, height, width, channels]}. Input to pool over. * @param ksize The size of the window for each dimension of the input tensor. * @param strides The stride of the sliding window for each dimension of the @@ -2239,7 +2169,6 @@ public MaxPoolWithArgmax maxPoolWit * values.shape = input.shape[:-1] * * - * @param data type for {@code values} output * @param input 1-D or higher with last dimension at least {@code n+1}. * @param n 0-D. Position of sorted vector to select along the last dimension (along * each row for matrices). Valid range of n is {@code [0, input.shape[:-1])} @@ -2255,7 +2184,6 @@ public NthElement nthElement(Operand input, Operand data type for {@code output} output * @param input 4-D with shape {@code [batch, height, width, channels]}. * @param minInput The float value that the lowest quantized input value represents. * @param maxInput The float value that the highest quantized input value represents. @@ -2278,7 +2206,6 @@ public QuantizedAvgPool quantizedAvgPool(Operand input * This op is deprecated and will be removed in the future. Prefer * {@code tf.nn.batch_normalization}. * - * @param data type for {@code result} output * @param t A 4D input Tensor. * @param tMin The value represented by the lowest quantized input. * @param tMax The value represented by the highest quantized input. @@ -2322,7 +2249,6 @@ public QuantizedBatchNormWithGlobalNormal * Adds Tensor 'bias' to Tensor 'input' for Quantized types. * Broadcasts the values of bias on dimensions 0..N-2 of 'input'. * - * @param data type for {@code output} output * @param input The input value * @param bias A 1D bias Tensor with size matching the last dimension of 'input'. * @param minInput The float value that the lowest quantized input value represents. @@ -2342,7 +2268,6 @@ public QuantizedBiasAdd quantizedBiasAdd(Operand data type for {@code output} output * @param input The input value * @param filter The filter value * @param minInput The minInput value @@ -2367,7 +2292,6 @@ public QuantizedConv2DAndRelu quantizedConv2DAndRelu( /** * The QuantizedConv2DAndReluAndRequantize operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param minInput The minInput value @@ -2395,7 +2319,6 @@ public QuantizedConv2DAndReluAndRequantize quantizedConv2 /** * The QuantizedConv2DAndRequantize operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param minInput The minInput value @@ -2423,7 +2346,6 @@ public QuantizedConv2DAndRequantize quantizedConv2DAndReq /** * Computes QuantizedConv2D per channel. * - * @param data type for {@code output} output * @param input The original input tensor. * @param filter The original filter tensor. * @param minInput The minimum value of the input tensor @@ -2448,7 +2370,6 @@ public QuantizedConv2DPerChannel quantizedConv2DPerChanne /** * The QuantizedConv2DWithBias operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param bias The bias value @@ -2474,7 +2395,6 @@ public QuantizedConv2DWithBias quantizedConv2DWithBias( /** * The QuantizedConv2DWithBiasAndRelu operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param bias The bias value @@ -2500,7 +2420,6 @@ public QuantizedConv2DWithBiasAndRelu quantizedConv2DWith /** * The QuantizedConv2DWithBiasAndReluAndRequantize operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param bias The bias value @@ -2529,7 +2448,6 @@ public QuantizedConv2DWithBiasAndReluAndRequantize quanti /** * The QuantizedConv2DWithBiasAndRequantize operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param bias The bias value @@ -2558,7 +2476,6 @@ public QuantizedConv2DWithBiasAndRequantize quantizedConv /** * The QuantizedConv2DWithBiasSignedSumAndReluAndRequantize operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param bias The bias value @@ -2592,7 +2509,6 @@ public QuantizedConv2DWithBiasSignedSumAndReluAndRequantize< /** * The QuantizedConv2DWithBiasSumAndRelu operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param bias The bias value @@ -2619,7 +2535,6 @@ public QuantizedConv2DWithBiasSumAndRelu quantizedConv2DW /** * The QuantizedConv2DWithBiasSumAndReluAndRequantize operation * - * @param data type for {@code output} output * @param input The input value * @param filter The filter value * @param bias The bias value @@ -2657,7 +2572,6 @@ public QuantizedConv2DWithBiasSumAndReluAndRequantize qua * This means that you can only interpret the quantized output in the same way, by * taking the returned minimum and maximum values into account. * - * @param data type for {@code output} output * @param input The input value * @param filter filter's input_depth dimension must match input's depth dimensions. * @param minInput The float value that the lowest quantized input value represents. @@ -2682,7 +2596,6 @@ public QuantizedConv2d quantizedConv2d(Operand data type for {@code output} output * @param input The original input tensor. * @param filter The original filter tensor. * @param minInput The float value that the minimum quantized input value represents. @@ -2707,7 +2620,6 @@ public QuantizedDepthwiseConv2D quantizedDepthwiseConv2D( /** * Computes quantized depthwise Conv2D with Bias. * - * @param data type for {@code output} output * @param input The original input tensor. * @param filter The original filter tensor. * @param bias The original bias tensor. @@ -2733,7 +2645,6 @@ public QuantizedDepthwiseConv2DWithBias quantizedDepthwis /** * Computes quantized depthwise Conv2D with Bias and Relu. * - * @param data type for {@code output} output * @param input The original input tensor. * @param filter The original filter tensor. * @param bias The original bias tensor. @@ -2759,7 +2670,6 @@ public QuantizedDepthwiseConv2DWithBiasAndRelu quantizedD /** * Computes quantized depthwise Conv2D with Bias, Relu and Requantize. * - * @param data type for {@code output} output * @param input The original input tensor. * @param filter The original filter tensor. * @param bias The original bias tensor. @@ -2788,7 +2698,6 @@ public QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize< /** * Quantized Instance normalization. * - * @param data type for {@code y} output * @param x A 4D input Tensor. * @param xMin The value represented by the lowest quantized input. * @param xMax The value represented by the highest quantized input. @@ -2804,7 +2713,6 @@ public QuantizedInstanceNorm quantizedInstanceNorm(Operan /** * Produces the max pool of the input tensor for quantized types. * - * @param data type for {@code output} output * @param input The 4D (batch x rows x cols x depth) Tensor to MaxReduce over. * @param minInput The float value that the lowest quantized input value represents. * @param maxInput The float value that the highest quantized input value represents. @@ -2825,7 +2733,6 @@ public QuantizedMaxPool quantizedMaxPool(Operand input /** * Computes Quantized Rectified Linear: {@code max(features, 0)} * - * @param data type for {@code activations} output * @param features The features value * @param minFeatures The float value that the lowest quantized value represents. * @param maxFeatures The float value that the highest quantized value represents. @@ -2841,7 +2748,6 @@ public QuantizedRelu quantizedRelu(Operand data type for {@code activations} output * @param features The features value * @param minFeatures The float value that the lowest quantized value represents. * @param maxFeatures The float value that the highest quantized value represents. @@ -2857,7 +2763,6 @@ public QuantizedRelu6 quantizedRelu6(Operand data type for {@code activations} output * @param features The features value * @param maxValue The maxValue value * @param minFeatures The float value that the lowest quantized value represents. @@ -2885,7 +2790,6 @@ public QuantizedReluX quantizedReluX(Operand * * - * @param data type for {@code activations} output * @param features The features value * @param data type for {@code Relu} output and operands * @return a new instance of Relu @@ -2897,7 +2801,6 @@ public Relu relu(Operand features) { /** * Computes rectified linear 6: {@code min(max(features, 0), 6)}. * - * @param data type for {@code activations} output * @param features The features value * @param data type for {@code Relu6} output and operands * @return a new instance of Relu6 @@ -2909,7 +2812,6 @@ public Relu6 relu6(Operand features) { /** * Computes rectified linear 6 gradients for a Relu6 operation. * - * @param data type for {@code backprops} output * @param gradients The backpropagated gradients to the corresponding Relu6 operation. * @param features The features passed as input to the corresponding Relu6 operation, or * its output; using either one produces the same result. @@ -2923,7 +2825,6 @@ public Relu6Grad relu6Grad(Operand gradients, Operand< /** * Computes rectified linear gradients for a Relu operation. * - * @param data type for {@code backprops} output * @param gradients The backpropagated gradients to the corresponding Relu operation. * @param features The features passed as input to the corresponding Relu operation, OR * the outputs of that operation (both work equivalently). @@ -2942,7 +2843,6 @@ public ReluGrad reluGrad(Operand gradients, Operand * For correct dropout, use {@code tf.contrib.nn.alpha_dropout}. *

See Self-Normalizing Neural Networks * - * @param data type for {@code activations} output * @param features The features value * @param data type for {@code Selu} output and operands * @return a new instance of Selu @@ -2954,7 +2854,6 @@ public Selu selu(Operand features) { /** * Computes gradients for the scaled exponential linear (Selu) operation. * - * @param data type for {@code backprops} output * @param gradients The backpropagated gradients to the corresponding Selu operation. * @param outputs The outputs of the corresponding Selu operation. * @param data type for {@code SeluGrad} output and operands @@ -2971,7 +2870,6 @@ public SeluGrad seluGrad(Operand gradients, Operand * $$softmax[i, j] = exp(logits[i, j]) / sum_j(exp(logits[i, j]))$$ * * - * @param data type for {@code softmax} output * @param logits 2-D with shape {@code [batch_size, num_classes]}. * @param data type for {@code Softmax} output and operands * @return a new instance of Softmax @@ -2984,7 +2882,6 @@ public Softmax softmax(Operand logits) { * Computes softmax cross entropy cost and gradients to backpropagate. * Inputs are the logits, not probabilities. * - * @param data type for {@code loss} output * @param features batch_size x num_classes matrix * @param labels batch_size x num_classes matrix * The caller must ensure that each batch of labels represents a valid @@ -3000,7 +2897,6 @@ public SoftmaxCrossEntropyWithLogits softmaxCrossEntropyW /** * Computes softsign: {@code features / (abs(features) + 1)}. * - * @param data type for {@code activations} output * @param features The features value * @param data type for {@code Softsign} output and operands * @return a new instance of Softsign @@ -3012,7 +2908,6 @@ public Softsign softsign(Operand features) { /** * Computes softsign gradients for a softsign operation. * - * @param data type for {@code backprops} output * @param gradients The backpropagated gradients to the corresponding softsign operation. * @param features The features passed as input to the corresponding softsign operation. * @param data type for {@code SoftsignGrad} output and operands @@ -3090,7 +2985,6 @@ public SoftsignGrad softsignGrad(Operand gradients, *

Among others, this operation is useful for reducing atrous convolution into * regular convolution. * - * @param data type for {@code output} output * @param input 4-D with shape {@code [batch, height, width, depth]}. * @param paddings 2-D tensor of non-negative integers with shape {@code [2, 2]}. It specifies * the padding of the input with zeros across the spatial dimensions as follows: @@ -3182,7 +3076,6 @@ public SpaceToBatch spaceToBatch(Operand input, * [13, 14, 15, 16]]]] * * - * @param data type for {@code output} output * @param input The input value * @param blockSize The size of the spatial block. * @param options carries optional attribute values @@ -3202,7 +3095,6 @@ public SpaceToDepth spaceToDepth(Operand input, Long blo * given row. *

Inputs are the logits, not probabilities. * - * @param data type for {@code loss} output * @param features batch_size x num_classes matrix * @param labels batch_size vector with values in [0, num_classes). * This is the label for the given minibatch entry. @@ -3226,8 +3118,6 @@ public SparseSoftmaxCrossEntropyWithLogits sparseSoftmaxC * *

If two elements are equal, the lower-index element appears first. * - * @param data type for {@code values} output - * @param data type for {@code indices} output * @param input 1-D or higher with last dimension at least {@code k}. * @param k 0-D. Number of top elements to look for along the last dimension (along each * row for matrices). @@ -3252,8 +3142,6 @@ public TopK topK(Operand input, Operand *

If two elements are equal, the lower-index element appears first. * - * @param data type for {@code values} output - * @param data type for {@code indices} output * @param input 1-D or higher with last dimension at least {@code k}. * @param k 0-D. Number of top elements to look for along the last dimension (along each * row for matrices). @@ -3287,7 +3175,6 @@ public TopK topK(Operand input, *

{@code output} is also quantized, using the same formula. * If {@code rhs} is per-tensor quantized, {@code output} must be also per-tensor quantized. * - * @param data type for {@code output} output * @param lhs Must be a quantized tensor, rank >= 3. * @param rhs Must be a quantized tensor, same rank as {@code lhs}. * @param lhsScales The float value(s) used as scale factors when quantizing the original data that {@code lhs} represents. @@ -3358,7 +3245,6 @@ public UniformQuantizedConvolution uni *

{@code rhs} must be quantized Tensor, where its data value is quantized using the formula: * quantized_data = clip(original_data / scale + zero_point, quantization_min_val, quantization_max_val). * - * @param data type for {@code output} output * @param lhs Must be a non-quantized Tensor of {@code Tlhs}, rank >= 3. * @param rhs Must be a quantized Tensor of {@code Trhs}, same rank as {@code lhs}. * @param rhsScales The float value(s) used as scale factors when quantizing the original data that {@code rhs} represents. diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java index bc83757228c..765a67f27e8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/Ops.java @@ -407,10 +407,10 @@ public final class Ops { public final CollectiveOps collective; - public final AudioOps audio; - public final DistributeOps distribute; + public final AudioOps audio; + public final SignalOps signal; public final TrainOps train; @@ -419,10 +419,10 @@ public final class Ops { public final SummaryOps summary; - public final ImageOps image; - public final RaggedOps ragged; + public final ImageOps image; + public final ShapeOps shape; public final IoOps io; @@ -450,14 +450,14 @@ public final class Ops { bitwise = new BitwiseOps(this); debugging = new DebuggingOps(this); collective = new CollectiveOps(this); - audio = new AudioOps(this); distribute = new DistributeOps(this); + audio = new AudioOps(this); signal = new SignalOps(this); train = new TrainOps(this); quantization = new QuantizationOps(this); summary = new SummaryOps(this); - image = new ImageOps(this); ragged = new RaggedOps(this); + image = new ImageOps(this); shape = new ShapeOps(this); io = new IoOps(this); dtypes = new DtypesOps(this); @@ -618,7 +618,6 @@ public Any any(Operand input, Operand axis, Any.Option * See https://arxiv.org/abs/2206.14286 for the algorithm details. * This op is only optimized on TPU currently. * - * @param data type for {@code values} output * @param input Array to search. Must be at least 1-D of the floating type * @param k Specifies the number of min/max-k. * @param options carries optional attribute values @@ -732,7 +731,6 @@ public AssertThat assertThat(Operand condition, Iterable> data * This operation outputs "ref" after the assignment is done. * This makes it easier to chain operations that need to use the reset value. * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. May be uninitialized. * @param value The value to be assigned to the variable. * @param options carries optional attribute values @@ -749,7 +747,6 @@ public Assign assign(Operand ref, Operand value, * This operation outputs "ref" after the update is done. * This makes it easier to chain operations that need to use the reset value. * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param value The value to be added to the variable. * @param options carries optional attribute values @@ -780,7 +777,6 @@ public AssignAddVariableOp assignAddVariableOp(Operand resource * This operation outputs "ref" after the update is done. * This makes it easier to chain operations that need to use the reset value. * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param value The value to be subtracted to the variable. * @param options carries optional attribute values @@ -1027,7 +1023,6 @@ public BatchFunction batchFunction(Iterable> inTensors, * dimension are moved in spatial blocks to the {@code height} and {@code width} dimensions, * followed by cropping along the {@code height} and {@code width} dimensions. * - * @param data type for {@code output} output * @param input 4-D tensor with shape * {@code [batch*block_size*block_size, height_pad/block_size, width_pad/block_size, depth]}. Note that the batch size of the input tensor must be divisible by * {@code block_size * block_size}. @@ -1055,7 +1050,6 @@ public BatchToSpace batchToSpace(Operand input, * optionally cropped according to {@code crops} to produce the output. This is the * reverse of SpaceToBatch. See below for a precise description. * - * @param data type for {@code output} output * @param input N-D with shape {@code input_shape = [batch] + spatial_shape + remaining_shape}, * where spatial_shape has M dimensions. * @param blockShape 1-D with shape {@code [M]}, all values must be >= 1. @@ -1221,7 +1215,6 @@ public BatchToSpaceNd batchToSpaceNd(Operand input, * buffer is made on BE machines when types are of different sizes in order to get * the same casting results as on LE machines. * - * @param data type for {@code output} output * @param input The input value * @param type The value of the type attribute * @param data type for {@code Bitcast} output and operands @@ -1292,7 +1285,6 @@ public Operand booleanMaskUpdate(Operand tensor, Operand * Given {@code s0} and {@code s1}, tensors that represent shapes, compute {@code r0}, the * broadcasted shape. {@code s0}, {@code s1} and {@code r0} are all integer vectors. * - * @param data type for {@code r0} output * @param s0 The s0 value * @param s1 The s1 value * @param data type for {@code BroadcastArgs} output and operands @@ -1307,7 +1299,6 @@ public BroadcastDynamicShape broadcastDynamicShape(Operan * Return the reduction indices for computing gradients of s0 op s1 with broadcast. * This is typically used by gradient computations for a broadcasting operation. * - * @param data type for {@code r0} output * @param s0 The s0 value * @param s1 The s1 value * @param data type for {@code BroadcastGradientArgs} output and operands @@ -1357,7 +1348,6 @@ public BroadcastGradientArgs broadcastGradientArgs(Operan * shape. (In a graph context, {@code broadcast_to} might be fused to * subsequent operation and then be optimized away, however.) * - * @param data type for {@code output} output * @param input A Tensor to broadcast. * @param shape An 1-D {@code int} Tensor. The shape of the desired output. * @param data type for {@code BroadcastTo} output and operands @@ -1458,7 +1448,6 @@ public Case caseOp(Operand branchIndex, Iterable> input, * Any values less than {@code clip_value_min} are set to {@code clip_value_min}. Any values * greater than {@code clip_value_max} are set to {@code clip_value_max}. * - * @param data type for {@code output} output * @param t A {@code Tensor}. * @param clipValueMin A 0-D (scalar) {@code Tensor}, or a {@code Tensor} with the same shape * as {@code t}. The minimum value to clip by. @@ -1508,7 +1497,6 @@ public CompositeTensorVariantToComponents compositeTensorVariantToComponents( /** * Concatenates tensors along one dimension. * - * @param data type for {@code output} output * @param values List of {@code N} Tensors to concatenate. Their ranks and types must match, * and their sizes must match in all dimensions except {@code concat_dim}. * @param axis 0-D. The dimension along which to concatenate. Must be in the @@ -1538,7 +1526,6 @@ public Concat concat(Iterable> values, * *

This is typically used by gradient computations for a concat operation. * - * @param data type for {@code offset} output * @param concatDim The dimension along which to concatenate. * @param shape The {@code N} int32 or int64 vectors representing shape of tensors being concatenated. * @param data type for {@code ConcatOffset} output and operands @@ -2262,11 +2249,7 @@ public Constant constant(Class type, Shape shape, ByteDa /** * Create a constant by making an immutable copy of {@code tensor}. {@code tensor} may be closed - * afterwards without issue. - * - *

Note: this endpoint cannot be simply called {@code constant} since it will conflict with - * other endpoints accepting an NdArray in parameter {e.g. {@link #tensorOf(Scope, - * FloatNdArray)}}. + * afterward without issue. * * @param tensor a Tensor holding the constant value * @return a constant of the same data type as `tensor` @@ -2318,7 +2301,6 @@ public ControlTrigger controlTrigger() { /** * The CopyToMesh operation * - * @param data type for {@code output} output * @param input The input value * @param mesh The value of the mesh attribute * @param data type for {@code CopyToMesh} output and operands @@ -2331,7 +2313,6 @@ public CopyToMesh copyToMesh(Operand input, String mesh) /** * The CopyToMeshGrad operation * - * @param data type for {@code output} output * @param input The input value * @param forwardInput The forwardInput value * @param data type for {@code CopyToMeshGrad} output and operands @@ -2345,7 +2326,6 @@ public CopyToMeshGrad copyToMeshGrad(Operand input, /** * Increments 'ref' until it reaches 'limit'. * - * @param data type for {@code output} output * @param ref Should be from a scalar {@code Variable} node. * @param limit If incrementing ref would bring it above limit, instead generates an * 'OutOfRange' error. @@ -2440,7 +2420,6 @@ public DecodeProto decodeProto(Operand bytes, String messageType, /** * Makes a copy of {@code x}. * - * @param data type for {@code y} output * @param x The source tensor of type {@code T}. * @param data type for {@code DeepCopy} output and operands * @return a new instance of DeepCopy @@ -2482,7 +2461,6 @@ public DestroyResourceOp destroyResourceOp(Operand resource, * using control dependencies. *

Outputs the final value of the tensor pointed to by 'ref'. * - * @param data type for {@code value} output * @param ref A reference to the temporary variable tensor. * @param varName Name of the temporary variable, usually the name of the matching * 'TemporaryVariable' op. @@ -2560,7 +2538,6 @@ public DummyMemoryCache dummyMemoryCache() { * * * - * @param data type for {@code outputs} output * @param data The data value * @param partitions Any shape. Indices in the range {@code [0, num_partitions)}. * @param numPartitions The number of partitions to output. @@ -2628,7 +2605,6 @@ public DynamicPartition dynamicPartition(Operand data, * * * - * @param data type for {@code merged} output * @param indices The indices value * @param data The data value * @param data type for {@code DynamicStitch} output and operands @@ -2672,7 +2648,6 @@ public EditDistance editDistance(Operand hypothesisInd * Creates a tensor with the given shape. *

This operation creates a tensor of {@code shape} and {@code dtype}. * - * @param data type for {@code output} output * @param shape 1-D. Represents the shape of the output tensor. * @param dtype The value of the dtype attribute * @param options carries optional attribute values @@ -2778,7 +2753,6 @@ public EncodeProto encodeProto(Operand sizes, Iterable> value * Raises an error if the input tensor's shape does not match the specified shape. * Returns the input tensor otherwise. * - * @param data type for {@code output} output * @param input A tensor, whose shape is to be validated. * @param shape The expected (possibly partially specified) shape of the input tensor. * @param data type for {@code EnsureShape} output and operands @@ -2796,7 +2770,6 @@ public EnsureShape ensureShape(Operand input, Shape shap * it may be changed in the child frame. At most {@code parallel_iterations} iterations * are run in parallel in the child frame. * - * @param data type for {@code output} output * @param data The tensor to be made available to the child frame. * @param frameName The name of the child frame. * @param options carries optional attribute values @@ -2812,7 +2785,6 @@ public Enter enter(Operand data, String frameName, * Exits the current frame to its parent frame. * Exit makes its input {@code data} available to the parent frame. * - * @param data type for {@code output} output * @param data The tensor to be made available to the parent frame. * @param data type for {@code Exit} output and operands * @return a new instance of Exit @@ -2847,7 +2819,6 @@ public Exit exit(Operand data) { *

This operation is related to {@code squeeze()}, which removes dimensions of * size 1. * - * @param data type for {@code output} output * @param input The input value * @param axis 0-D (scalar). Specifies the dimension index at which to * expand the shape of {@code input}. Must be in the range @@ -2863,7 +2834,6 @@ public ExpandDims expandDims(Operand input, /** * Extract {@code patches} from {@code input} and put them in the {@code "depth"} output dimension. 3D extension of {@code extract_image_patches}. * - * @param data type for {@code patches} output * @param input 5-D Tensor with shape {@code [batch, in_planes, in_rows, in_cols, depth]}. * @param ksizes The size of the sliding window for each dimension of {@code input}. * @param strides 1-D of length 5. How far the centers of two consecutive patches are in @@ -2888,7 +2858,6 @@ public ExtractVolumePatches extractVolumePatches(Operand< * function input) or guaranteed not to be used (e.g. if mirroring an * intermediate output needed for the gradient computation of the other branch). * - * @param data type for {@code output} output * @param dtype The type of the output. * @param shape 

    *  The purported shape of the output. This is only used for shape inference;
@@ -2934,7 +2903,6 @@ public FileSystemSetConfiguration fileSystemSetConfiguration(Operand sc
    *  based on other runtime Tensors, unlike {@code tf.constant}.
    *  
    *
-   * @param  data type for {@code output} output
    * @param dims 1-D. Represents the shape of the output tensor.
    * @param value 0-D (scalar). Value to fill the returned tensor.
    *  
{@literal @}compatibility(numpy)

@@ -3030,7 +2998,6 @@ public For forOp(Operand start, Operand limit, Operand d
    *  corresponding output value.
    *  
See also {@code tf.batch_gather} and {@code tf.gather_nd}.
    *
-   * @param  data type for {@code output} output
    * @param params The tensor from which to gather values. Must be at least rank
    *  {@code axis + 1}.
    * @param indices Index tensor. Must be in range {@code [0, params.shape[axis])}.
@@ -3137,7 +3104,6 @@ public  Gather gather(Operand params, Operand
    *  
See also {@code tf.gather} and {@code tf.batch_gather}.
    *
-   * @param  data type for {@code output} output
    * @param params The tensor from which to gather values.
    * @param indices Index tensor.
    * @param  data type for {@code GatherNd} output and operands
@@ -3185,7 +3151,6 @@ public GetSessionHandle getSessionHandle(Operand value) {
   /**
    * Get the value of the tensor specified by its handle.
    *
-   * @param  data type for {@code value} output
    * @param handle The handle for a tensor stored in the session state.
    * @param dtype The type of the output value.
    * @param  data type for {@code GetSessionTensor} output and operands
@@ -3250,7 +3215,6 @@ public Gradients gradients(Iterable> y, IterableReturns the input tensor without modification.
    *
-   * @param  data type for {@code output} output
    * @param input The input value
    * @param  data type for {@code GuaranteeConst} output and operands
    * @return a new instance of GuaranteeConst
@@ -3294,7 +3258,6 @@ public  HashTable hashTable(Class keyDtype,
    *    sess.run(hist) => [2, 1, 1, 0, 2]
    *
* - * @param data type for {@code out} output * @param values Numeric {@code Tensor}. * @param valueRange Shape [2] {@code Tensor} of same {@code dtype} as {@code values}. * values <= value_range[0] will be mapped to hist[0], @@ -3325,7 +3288,6 @@ public HistogramFixedWidth histogramFixedWidth(Opera * sess.run(hist) => [2, 1, 1, 0, 2] * * - * @param data type for {@code out} output * @param values Numeric {@code Tensor}. * @param valueRange Shape [2] {@code Tensor} of same {@code dtype} as {@code values}. * values <= value_range[0] will be mapped to hist[0], @@ -3344,7 +3306,6 @@ public HistogramFixedWidth histogramFi /** * Returns a constant tensor on the host. Only for writing C++ tests. * - * @param data type for {@code output} output * @param value Attr {@code value} is the tensor to return. * @param dtype The value of the dtype attribute * @param data type for {@code HostConst} output and operands @@ -3357,7 +3318,6 @@ public HostConst hostConst(Tensor value, Class dtype) { /** * Return a tensor with the same shape and contents as the input tensor or value. * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code Identity} output and operands * @return a new instance of Identity @@ -3425,7 +3385,6 @@ public If ifOp(Operand cond, Iterable> input, * Returns immutable tensor from memory region. * The current implementation memmaps the tensor from a file. * - * @param data type for {@code tensor} output * @param dtype Type of the returned tensor. * @param shape Shape of the returned tensor. * @param memoryRegionName Name of readonly memory region used by the tensor, see @@ -3485,7 +3444,6 @@ public InitializeTableFromTextFile initializeTableFromTextFile( * Computes y = x; y[i, :] += v; return y. * * - * @param data type for {@code y} output * @param x A {@code Tensor} of type T. * @param i A vector. Indices into the left-most dimension of {@code x}. * @param v A {@code Tensor} of type T. Same dimension sizes as x except the first dimension, which must be the same as i's size. @@ -3503,7 +3461,6 @@ public InplaceAdd inplaceAdd(Operand x, Operand * Computes y = x; y[i, :] -= v; return y. * * - * @param data type for {@code y} output * @param x A {@code Tensor} of type T. * @param i A vector. Indices into the left-most dimension of {@code x}. * @param v A {@code Tensor} of type T. Same dimension sizes as x except the first dimension, which must be the same as i's size. @@ -3520,7 +3477,6 @@ public InplaceSub inplaceSub(Operand x, Operand *

Originally this function is mutative however for compilation we make this * operation create / operate on a copy of {@code x}. * - * @param data type for {@code y} output * @param x A tensor of type {@code T}. * @param i A vector. Indices into the left-most dimension of {@code x}. * @param v A {@code Tensor} of type T. Same dimension sizes as x except the first dimension, which must be the same as i's size. @@ -3578,7 +3534,6 @@ public KthOrderStatistic kthOrderStatistic(Operand input, Long k) { * tf.linspace(10.0, 12.0, 3, name="linspace") => [ 10.0 11.0 12.0] * * - * @param data type for {@code output} output * @param start 0-D tensor. First entry in the range. * @param stop 0-D tensor. Last entry in the range. * @param num 0-D tensor. Number of values to generate. @@ -3593,8 +3548,6 @@ public LinSpace linSpace(Operand start, Operand sto /** * Outputs all keys and values in the table. * - * @param data type for {@code keys} output - * @param data type for {@code values} output * @param tableHandle Handle to the table. * @param Tkeys The value of the Tkeys attribute * @param Tvalues The value of the Tvalues attribute @@ -3614,7 +3567,6 @@ public LookupTableExport lookupTableExp *

The scalar {@code default_value} is the value output for keys not present in the * table. It must also be of the same type as the table values. * - * @param data type for {@code values} output * @param tableHandle Handle to the table. * @param keys Any shape. Keys to look up. * @param defaultValue The defaultValue value @@ -3708,7 +3660,6 @@ public LoopCond loopCond(Operand input) { *

result == [[1, 2, 2], * [0, 1, 5]] * - * @param data type for {@code output} output * @param sortedInputs 2-D Tensor where each row is ordered. * @param values 2-D Tensor with the same numbers of rows as {@code sorted_search_values}. Contains * the values that will be searched for in {@code sorted_search_values}. @@ -3736,7 +3687,6 @@ public LowerBound lowerBound(Operand sortedInputs, *

result == [[1, 2, 2], * [0, 1, 5]] * - * @param data type for {@code output} output * @param sortedInputs 2-D Tensor where each row is ordered. * @param values 2-D Tensor with the same numbers of rows as {@code sorted_search_values}. Contains * the values that will be searched for in {@code sorted_search_values}. @@ -3901,7 +3851,6 @@ public MapUnstageNoKey mapUnstageNoKey(Operand indices, * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -3921,7 +3870,6 @@ public Max max(Operand input, Operand{@code Merge} forwards the first tensor to become available to {@code output}, and sets * {@code value_index} to its index in {@code inputs}. * - * @param data type for {@code output} output * @param inputs The input tensors, exactly one of which will become available. * @param data type for {@code Merge} output and operands * @return a new instance of Merge @@ -3937,7 +3885,6 @@ public Merge merge(Iterable> inputs) { * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -3974,7 +3921,6 @@ public Min min(Operand input, Operand * - * @param data type for {@code output} output * @param input The input tensor to be padded. * @param paddings A two-column matrix specifying the padding sizes. The number of * rows must be the same as the rank of {@code input}. @@ -4008,7 +3954,6 @@ public MirrorPad mirrorPad(Operand input, * [11, 28]] * * - * @param data type for {@code output} output * @param input The input tensor to be folded. * @param paddings A two-column matrix specifying the padding sizes. The number of * rows must be the same as the rank of {@code input}. @@ -4187,7 +4132,6 @@ public MutexLock mutexLock(Operand mutex) { * num_devices: The number of devices participating in this reduction. * shared_name: Identifier that shared between ops of the same reduction. * - * @param data type for {@code data} output * @deprecated use {@link org.tensorflow.op.distribute.NcclAllReduce} instead * @param input The input value * @param reduction The value of the reduction attribute @@ -4211,7 +4155,6 @@ public NcclAllReduce ncclAllReduce(Operand input, Stri * output: The same as input. * shape: The shape of the input tensor. * - * @param data type for {@code output} output * @deprecated use {@link org.tensorflow.op.distribute.NcclBroadcast} instead * @param input The input value * @param shape The value of the shape attribute @@ -4232,7 +4175,6 @@ public NcclBroadcast ncclBroadcast(Operand input, Shap * data: the value of the reduction across all {@code num_devices} devices. * reduction: the reduction operation to perform. * - * @param data type for {@code data} output * @deprecated use {@link org.tensorflow.op.distribute.NcclReduce} instead * @param input The input value * @param reduction The value of the reduction attribute @@ -4248,7 +4190,6 @@ public NcclReduce ncclReduce(Iterable> input, /** * Makes its input available to the next iteration. * - * @param data type for {@code output} output * @param data The tensor to be made available to the next iteration. * @param data type for {@code NextIteration} output and operands * @return a new instance of NextIteration @@ -4343,7 +4284,6 @@ public NoOp noOp() { * ] * * - * @param data type for {@code output} output * @param indices A tensor of indices. * @param depth A scalar defining the depth of the one hot dimension. * @param onValue A scalar defining the value to fill in output when {@code indices[j] = i}. @@ -4372,7 +4312,6 @@ public Ones ones(Operand dims, Class /** * Returns a tensor of ones with the same shape and type as x. * - * @param data type for {@code y} output * @param x a tensor of type T. * @param data type for {@code OnesLike} output and operands * @return a new instance of OnesLike @@ -4506,7 +4445,6 @@ public OrderedMapUnstageNoKey orderedMapUnstageNoKey(Operand indices, * [0, 0, 0, 0, 0, 0]] * * - * @param data type for {@code output} output * @param input The input value * @param paddings The paddings value * @param constantValues The constantValues value @@ -4534,7 +4472,6 @@ public Pad pad(Operand input, Operand * will copy pieces of the input into the output as they become available, in * some situations this can provide a performance benefit. * - * @param data type for {@code output} output * @param values Tensors to be concatenated. All must have size 1 in the first dimension * and same shape. * @param shape the final shape of the result; should be equal to the shapes of any input @@ -4602,7 +4539,6 @@ public ParallelConcat parallelConcat(Iterable> v * * * - * @param data type for {@code merged} output * @param indices The indices value * @param data The data value * @param data type for {@code ParallelDynamicStitch} output and operands @@ -4641,7 +4577,6 @@ public PartitionedCall partitionedCall(Iterable> args, * intended as a way to represent a value that will always be fed, and to * provide attrs that enable the fed value to be checked at runtime. * - * @param data type for {@code output} output * @param dtype The type of elements in the tensor. * @param options carries optional attribute values * @param data type for {@code Placeholder} output and operands @@ -4655,7 +4590,6 @@ public Placeholder placeholder(Class dtype, /** * A placeholder op that passes through {@code input} when its output is not fed. * - * @param data type for {@code output} output * @param input The default value to produce when {@code output} is not fed. * @param shape The (possibly partial) shape of the tensor. * @param data type for {@code PlaceholderWithDefault} output and operands @@ -4685,7 +4619,6 @@ public Print print(Operand input, Print.Options... options) { * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -4701,7 +4634,6 @@ public Prod prod(Operand input, Operand data type for {@code output} output * @param tensor The tensor value * @param shape Defines the shape of the output tensor. * @param inputMin The minimum value of the input. @@ -4721,7 +4653,6 @@ public QuantizedReshape quantizedReshape(Operand tensor, * first dimension must match. *

The outputs are deterministic. * - * @param data type for {@code output} output * @param index A scalar tensor or a vector of dtype {@code dtype}. The index (or indices) to be shuffled. Must be within [0, max_index]. * @param seed A tensor of dtype {@code Tseed} and shape [3] or [n, 3]. The random seed. * @param maxIndex A scalar tensor or vector of dtype {@code dtype}. The upper bound(s) of the interval (inclusive). @@ -4746,7 +4677,6 @@ public RandomIndexShuffle randomIndexShuffle(Operand i * tf.range(start, limit, delta) ==> [3, 6, 9, 12, 15] * * - * @param data type for {@code output} output * @param start 0-D (scalar). First entry in the sequence. * @param limit 0-D (scalar). Upper limit of sequence, exclusive. * @param delta 0-D (scalar). Optional. Default is 1. Number that increments {@code start}. @@ -4785,7 +4715,6 @@ public Rank rank(Operand input) { * influenced by any of the writes which depend directly or indirectly on this * operation. * - * @param data type for {@code value} output * @param resource handle to the resource in which to store the variable. * @param dtype the dtype of the value. * @param data type for {@code ReadVariableOp} output and operands @@ -4799,7 +4728,6 @@ public ReadVariableOp readVariableOp(Operand data type for {@code tensor} output * @param tensorType The value of the tensorType attribute * @param tensorName The name of the tensor to receive. * @param sendDevice The name of the device sending the tensor. @@ -4857,7 +4785,6 @@ public ReduceAny reduceAny(Operand input, Operand axis * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -4877,7 +4804,6 @@ public ReduceMax reduceMax(Operand input, * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -4897,7 +4823,6 @@ public ReduceMin reduceMin(Operand input, * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -4917,7 +4842,6 @@ public ReduceProd reduceProd(Operand input, * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -4937,7 +4861,6 @@ public ReduceSum reduceSum(Operand input, Operand data type for {@code output} output * @param data The tensor to be made available to the child frame. * @param frameName The name of the child frame. * @param options carries optional attribute values @@ -4953,7 +4876,6 @@ public RefEnter refEnter(Operand data, String frameName, * Exits the current frame to its parent frame. * Exit makes its input {@code data} available to the parent frame. * - * @param data type for {@code output} output * @param data The tensor to be made available to the parent frame. * @param data type for {@code RefExit} output and operands * @return a new instance of RefExit @@ -4965,7 +4887,6 @@ public RefExit refExit(Operand data) { /** * Return the same ref tensor as the input ref tensor. * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code RefIdentity} output and operands * @return a new instance of RefIdentity @@ -4981,7 +4902,6 @@ public RefIdentity refIdentity(Operand input) { *

{@code Merge} forwards the first tensor for become available to {@code output}, and sets * {@code value_index} to its index in {@code inputs}. * - * @param data type for {@code output} output * @param inputs The input tensors, exactly one of which will become available. * @param data type for {@code RefMerge} output and operands * @return a new instance of RefMerge @@ -4993,7 +4913,6 @@ public RefMerge refMerge(Iterable> inputs) { /** * Makes its input available to the next iteration. * - * @param data type for {@code output} output * @param data The tensor to be made available to the next iteration. * @param data type for {@code RefNextIteration} output and operands * @return a new instance of RefNextIteration @@ -5005,7 +4924,6 @@ public RefNextIteration refNextIteration(Operand data) { /** * Forwards the {@code index}th element of {@code inputs} to {@code output}. * - * @param data type for {@code output} output * @param index A scalar that determines the input that gets selected. * @param inputs A list of ref tensors, one of which will be forwarded to {@code output}. * @param data type for {@code RefSelect} output and operands @@ -5022,7 +4940,6 @@ public RefSelect refSelect(Operand index, * the data goes to {@code output_false}. *

See also {@code Switch} and {@code Merge}. * - * @param data type for {@code output_false} output * @param data The ref tensor to be forwarded to the appropriate output. * @param pred A scalar that specifies which output port will receive data. * @param data type for {@code RefSwitch} output and operands @@ -5035,7 +4952,6 @@ public RefSwitch refSwitch(Operand data, Operand /** * The Relayout operation * - * @param data type for {@code output} output * @param input The input value * @param layout The value of the layout attribute * @param data type for {@code Relayout} output and operands @@ -5048,7 +4964,6 @@ public Relayout relayout(Operand input, String layout) { /** * The RelayoutLike operation * - * @param data type for {@code output} output * @param input The input value * @param layoutInput The layoutInput value * @param data type for {@code RelayoutLike} output and operands @@ -5130,7 +5045,6 @@ public RemoteCall remoteCall(Operand target, Iterable> args, * reshape(t, []) ==> 7 * * - * @param data type for {@code output} output * @param tensor The tensor value * @param shape Defines the shape of the output tensor. * @param data type for {@code Reshape} output and operands @@ -5143,7 +5057,6 @@ public Reshape reshape(Operand tensor, Operand data type for {@code output} output * @param resource Should be from a scalar {@code Variable} node. * @param limit If incrementing ref would bring it above limit, instead generates an * 'OutOfRange' error. @@ -5171,7 +5084,6 @@ public ResourceCountUpTo resourceCountUpTo( * output[i, ..., j, :, ... :] = params[indices[i, ..., j], :, ..., :] * * - * @param data type for {@code output} output * @param resource The resource value * @param indices The indices value * @param dtype The value of the dtype attribute @@ -5187,7 +5099,6 @@ public ResourceGather resourceGather(Operand data type for {@code output} output * @param resource The resource value * @param indices The indices value * @param dtype The value of the dtype attribute @@ -5633,7 +5544,6 @@ public ResourceStridedSliceAssign resourceStridedSliceAssign * [12, 13, 14, 15]]]] * * - * @param data type for {@code output} output * @param tensor Up to 8-D. * @param axis 1-D. The indices of the dimensions to reverse. Must be in the range * {@code [-rank(tensor), rank(tensor))}. @@ -5695,7 +5605,6 @@ public Reverse reverse(Operand tensor, Operand * - * @param data type for {@code output} output * @param input The input to reverse. * @param seqLengths 1-D with length {@code input.dims(batch_dim)} and * {@code max(seq_lengths) <= input.dims(seq_dim)} @@ -5730,7 +5639,6 @@ public ReverseSequence reverseSequence(Operand input, * roll(t, shift=[2, -3], axis=[1, 1]) ==> [[1, 2, 3, 4, 0], [6, 7, 8, 9, 5]] * * - * @param data type for {@code output} output * @param input The input value * @param shift Dimension must be 0-D or 1-D. {@code shift[i]} specifies the number of places by which * elements are shifted positively (towards larger indices) along the dimension @@ -5770,7 +5678,6 @@ public Roll roll(Operand input, Operand * * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param indices A tensor of indices into the first dimension of {@code ref}. * @param updates A tensor of updated values to add to {@code ref}. @@ -5802,7 +5709,6 @@ public ScatterAdd scatterAdd(Operand ref, * the same location, their contributions divide. *

Requires {@code updates.shape = indices.shape + ref.shape[1:]} or {@code updates.shape = []}. * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param indices A tensor of indices into the first dimension of {@code ref}. * @param updates A tensor of values that {@code ref} is divided by. @@ -5837,7 +5743,6 @@ public ScatterDiv scatterDiv(Operand ref, * * * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param indices A tensor of indices into the first dimension of {@code ref}. * @param updates A tensor of updated values to reduce into {@code ref}. @@ -5872,7 +5777,6 @@ public ScatterMax scatterMax(Operand ref, * * * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param indices A tensor of indices into the first dimension of {@code ref}. * @param updates A tensor of updated values to reduce into {@code ref}. @@ -5904,7 +5808,6 @@ public ScatterMin scatterMin(Operand ref, * the same location, their contributions multiply. *

Requires {@code updates.shape = indices.shape + ref.shape[1:]} or {@code updates.shape = []}. * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param indices A tensor of indices into the first dimension of {@code ref}. * @param updates A tensor of updated values to multiply to {@code ref}. @@ -5993,7 +5896,6 @@ public ScatterMul scatterMul(Operand ref, *

Note that on CPU, if an out of bound index is found, an error is returned. * On GPU, if an out of bound index is found, the index is ignored. * - * @param data type for {@code output} output * @param indices Tensor of indices. * @param updates Values to scatter into the output tensor. * @param shape 1-D. The shape of the output tensor. @@ -6035,7 +5937,6 @@ public ScatterNd scatterNd(Operand in *

See {@code tf.scatter_nd} for more details about how to make updates to * slices. * - * @param data type for {@code output_ref} output * @param ref A mutable Tensor. Should be from a Variable node. * @param indices A Tensor. Must be one of the following types: int32, int64. * A tensor of indices into ref. @@ -6053,7 +5954,6 @@ public ScatterNdAdd scatterNdAdd(Operand ref, /** * Computes element-wise maximum. * - * @param data type for {@code output_ref} output * @param ref A mutable Tensor. Should be from a Variable node. * @param indices A Tensor. Must be one of the following types: int32, int64. * A tensor of indices into ref. @@ -6071,7 +5971,6 @@ public ScatterNdMax scatterNdMax(Operand ref, /** * Computes element-wise minimum. * - * @param data type for {@code output_ref} output * @param ref A mutable Tensor. Should be from a Variable node. * @param indices A Tensor. Must be one of the following types: int32, int64. * A tensor of indices into ref. @@ -6116,7 +6015,6 @@ public ScatterNdMin scatterNdMin(Operand ref, * *

See {@code tf.scatter_nd} for more details about how to make updates to slices. * - * @param data type for {@code output} output * @param input A Tensor. * @param indices A Tensor. Must be one of the following types: {@code int32}, {@code int64}. * A tensor of indices into {@code input}. @@ -6160,7 +6058,6 @@ public ScatterNdNonAliasingAdd scatterNdNonAliasingAdd(Oper *

See {@code tf.scatter_nd} for more details about how to make updates to * slices. * - * @param data type for {@code output_ref} output * @param ref A mutable Tensor. Should be from a Variable node. * @param indices A Tensor. Must be one of the following types: int32, int64. * A tensor of indices into ref. @@ -6204,7 +6101,6 @@ public ScatterNdSub scatterNdSub(Operand ref, * slices. *

See also {@code tf.scatter_update} and {@code tf.batch_scatter_update}. * - * @param data type for {@code output_ref} output * @param ref A mutable Tensor. Should be from a Variable node. * @param indices A Tensor. Must be one of the following types: int32, int64. * A tensor of indices into ref. @@ -6240,7 +6136,6 @@ public ScatterNdUpdate scatterNdUpdate(Operand ref, * * * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param indices A tensor of indices into the first dimension of {@code ref}. * @param updates A tensor of updated values to subtract from {@code ref}. @@ -6277,7 +6172,6 @@ public ScatterSub scatterSub(Operand ref, * *

See also {@code tf.batch_scatter_update} and {@code tf.scatter_nd_update}. * - * @param data type for {@code output_ref} output * @param ref Should be from a {@code Variable} node. * @param indices A tensor of indices into the first dimension of {@code ref}. * @param updates A tensor of updated values to store in {@code ref}. @@ -6293,7 +6187,6 @@ public ScatterUpdate scatterUpdate(Operand ref, /** * The SelectV2 operation * - * @param data type for {@code output} output * @param condition The condition value * @param t The t value * @param e The e value @@ -6339,8 +6232,6 @@ public Send send(Operand tensor, String tensorName, String send * idx ==> [1, 3, 5] * * - * @param data type for {@code out} output - * @param data type for {@code idx} output * @param x 1-D. Values to keep. * @param y 1-D. Values to remove. * @param data type for {@code ListDiff} output and operands @@ -6369,8 +6260,6 @@ public SetDiff1d setDiff1d(Operand x, Operand * idx ==> [1, 3, 5] * * - * @param data type for {@code out} output - * @param data type for {@code idx} output * @param x 1-D. Values to keep. * @param y 1-D. Values to remove. * @param outIdx The value of the outIdx attribute @@ -6412,7 +6301,6 @@ public SetSize setSize(Operand setIndices, Operand setV * shape(t) ==> [2, 2, 3] * * - * @param data type for {@code output} output * @param input The input value * @return a new instance of Shape, with default output types */ @@ -6429,7 +6317,6 @@ public org.tensorflow.op.core.Shape shape(Operand input * shape(t) ==> [2, 2, 3] * * - * @param data type for {@code output} output * @param input The input value * @param outType The value of the outType attribute * @param data type for {@code Shape} output and operands @@ -6444,7 +6331,6 @@ public org.tensorflow.op.core.Shape shape(Operand data type for {@code output} output * @param input The input value * @return a new instance of ShapeN, with default output types */ @@ -6456,7 +6342,6 @@ public ShapeN shapeN(Iterable> input) { * Returns shape of tensors. * This operation returns N 1-D integer tensors representing shape of {@code input[i]s}. * - * @param data type for {@code output} output * @param input The input value * @param outType The value of the outType attribute * @param data type for {@code ShapeN} output and operands @@ -6477,7 +6362,6 @@ public ShapeN shapeN(Iterable> i * size(t) ==> 12 * * - * @param data type for {@code output} output * @param input The input value * @return a new instance of Size, with default output types */ @@ -6495,7 +6379,6 @@ public Size size(Operand input) { * size(t) ==> 12 * * - * @param data type for {@code output} output * @param input The input value * @param outType The value of the outType attribute * @param data type for {@code Size} output and operands @@ -6525,7 +6408,6 @@ public Skipgram skipgram(String filename, Long batchSize, Skipgram.Options... op *

Requirements: * 0 <= begin[i] <= begin[i] + size[i] <= Di for i in [0, n) * - * @param data type for {@code output} output * @param input The input value * @param begin begin[i] specifies the offset into the 'i'th dimension of * 'input' to slice from. @@ -6545,7 +6427,6 @@ public Slice slice(Operand input, Ope /** * Returns a copy of the input tensor. * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code Snapshot} output and operands * @return a new instance of Snapshot @@ -6653,7 +6534,6 @@ public Snapshot snapshot(Operand input) { *

Among others, this operation is useful for reducing atrous convolution into * regular convolution. * - * @param data type for {@code output} output * @param input N-D with shape {@code input_shape = [batch] + spatial_shape + remaining_shape}, * where spatial_shape has {@code M} dimensions. * @param blockShape 1-D with shape {@code [M]}, all values must be >= 1. @@ -6672,7 +6552,6 @@ public SpaceToBatchNd spaceToBatchNd(Operand input, /** * Splits a tensor into {@code num_split} tensors along one dimension. * - * @param data type for {@code output} output * @param axis 0-D. The dimension along which to split. Must be in the range * {@code [-rank(value), rank(value))}. * @param value The tensor to split. @@ -6688,7 +6567,6 @@ public Split split(Operand axis, Operand value, /** * Splits a tensor into {@code num_split} tensors along one dimension. * - * @param data type for {@code output} output * @param value The tensor to split. * @param sizeSplits list containing the sizes of each output tensor along the split * dimension. Must sum to the dimension of value along split_dim. @@ -6721,7 +6599,6 @@ public SplitV splitV(Operand value, Operand * - * @param data type for {@code output} output * @param input The {@code input} to squeeze. * @param options carries optional attribute values * @param data type for {@code Squeeze} output and operands @@ -6749,7 +6626,6 @@ public Squeeze squeeze(Operand input, Squeeze.Options... * *

This is the opposite of {@code unpack}. * - * @param data type for {@code output} output * @param values Must be of same shape and type. * @param options carries optional attribute values * @param data type for {@code Pack} output and operands @@ -6787,7 +6663,6 @@ public StackCreate stackCreate(Operand maxSize, Class< /** * Pop the element at the top of the stack. * - * @param data type for {@code elem} output * @param handle The handle to a stack. * @param elemType The type of the elem that is popped. * @param data type for {@code StackPopV2} output and operands @@ -6801,7 +6676,6 @@ public StackPop stackPop(Operand handle, /** * Push an element onto the stack. * - * @param data type for {@code output} output * @param handle The handle to a stack. * @param elem The tensor to be pushed onto the stack. * @param options carries optional attribute values @@ -7083,7 +6957,6 @@ public StatelessWhile statelessWhile(Iterable> input, ConcreteFunctio * The values are cast with a deterministic pseudo-random tensor from a uniform distribution generated from user given key, counter, algorithm. Values will saturate if out of the specified integer type range, and will become zero if inputs are NaN. *

The outputs are a deterministic function of {@code input}, {@code key}, {@code counter}, {@code alg}. * - * @param data type for {@code output} output * @param input The operand to stochastically cast to int. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -7151,7 +7024,6 @@ public StochasticCastToInt stochasticCastToInt( * example generation process. * * - * @param data type for {@code output} output * @param input The input value * @param data type for {@code StopGradient} output and operands * @return a new instance of StopGradient @@ -7169,16 +7041,17 @@ public StopGradient stopGradient(Operand input) { * equal to `n`, but this need not be the case. Each range specification entry can be one of the * following: * - *

- An ellipsis (...) using {@link Indices#ellipsis()}. Ellipses are used to imply zero or - * more dimensions of full-dimension selection. For example, {@code stridedSlice(foo, - * Indices.ellipsis()} is the identity slice. + *

- An ellipsis (...) using {@link org.tensorflow.ndarray.index.Indices#ellipsis()}. Ellipses + * are used to imply zero or more dimensions of full-dimension selection. For example, {@code + * stridedSlice(foo, Indices.ellipsis()} is the identity slice. * - *

- A new axis using {@link Indices#newAxis()}. This is used to insert a new shape=1 - * dimension. For example, `{@code stridedSlice(foo, Indices.newAxis())} where {@code foo} is - * shape {@code (3, 4)} produces a {@code (1, 3, 4)} tensor. + *

- A new axis using {@link org.tensorflow.ndarray.index.Indices#newAxis()}. This is used to + * insert a new shape=1 dimension. For example, `{@code stridedSlice(foo, Indices.newAxis())} + * where {@code foo} is shape {@code (3, 4)} produces a {@code (1, 3, 4)} tensor. * - *

- A range {@code begin:end:stride} using {@link Indices#slice(Long, Long, long)} - * Index.slice()} or {@link Indices#all()}. This is used to specify how much to choose from a + *

- A range {@code begin:end:stride} using {@link + * org.tensorflow.ndarray.index.Indices#slice(Long, Long, long)} Index.slice()} or {@link + * org.tensorflow.ndarray.index.Indices#all()}. This is used to specify how much to choose from a * given dimension. {@code stride} can be any integer but 0. {@code begin} is an integer which * represents the index of the first value to select while {@code end} represents the index of the * last value to select (exclusive). Begin and end can be null, in which case the index begins or @@ -7195,10 +7068,11 @@ public StopGradient stopGradient(Operand input) { * elements). For example {@code foo = [1,2,3,4]; stridedSlice(foo, Indices.slice(-2, null, -1)} * is {@code [4,3]}. * - *

- A single index using {@link Indices#at(long)}. This is used to keep only elements that - * have a given index. For example ({@code stridedSlice(foo, Indices.at(2))} on a shape {@code - * (5,6)} tensor produces a shape {@code (6,)} tensor. The dimension can be kept with size one - * using {@link Indices#at(long, boolean)}. + *

- A single index using {@link org.tensorflow.ndarray.index.Indices#at(long)}. This is used + * to keep only elements that have a given index. For example ({@code stridedSlice(foo, + * Indices.at(2))} on a shape {@code (5,6)} tensor produces a shape {@code (6,)} tensor. The + * dimension can be kept with size one using {@link org.tensorflow.ndarray.index.Indices#at(long, + * boolean)}. * *

These semantics generally follow NumPy's indexing semantics, which can be found here: https://numpy.org/doc/stable/reference/arrays.indexing.html @@ -7206,9 +7080,9 @@ public StopGradient stopGradient(Operand input) { *

Requirements: `0 != strides[i] for i in [0, m)` Only one ellipsis. * * @param data type for {@code output()} output - * @param indices The indices to slice. See {@link Indices}. + * @param indices The indices to slice. See {@link org.tensorflow.ndarray.index.Indices}. * @return a new instance of StridedSlice - * @see Indices + * @see org.tensorflow.ndarray.index.Indices */ public StridedSlice stridedSlice(Operand input, Index... indices) { return StridedSliceHelper.stridedSlice(scope, input, indices); @@ -7314,7 +7188,6 @@ public StridedSlice stridedSlice(Operand input, Index... * {@code 0 != strides[i] for i in [0, m)} * {@code ellipsis_mask must be a power of two (only one ellipsis)} * - * @param data type for {@code output} output * @param input The input value * @param begin {@code begin[k]} specifies the offset into the {@code k}th range specification. * The exact dimension this corresponds to will be determined by context. @@ -7351,9 +7224,10 @@ public StridedSlice stridedSlice(Operand * @param data type for {@code outputRef()} output * @param ref the tensor to assign to. * @param value the value to assign. - * @param indices The indices to slice. See {@link Indices}. + * @param indices The indices to slice. See {@link org.tensorflow.ndarray.index.Indices}. * @return a new instance of StridedSliceAssign - * @see org.tensorflow.op.Ops#stridedSlice(Operand, Index...) + * @see org.tensorflow.op.Ops#stridedSlice(org.tensorflow.Operand, + * org.tensorflow.ndarray.index.Index...) */ public StridedSliceAssign stridedSliceAssign(Operand ref, Operand value, Index... indices) { @@ -7368,7 +7242,6 @@ public StridedSliceAssign stridedSliceAssign(Operand ref *

NOTE this op currently does not support broadcasting and so {@code value}'s * shape must be exactly the shape produced by the slice of {@code ref}. * - * @param data type for {@code output_ref} output * @param ref The ref value * @param begin The begin value * @param end The end value @@ -7395,7 +7268,6 @@ public StridedSliceAssign stridedSliceAs * {@code dy} is the input gradient to be propagated and {@code shape} is the * shape of {@code StridedSlice}'s {@code input}. * - * @param data type for {@code output} output * @param shape The shape value * @param begin The begin value * @param end The end value @@ -7419,7 +7291,6 @@ public StridedSliceGrad stridedSliceGrad * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. * - * @param data type for {@code output} output * @param input The tensor to reduce. * @param axis The dimensions to reduce. Must be in the range * {@code [-rank(input), rank(input))}. @@ -7438,7 +7309,6 @@ public Sum sum(Operand input, Operand * the data goes to {@code output_false}. *

See also {@code RefSwitch} and {@code Merge}. * - * @param data type for {@code output_false} output * @param data The tensor to be forwarded to the appropriate output. * @param pred A scalar that specifies which output port will receive data. * @param data type for {@code Switch} output and operands @@ -7473,7 +7343,6 @@ public SyncDevice syncDevice() { * var = state_ops.assign_add(var, [[6.0, 7.0]]) * final = state_ops._destroy_temporary_variable(var, var_name=var_name) * - * @param data type for {@code ref} output * @param shape The shape of the variable tensor. * @param dtype The type of elements in the variable tensor. * @param options carries optional attribute values @@ -7524,7 +7393,6 @@ public TensorArrayClose tensorArrayClose(Operand handle) { * *

All elements must have the same shape (excepting the first dimension). * - * @param data type for {@code value} output * @param handle The handle to a TensorArray. * @param flowIn A float scalar that enforces proper chaining of operations. * @param dtype The type of the elem that is returned. @@ -7541,7 +7409,6 @@ public TensorArrayConcat tensorArrayConcat(Operand data type for {@code value} output * @param handle The handle to a TensorArray. * @param indices The locations in the TensorArray from which to read tensor elements. * @param flowIn A float scalar that enforces proper chaining of operations. @@ -7622,7 +7489,6 @@ public TensorArrayGradWithShape tensorArrayGradWithShape(Operand data type for {@code value} output * @param handle The handle value * @param flowIn The flowIn value * @param dtype The value of the dtype attribute @@ -7638,7 +7504,6 @@ public TensorArrayPack tensorArrayPack(Operand han /** * Read an element from the TensorArray into output {@code value}. * - * @param data type for {@code value} output * @param handle The handle to a TensorArray. * @param index The index value * @param flowIn A float scalar that enforces proper chaining of operations. @@ -7750,7 +7615,6 @@ public TensorArrayWrite tensorArrayWrite(Operand handle, Operan * tensor: The concated result. * lengths: Output tensor containing sizes of the 0th dimension of tensors in the list, used for computing the gradient. * - * @param data type for {@code tensor} output * @param inputHandle The inputHandle value * @param elementShape The elementShape value * @param leadingDims The leadingDims value @@ -7783,7 +7647,6 @@ public TensorListConcatLists tensorListConcatLists( * input_handle: the list * element_shape: the shape of elements of the list * - * @param data type for {@code element_shape} output * @param inputHandle The inputHandle value * @param shapeType The value of the shapeType attribute * @param data type for {@code TensorListElementShape} output and operands @@ -7817,7 +7680,6 @@ public TensorListFromTensor tensorListFromTensor(Operand tensor * indices: The indices used to index into the list. * values: The tensor. * - * @param data type for {@code values} output * @param inputHandle The inputHandle value * @param indices The indices value * @param elementShape The elementShape value @@ -7837,7 +7699,6 @@ public TensorListGather tensorListGather( * index: the position in the list from which an element will be retrieved * item: the element at that position * - * @param data type for {@code item} output * @param inputHandle The inputHandle value * @param index The index value * @param elementShape The elementShape value @@ -7871,7 +7732,6 @@ public TensorListLength tensorListLength(Operand inputHandle) { * element_dtype: the type of elements in the list * element_shape: the shape of the output tensor * - * @param data type for {@code tensor} output * @param inputHandle The inputHandle value * @param elementShape The elementShape value * @param elementDtype The value of the elementDtype attribute @@ -8033,7 +7893,6 @@ public TensorListSplit tensorListSplit(Operand tensor, * tensor: the gathered result * num_elements: optional. If not -1, the number of elements in the list. * - * @param data type for {@code tensor} output * @param inputHandle The inputHandle value * @param elementShape The elementShape value * @param elementDtype The value of the elementDtype attribute @@ -8101,7 +7960,6 @@ public TensorMapInsert tensorMapInsert(Operand inputHandle, * key: the key to be looked up * value: the value found from the given key * - * @param data type for {@code value} output * @param inputHandle The inputHandle value * @param key The key value * @param valueDtype The value of the valueDtype attribute @@ -8130,7 +7988,6 @@ public TensorMapSize tensorMapSize(Operand inputHandle) { * input_handle: the input map * keys: the returned Tensor of all keys in the map * - * @param data type for {@code keys} output * @param inputHandle The inputHandle value * @param keyDtype The value of the keyDtype attribute * @param data type for {@code TensorMapStackKeys} output and operands @@ -8204,7 +8061,6 @@ public TensorMapStackKeys tensorMapStackKeys( *

Note: on CPU, if an out of bound index is found, an error is returned. * On GPU, if an out of bound index is found, the index is ignored. * - * @param data type for {@code output} output * @param tensor Tensor to copy/update. * @param indices Index tensor. * @param updates Updates to scatter into output. @@ -8233,7 +8089,6 @@ public TensorScatterNdAdd tensorScatterNdAdd(Operand ten * *

Refer to {@code tf.tensor_scatter_nd_update} for more details. * - * @param data type for {@code output} output * @param tensor Tensor to update. * @param indices Index tensor. * @param updates Updates to scatter into output. @@ -8248,7 +8103,6 @@ public TensorScatterNdMax tensorScatterNdMax(Operand ten /** * The TensorScatterMin operation * - * @param data type for {@code output} output * @param tensor Tensor to update. * @param indices Index tensor. * @param updates Updates to scatter into output. @@ -8318,7 +8172,6 @@ public TensorScatterNdMin tensorScatterNdMin(Operand ten *

Note that on CPU, if an out of bound index is found, an error is returned. * On GPU, if an out of bound index is found, the index is ignored. * - * @param data type for {@code output} output * @param tensor Tensor to copy/update. * @param indices Index tensor. * @param updates Updates to scatter into output. @@ -8362,7 +8215,6 @@ public TensorScatterNdSub tensorScatterNdSub(Operand ten * *

For usage examples see the python tf.tensor_scatter_nd_update {@link org.tensorflow.op.Ops#tensorScatterNdUpdate} function * - * @param data type for {@code output} output * @param tensor Tensor to copy/update. * @param indices Index tensor. * @param updates Updates to scatter into output. @@ -8382,7 +8234,6 @@ public TensorScatterNdUpdate tensorScatterNdUpdate(Operand< *

NOTE this op currently does not support broadcasting and so {@code value}'s shape * must be exactly the shape produced by the slice of {@code input}. * - * @param data type for {@code output} output * @param input The input value * @param begin The begin value * @param end The end value @@ -8433,7 +8284,6 @@ public TensorStridedSliceUpdate tensorSt * * * - * @param data type for {@code output} output * @param input Can be of any rank. * @param multiples 1-D. Length must be the same as the number of dimensions in {@code input} * @param data type for {@code Tile} output and operands @@ -8522,7 +8372,6 @@ public TopKWithUnique topKWithUnique(Operand input, Long k) { * assumed to possibly belong to the same batch. If left empty, the op name will * be used as the shared name. * - * @param data type for {@code unbatched_tensor} output * @param batchedTensor The batchedTensor value * @param batchIndex The batchIndex value * @param id The id value @@ -8552,7 +8401,6 @@ public Unbatch unbatch(Operand batchedTensor, Operand data type for {@code batched_grad} output * @param originalInput The originalInput value * @param batchIndex The batchIndex value * @param grad The grad value @@ -8573,7 +8421,6 @@ public UnbatchGrad unbatchGrad(Operand originalInput, * If quantization_axis is -1 (per-tensor quantized), the entire operand is clipped using scalar min, max. * Otherwise (per-channel quantized), the clipping is also done per-channel. * - * @param data type for {@code output} output * @param operand Must be a Tensor of T. * @param min The min value(s) to clip operand. Must be a Tensor of T. * Must be a scalar Tensor if quantization_axis is -1 (per-tensor quantization), otherwise 1D Tensor of size (operand.dim_size(quantization_axis),) (per-axis quantization). @@ -8635,8 +8482,6 @@ public UniformQuantizedClipByValue uniformQuantizedClipBy * idx ==> [0, 1, 1] * * - * @param data type for {@code y} output - * @param data type for {@code idx} output * @param x A {@code Tensor}. * @param axis A {@code Tensor} of type {@code int32} (default: None). The axis of the Tensor to * find the unique elements. @@ -8686,8 +8531,6 @@ public Unique unique(Operand x, Operand * - * @param data type for {@code y} output - * @param data type for {@code idx} output * @param x A {@code Tensor}. * @param axis A {@code Tensor} of type {@code int32} (default: None). The axis of the Tensor to * find the unique elements. @@ -8744,8 +8587,6 @@ public Unique unique(Operand x, * count ==> [1, 2] * * - * @param data type for {@code y} output - * @param data type for {@code idx} output * @param x A {@code Tensor}. * @param axis A {@code Tensor} of type {@code int32} (default: None). The axis of the Tensor to * find the unique elements. @@ -8800,8 +8641,6 @@ public UniqueWithCounts uniqueWithCounts(Operand * count ==> [1, 2] * * - * @param data type for {@code y} output - * @param data type for {@code idx} output * @param x A {@code Tensor}. * @param axis A {@code Tensor} of type {@code int32} (default: None). The axis of the Tensor to * find the unique elements. @@ -8835,7 +8674,6 @@ public UniqueWithCounts uniqueWithCou * Equivalent to np.unravel_index *
{@literal @}end_compatibility * - * @param data type for {@code output} output * @param indices An 0-D or 1-D {@code int} Tensor whose elements are indices into the * flattened version of an array of dimensions dims. * @param dims An 1-D {@code int} Tensor. The shape of the array to use for unraveling @@ -8859,7 +8697,6 @@ public UnravelIndex unravelIndex(Operand indices, Oper * Etc. *

This is the opposite of {@code pack}. * - * @param data type for {@code output} output * @param value 1-D or higher, with {@code axis} dimension size equal to {@code num}. * @param num The value of the num attribute * @param options carries optional attribute values @@ -8900,7 +8737,6 @@ public Unstage unstage(List> dtypes, Unstage.Options... o *

result == [[1, 2, 4], * [0, 2, 5]] * - * @param data type for {@code output} output * @param sortedInputs 2-D Tensor where each row is ordered. * @param values 2-D Tensor with the same numbers of rows as {@code sorted_search_values}. Contains * the values that will be searched for in {@code sorted_search_values}. @@ -8928,7 +8764,6 @@ public UpperBound upperBound(Operand sortedInputs, *

result == [[1, 2, 4], * [0, 2, 5]] * - * @param data type for {@code output} output * @param sortedInputs 2-D Tensor where each row is ordered. * @param values 2-D Tensor with the same numbers of rows as {@code sorted_search_values}. Contains * the values that will be searched for in {@code sorted_search_values}. @@ -8988,7 +8823,6 @@ public Variable variable(Operand init, Variable.Options. * TODO(zhifengc/mrry): Adds a pointer to a more detail document * about sharing states in tensorflow. * - * @param data type for {@code ref} output * @param shape The shape of the variable tensor. * @param dtype The type of elements in the variable tensor. * @param options carries optional attribute values @@ -9009,7 +8843,6 @@ public Variable variable(Shape shape, Class dtype, * shape(t) ==> [2, 2, 3] * * - * @param data type for {@code output} output * @param input The input value * @return a new instance of VariableShape, with default output types */ @@ -9026,7 +8859,6 @@ public VariableShape variableShape(Operand input) { * shape(t) ==> [2, 2, 3] * * - * @param data type for {@code output} output * @param input The input value * @param outType The value of the outType attribute * @param data type for {@code VariableShape} output and operands @@ -9147,7 +8979,6 @@ public Zeros zeros(Operand dims, Class data type for {@code y} output * @param x a tensor of type T. * @param data type for {@code ZerosLike} output and operands * @return a new instance of ZerosLike @@ -9159,7 +8990,7 @@ public ZerosLike zerosLike(Operand x) { /** * Returns an API that builds operations with the provided name prefix. * - * @see {@link Scope#withSubScope(String)} + * @see Scope#withSubScope(String) */ public Ops withSubScope(String childScopeName) { return new Ops(scope.withSubScope(childScopeName)); @@ -9181,7 +9012,7 @@ public Ops withInitScope() { /** * Returns an API that uses the provided name for an op. * - * @see {@link Scope#withName(String)} + * @see Scope#withName(String) */ public Ops withName(String opName) { return new Ops(scope.withName(opName)); @@ -9190,7 +9021,7 @@ public Ops withName(String opName) { /** * Returns an API that places the created operations on the device(s) matching the provided spec. * - * @see {@link Scope#withDevice(DeviceSpec)} + * @see Scope#withDevice(DeviceSpec) */ public Ops withDevice(DeviceSpec deviceSpec) { return new Ops(scope.withDevice(deviceSpec)); @@ -9199,7 +9030,7 @@ public Ops withDevice(DeviceSpec deviceSpec) { /** * Returns an API that adds operations to the graph with the provided control dependencies. * - * @see {@link Scope#withControlDependencies(Iterable>)} + * @see Scope#withControlDependencies(Iterable) */ public Ops withControlDependencies(Iterable controls) { return new Ops(scope.withControlDependencies(controls)); @@ -9208,7 +9039,7 @@ public Ops withControlDependencies(Iterable controls) { /** * Returns an API that adds operations to the graph with the provided control dependencies. * - * @see {@link Scope#withControlDependencies(Iterable>)} + * @see Scope#withControlDependencies(Iterable) */ public Ops withControlDependencies(Op... controls) { return withControlDependencies(Arrays.asList(controls)); @@ -9217,7 +9048,7 @@ public Ops withControlDependencies(Op... controls) { /** * Returns an API that adds operations to the graph with the provided control dependencies. * - * @see {@link Scope#withControlDependencyOps(Iterable)} + * @see Scope#withControlDependencyOps(Iterable) */ public Ops withControlDependencyOps(Iterable controls) { return new Ops(scope.withControlDependencyOps(controls)); @@ -9226,7 +9057,7 @@ public Ops withControlDependencyOps(Iterable controls) { /** * Returns an API that adds operations to the graph with the provided control dependencies. * - * @see {@link Scope#withControlDependencyOps(Iterable)} + * @see Scope#withControlDependencyOps(Iterable) */ public Ops withControlDependencyOps(Operation... controls) { return withControlDependencyOps(Arrays.asList(controls)); diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java index 54527d187d0..c01f6462dac 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/QuantizationOps.java @@ -49,7 +49,7 @@ /** * An API for building {@code quantization} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class QuantizationOps { private final Scope scope; @@ -107,7 +107,6 @@ public final class QuantizationOps { * max_range / max_expected_T); * * - * @param data type for {@code output} output * @param input The input value * @param minRange The minimum scalar value possibly produced for the input. * @param maxRange The maximum scalar value possibly produced for the input. @@ -165,7 +164,6 @@ public Dequantize dequantize(Operand input, * max_range / max_expected_T); * * - * @param data type for {@code output} output * @param input The input value * @param minRange The minimum scalar value possibly produced for the input. * @param maxRange The maximum scalar value possibly produced for the input. @@ -456,7 +454,6 @@ public FakeQuantWithMinMaxVarsPerChannelGradient fakeQuantWithMinMaxVarsPerChann * The legacy default value for this is 0.01, but it is strongly suggested to * set it to 0 for new uses. * - * @param data type for {@code output} output * @param input The input value * @param minRange The minimum value of the quantization range. This value may be adjusted by the * op depending on other parameters. The adjusted value is written to {@code output_min}. @@ -482,7 +479,6 @@ public Quantize quantize(Operand input, * This is almost identical to QuantizeAndDequantizeV2, except that num_bits is a * tensor, so its value can change during training. * - * @param data type for {@code output} output * @param input The input value * @param inputMin The inputMin value * @param inputMax The inputMax value @@ -502,7 +498,6 @@ public QuantizeAndDequantize quantizeAndDequantize(Operan * This is almost identical to QuantizeAndDequantizeV2, except that num_bits is a * tensor, so its value can change during training. * - * @param data type for {@code output} output * @param input The input value * @param inputMin The inputMin value * @param inputMax The inputMax value @@ -522,7 +517,6 @@ public QuantizeAndDequantizeV3 quantizeAndDequantizeV3(Op * This is almost identical to QuantizeAndDequantizeV2, except that it returns a * gradient of 1 for inputs that are within the quantization range, or 0 otherwise. * - * @param data type for {@code output} output * @param input Tensor to quantize and then dequantize. * @param inputMin If {@code range_given == True}, this specifies the minimum input value that needs to * be represented, otherwise it is determined from the min value of the {@code input} @@ -544,7 +538,6 @@ public QuantizeAndDequantizeV4 quantizeAndDequantizeV4(Op * Returns a gradient of 1 for inputs that are within the quantization range, * or 0 otherwise. * - * @param data type for {@code input_backprop} output * @param gradients The gradients value * @param input The input value * @param inputMin The inputMin value @@ -581,7 +574,6 @@ public QuantizeAndDequantizeV4Grad quantizeAndDequantizeV * that output into this operator, we can reduce it from 32 bits down to 8 with * minimal loss of accuracy. * - * @param data type for {@code output} output * @param input The input value * @param inputMin The float value that the minimum quantized input value represents. * @param inputMax The float value that the maximum quantized input value represents. @@ -598,7 +590,6 @@ public QuantizeDownAndShrinkRange quantizeDownAndShrinkRa /** * Concatenates quantized tensors along one dimension. * - * @param data type for {@code output} output * @param concatDim 0-D. The dimension along which to concatenate. Must be in the * range [0, rank(values)). * @param values The {@code N} Tensors to concatenate. Their ranks and types must match, @@ -617,7 +608,6 @@ public QuantizedConcat quantizedConcat(Operand conc /** * The QuantizedMatMulWithBiasAndDequantize operation * - * @param data type for {@code out} output * @param a The a value * @param b The b value * @param bias The bias value @@ -644,7 +634,6 @@ public QuantizedMatMulWithBiasAndDequantize quantizedMatM /** * The QuantizedMatMulWithBiasAndRequantize operation * - * @param data type for {@code out} output * @param a The a value * @param b The b value * @param bias The bias value @@ -694,7 +683,6 @@ public RequantizationRange requantizationRange(Operand input, * {@code input_max} is 1.0f, and we are dealing with {@code quint16} quantized data, then a 0 * value in the 16-bit data should be interpreted as -1.0f, and a 65535 means 1.0f. * - * @param data type for {@code output} output * @param input The input value * @param inputMin The float value that the minimum quantized input value represents. * @param inputMax The float value that the maximum quantized input value represents. @@ -715,7 +703,6 @@ public Requantize requantize(Operand i * Given quantized {@code input} which was quantized using {@code scales} and {@code zero_points}, performs dequantization using the formula: * dequantized_data = (quantized_data - zero_point) * scale. * - * @param data type for {@code output} output * @param input Must be a Tensor of Tin. * @param scales The float value(s) used as scale(s) when quantizing original data that input represents. * Must be a scalar Tensor if quantization_axis is -1 (per-tensor quantization), otherwise 1D Tensor of size (input.dim_size(quantization_axis),) (per-axis quantization). @@ -746,7 +733,6 @@ public UniformDequantize uniformDequantize( * Given {@code input}, {@code scales} and {@code zero_points}, performs quantization using the formula: * quantized_data = floor(input_data * (1.0f / scale) + 0.5f) + zero_point * - * @param data type for {@code output} output * @param input Must be a Tensor of Tin. * @param scales The float value(s) to use as scale(s) to quantize {@code input}. * Must be a scalar Tensor if quantization_axis is -1 (per-tensor quantization), otherwise 1D Tensor of size (input.dim_size(quantization_axis),) (per-axis quantization). @@ -780,7 +766,6 @@ public UniformQuantize uniformQuantize(Operand data type for {@code output} output * @param lhs Must be a 2D Tensor of Tin. * @param rhs Must be a 2D Tensor of Tin. * @param lhsScales The float value(s) used as scale when quantizing original data that lhs represents. @@ -833,7 +818,6 @@ public UniformQuantizedDot uniformQuan * {@code rhs} must be quantized Tensor, where its data value is quantized using the formula: * quantized_data = clip(original_data / scale + zero_point, quantization_min_val, quantization_max_val). * - * @param data type for {@code output} output * @param lhs Must be a 2D Tensor of Tlhs. * @param rhs Must be a 2D Tensor of Trhs. * @param rhsScales The float value(s) used as scale when quantizing original data that rhs represents. @@ -873,7 +857,6 @@ public UniformQuantizedDotHybrid uniformQuantizedDotHybri * i.e. At least one among input_quantization_axis and output_quantization_axis must be -1, or two must be equal. * * - * @param data type for {@code output} output * @param input Must be a Tensor of Tin. * @param inputScales The float value(s) used as scale(s) when quantizing original data that {@code input} represents. * Must be a scalar Tensor if quantization_axis is -1 (per-tensor quantization), otherwise 1D Tensor of size (input.dim_size(quantization_axis),) (per-axis quantization). diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RaggedOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RaggedOps.java index ddc1e0c4c0e..43b18f0cf57 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RaggedOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RaggedOps.java @@ -39,7 +39,7 @@ /** * An API for building {@code ragged} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class RaggedOps { private final Scope scope; @@ -60,7 +60,6 @@ public final class RaggedOps { * {@code i}. *

Values in {@code arr} outside of the range [0, size) are ignored. * - * @param data type for {@code output} output * @param splits 1D int64 {@code Tensor}. * @param values 2D int {@code Tensor}. * @param sizeOutput non-negative int scalar {@code Tensor}. @@ -82,7 +81,6 @@ public RaggedBincount raggedBincount( * Performs sparse-output bin counting for a ragged tensor input. * Counts the number of times each value occurs in the input. * - * @param data type for {@code output_values} output * @param splits Tensor containing the row splits of the ragged tensor to count. * @param values Tensor containing values of the sparse tensor to count. * @param weights A Tensor of the same shape as indices containing per-index weight values. @@ -102,8 +100,6 @@ public RaggedCountSparseOutput raggedCountSparseOutput( * Generates a feature cross from a list of tensors, and returns it as a * RaggedTensor. See {@code tf.ragged.cross} for more details. * - * @param data type for {@code output_values} output - * @param data type for {@code output_row_splits} output * @param raggedValues The values tensor for each RaggedTensor input. * @param raggedRowSplits The row_splits tensor for each RaggedTensor input. * @param sparseIndices The indices tensor for each SparseTensor input. @@ -135,7 +131,6 @@ public RaggedCross raggedCross( /** * The RaggedFillEmptyRows operation * - * @param data type for {@code output_values} output * @param valueRowids The valueRowids value * @param values The values value * @param nrows The nrows value @@ -151,7 +146,6 @@ public RaggedFillEmptyRows raggedFillEmptyRows(Operand data type for {@code d_values} output * @param reverseIndexMap The reverseIndexMap value * @param gradValues The gradValues value * @param data type for {@code RaggedFillEmptyRowsGrad} output and operands @@ -183,8 +177,6 @@ public RaggedFillEmptyRowsGrad raggedFillEmptyRowsGrad( *

(Note: This c++ op is used to implement the higher-level python * {@code tf.ragged.gather} op, which also supports ragged indices.) * - * @param data type for {@code output_nested_splits} output - * @param data type for {@code output_dense_values} output * @param paramsNestedSplits The {@code nested_row_splits} tensors that define the row-partitioning for the * {@code params} RaggedTensor input. * @param paramsDenseValues The {@code flat_values} for the {@code params} RaggedTensor. There was a terminology change @@ -221,8 +213,6 @@ public RaggedGather raggedGather( * The vector inputs must all have the same size. Scalar inputs are broadcast * to match the size of the vector inputs. * - * @param data type for {@code rt_nested_splits} output - * @param data type for {@code rt_dense_values} output * @param starts The starts of each range. * @param limits The limits of each range. * @param deltas The deltas of each range. @@ -250,8 +240,6 @@ public RaggedRange raggedRange(Operand starts, * The vector inputs must all have the same size. Scalar inputs are broadcast * to match the size of the vector inputs. * - * @param data type for {@code rt_nested_splits} output - * @param data type for {@code rt_dense_values} output * @param starts The starts of each range. * @param limits The limits of each range. * @param deltas The deltas of each range. @@ -279,8 +267,6 @@ public RaggedRange raggedRange(Oper * inferred as {@code output_ragged_rank} - {@code rank(encoded_ragged)}. See * {@code RaggedTensorToVariant} for the corresponding encoding logic. * - * @param data type for {@code output_nested_splits} output - * @param data type for {@code output_dense_values} output * @param encodedRagged A {@code variant} Tensor containing encoded {@code RaggedTensor}s. * @param inputRaggedRank The ragged rank of each encoded {@code RaggedTensor} component in the input. If set to * -1, this is inferred as {@code output_ragged_rank} - {@code rank(encoded_ragged)} @@ -310,8 +296,6 @@ public RaggedTensorFromVariant raggedTensorFromVari * inferred as {@code output_ragged_rank} - {@code rank(encoded_ragged)}. See * {@code RaggedTensorToVariant} for the corresponding encoding logic. * - * @param data type for {@code output_nested_splits} output - * @param data type for {@code output_dense_values} output * @param encodedRagged A {@code variant} Tensor containing encoded {@code RaggedTensor}s. * @param inputRaggedRank The ragged rank of each encoded {@code RaggedTensor} component in the input. If set to * -1, this is inferred as {@code output_ragged_rank} - {@code rank(encoded_ragged)} @@ -335,7 +319,6 @@ public RaggedTensorFromVariant ragged * output=SparseTensor(indices=sparse_indices, values=sparse_values, * dense_shape=sparse_dense_shape) * - * @param data type for {@code sparse_values} output * @param rtNestedSplits The {@code row_splits} for the {@code RaggedTensor}. * @param rtDenseValues The {@code flat_values} for the {@code RaggedTensor}. * @param data type for {@code RaggedTensorToSparse} output and operands @@ -365,7 +348,6 @@ public RaggedTensorToSparse raggedTensorToSparse( * is preceded by "FIRST_DIM_SIZE". * * - * @param data type for {@code result} output * @param shape The desired shape of the output tensor. If left unspecified (empty), * the minimal shape required to contain all the elements in the ragged tensor * (the natural shape) will be used. If some dimensions are left unspecified, then @@ -438,7 +420,6 @@ public RaggedTensorToVariant raggedTensorToVariant( * the outer row-splits and the shape of the dense-values that were provided as * inputs to the RaggedTensorToVariant op. * - * @param data type for {@code dense_values_grad} output * @param encodedRaggedGrad A {@code variant} Tensor containing encoded {@code RaggedTensor} gradients. * @param rowSplits Outermost row-splits that were used as input to the RaggedTensorToVariant op. * @param denseValuesShape Shape of the dense_values that was used as an input to the diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomExperimentalOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomExperimentalOps.java index b1d86643cce..34d3585f270 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomExperimentalOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomExperimentalOps.java @@ -25,7 +25,7 @@ /** * An API for building {@code random.experimental} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class RandomExperimentalOps { private final Scope scope; @@ -49,7 +49,6 @@ public final class RandomExperimentalOps { * *

The outputs are a deterministic function of {@code value}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param value The tensor to be shuffled. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java index 8abc032de91..c5ff9a489a0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/RandomOps.java @@ -75,7 +75,7 @@ /** * An API for building {@code random} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class RandomOps { public final RandomExperimentalOps experimental; @@ -203,7 +203,6 @@ public LogUniformCandidateSampler logUniformCandidateSampler(Operand tru /** * Draws samples from a multinomial distribution. * - * @param data type for {@code output} output * @param logits 2-D Tensor with shape {@code [batch_size, num_classes]}. Each slice {@code [i, :]} * represents the unnormalized log probabilities for all classes. * @param numSamples 0-D. Number of independent samples to draw for each row slice. @@ -218,7 +217,6 @@ public Multinomial multinomial(Operand logits, /** * Draws samples from a multinomial distribution. * - * @param data type for {@code output} output * @param logits 2-D Tensor with shape {@code [batch_size, num_classes]}. Each slice {@code [i, :]} * represents the unnormalized log probabilities for all classes. * @param numSamples 0-D. Number of independent samples to draw for each row slice. @@ -236,7 +234,6 @@ public Multinomial multinomial(Operand * Non-deterministically generates some integers. * This op may use some OS-provided source of non-determinism (e.g. an RNG), so each execution will give different results. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @return a new instance of NonDeterministicInts, with default output types */ @@ -248,7 +245,6 @@ public NonDeterministicInts nonDeterministicInts(Operand data type for {@code output} output * @param shape The shape of the output tensor. * @param dtype The type of the output. * @param data type for {@code NonDeterministicInts} output and operands @@ -264,7 +260,6 @@ public NonDeterministicInts nonDeterministicInts( * scalar which applies to the entire output, or a vector of length shape[0] which * stores the parameters for each batch. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. Batches are indexed by the 0th dimension. * @param means The mean parameter of each batch. * @param stdevs The standard deviation parameter of each batch. Must be greater than 0. @@ -287,7 +282,6 @@ public ParameterizedTruncatedNormal parameterizedTruncate * transformation-rejection from pairs of uniform and normal random variables. * See http://dl.acm.org/citation.cfm?id=358414 * - * @param data type for {@code output} output * @param shape 1-D integer tensor. Shape of independent samples to draw from each * distribution described by the shape parameters given in alpha. * @param alpha A tensor in which each scalar is a "shape" parameter describing the @@ -304,7 +298,6 @@ public RandomGamma randomGamma(Operand /** * Computes the derivative of a Gamma random sample w.r.t. {@code alpha}. * - * @param data type for {@code output} output * @param alpha The alpha value * @param sample The sample value * @param data type for {@code RandomGammaGrad} output and operands @@ -326,7 +319,6 @@ public RandomGammaGrad randomGammaGrad(Operand alpha, * See Donald E. Knuth (1969). Seminumerical Algorithms. The Art of Computer * Programming, Volume 2. Addison Wesley * - * @param data type for {@code output} output * @param shape 1-D integer tensor. Shape of independent samples to draw from each * distribution described by the shape parameters given in rate. * @param rate A tensor in which each scalar is a "rate" parameter describing the @@ -350,7 +342,6 @@ public RandomPoisson randomPoisson(Operand shape, * See Donald E. Knuth (1969). Seminumerical Algorithms. The Art of Computer * Programming, Volume 2. Addison Wesley * - * @param data type for {@code output} output * @param shape 1-D integer tensor. Shape of independent samples to draw from each * distribution described by the shape parameters given in rate. * @param rate A tensor in which each scalar is a "rate" parameter describing the @@ -376,7 +367,6 @@ public RandomPoisson randomPoisson(Operand * - * @param data type for {@code output} output * @param value The tensor to be shuffled. * @param options carries optional attribute values * @param data type for {@code RandomShuffle} output and operands @@ -391,7 +381,6 @@ public RandomShuffle randomShuffle(Operand value, * Outputs random values from a normal distribution. * The generated values will have mean 0 and standard deviation 1. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param dtype The type of the output. * @param options carries optional attribute values @@ -408,7 +397,6 @@ public RandomStandardNormal randomStandardNormal( * The generated values follow a uniform distribution in the range {@code [0, 1)}. The * lower bound 0 is included in the range, while the upper bound 1 is excluded. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param dtype The type of the output. * @param options carries optional attribute values @@ -429,7 +417,6 @@ public RandomUniform randomUniform(Operand data type for {@code output} output * @param shape The shape of the output tensor. * @param minval 0-D. Inclusive lower bound on the generated integers. * @param maxval 0-D. Exclusive upper bound on the generated integers. @@ -491,7 +478,6 @@ public RngSkip rngSkip(Operand resource, Operand algori /** * The StatefulRandomBinomial operation * - * @param data type for {@code output} output * @param resource The resource value * @param algorithm The algorithm value * @param shape The shape value @@ -509,7 +495,6 @@ public StatefulRandomBinomial statefulRandomBinomial /** * The StatefulRandomBinomial operation * - * @param data type for {@code output} output * @param resource The resource value * @param algorithm The algorithm value * @param shape The shape value @@ -530,7 +515,6 @@ public StatefulRandomBinomial stateful * Outputs random values from a normal distribution. * The generated values will have mean 0 and standard deviation 1. * - * @param data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -545,7 +529,6 @@ public StatefulStandardNormal statefulStandardNormal(Operand data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -565,7 +548,6 @@ public StatefulStandardNormal statefulStandardNormal( * deviation 1, except that values whose magnitude is more than 2 standard * deviations from the mean are dropped and re-picked. * - * @param data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -583,7 +565,6 @@ public StatefulTruncatedNormal statefulTruncatedNormal( * deviation 1, except that values whose magnitude is more than 2 standard * deviations from the mean are dropped and re-picked. * - * @param data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -602,7 +583,6 @@ public StatefulTruncatedNormal statefulTruncatedNormal( * The generated values follow a uniform distribution in the range {@code [0, 1)}. The * lower bound 0 is included in the range, while the upper bound 1 is excluded. * - * @param data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -618,7 +598,6 @@ public StatefulUniform statefulUniform(Operand resour * The generated values follow a uniform distribution in the range {@code [0, 1)}. The * lower bound 0 is included in the range, while the upper bound 1 is excluded. * - * @param data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -635,7 +614,6 @@ public StatefulUniform statefulUniform(Operand data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -658,7 +636,6 @@ public StatefulUniformFullInt statefulUniformFullInt( * power of two. The bias is small for values of {@code maxval - minval} significantly * smaller than the range of the output (either {@code 2^32} or {@code 2^64}). * - * @param data type for {@code output} output * @param resource The handle of the resource variable that stores the state of the RNG. * @param algorithm The RNG algorithm. * @param shape The shape of the output tensor. @@ -676,7 +653,6 @@ public StatefulUniformInt statefulUniformInt( /** * Draws samples from a multinomial distribution. * - * @param data type for {@code output} output * @param logits 2-D Tensor with shape {@code [batch_size, num_classes]}. Each slice {@code [i, :]} * represents the unnormalized log probabilities for all classes. * @param numSamples 0-D. Number of independent samples to draw for each row slice. @@ -691,7 +667,6 @@ public StatelessMultinomial statelessMultinomial(Operand data type for {@code output} output * @param logits 2-D Tensor with shape {@code [batch_size, num_classes]}. Each slice {@code [i, :]} * represents the unnormalized log probabilities for all classes. * @param numSamples 0-D. Number of independent samples to draw for each row slice. @@ -709,7 +684,6 @@ public StatelessMultinomial statelessMultinomial( /** * The StatelessParameterizedTruncatedNormal operation * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param means The mean parameter of each batch. @@ -731,7 +705,6 @@ public StatelessParameterizedTruncatedNormal statelessPar * Outputs random values from a binomial distribution. *

The outputs are a deterministic function of {@code shape}, {@code seed}, {@code counts}, and {@code probs}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param counts The counts of the binomial distribution. Must be broadcastable with {@code probs}, @@ -752,7 +725,6 @@ public StatelessRandomBinomial statelessRandomBinomi * Outputs random values from a binomial distribution. *

The outputs are a deterministic function of {@code shape}, {@code seed}, {@code counts}, and {@code probs}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param counts The counts of the binomial distribution. Must be broadcastable with {@code probs}, @@ -775,7 +747,6 @@ public StatelessRandomBinomial statele * Outputs random values from a gamma distribution. *

The outputs are a deterministic function of the inputs. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -830,7 +801,6 @@ public StatelessRandomGetKeyCounterAlg statelessRandomGetKeyCounterAlg( * The generated values will have mean 0 and standard deviation 1. *

The outputs are a deterministic function of {@code shape} and {@code seed}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @return a new instance of StatelessRandomNormal, with default output types @@ -845,7 +815,6 @@ public StatelessRandomNormal statelessRandomNormal(OperandThe outputs are a deterministic function of {@code shape} and {@code seed}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param dtype The type of the output. @@ -862,7 +831,6 @@ public StatelessRandomNormal statelessRandomNormal( * The generated values will have mean 0 and standard deviation 1. *

The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -879,7 +847,6 @@ public StatelessRandomNormalV2 statelessRandomNormalV2(OperandThe outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -899,7 +866,6 @@ public StatelessRandomNormalV2 statelessRandomNormalV2( * Outputs random values from a Poisson distribution. *

The outputs are a deterministic function of {@code shape}, {@code seed}, and {@code lam}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param lam The rate of the Poisson distribution. Shape must match the rightmost dimensions @@ -920,7 +886,6 @@ public StatelessRandomPoisson statelessRandomPoisson( * lower bound 0 is included in the range, while the upper bound 1 is excluded. *

The outputs are a deterministic function of {@code shape} and {@code seed}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @return a new instance of StatelessRandomUniform, with default output types @@ -936,7 +901,6 @@ public StatelessRandomUniform statelessRandomUniform(OperandThe outputs are a deterministic function of {@code shape} and {@code seed}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param dtype The type of the output. @@ -953,7 +917,6 @@ public StatelessRandomUniform statelessRandomUniform( * The generated values are uniform integers covering the whole range of {@code dtype}. *

The outputs are a deterministic function of {@code shape} and {@code seed}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param dtype The type of the output. @@ -970,7 +933,6 @@ public StatelessRandomUniformFullInt statelessRandomUnifo * The generated values are uniform integers covering the whole range of {@code dtype}. *

The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -990,7 +952,6 @@ public StatelessRandomUniformFullIntV2 statelessRandomUni * The generated values follow a uniform distribution in the range {@code [minval, maxval)}. *

The outputs are a deterministic function of {@code shape}, {@code seed}, {@code minval}, and {@code maxval}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param minval Minimum value (inclusive, scalar). @@ -1009,7 +970,6 @@ public StatelessRandomUniformInt statelessRandomUniformIn * The generated values follow a uniform distribution in the range {@code [minval, maxval)}. *

The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter}, {@code alg}, {@code minval} and {@code maxval}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -1031,7 +991,6 @@ public StatelessRandomUniformIntV2 statelessRandomUniform * lower bound 0 is included in the range, while the upper bound 1 is excluded. *

The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -1050,7 +1009,6 @@ public StatelessRandomUniformV2 statelessRandomUniformV2( * lower bound 0 is included in the range, while the upper bound 1 is excluded. *

The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -1072,7 +1030,6 @@ public StatelessRandomUniformV2 statelessRandomUniformV2( * deviations from the mean are dropped and re-picked. *

The outputs are a deterministic function of {@code shape} and {@code seed}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @return a new instance of StatelessTruncatedNormal, with default output types @@ -1089,7 +1046,6 @@ public StatelessTruncatedNormal statelessTruncatedNormal( * deviations from the mean are dropped and re-picked. *

The outputs are a deterministic function of {@code shape} and {@code seed}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param seed 2 seeds (shape [2]). * @param dtype The type of the output. @@ -1108,7 +1064,6 @@ public StatelessTruncatedNormal statelessTruncatedNormal( * deviations from the mean are dropped and re-picked. *

The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -1128,7 +1083,6 @@ public StatelessTruncatedNormalV2 statelessTruncatedNormalV2( * deviations from the mean are dropped and re-picked. *

The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param key Key for the counter-based RNG algorithm (shape uint64[1]). * @param counter Initial counter for the counter-based RNG algorithm (shape uint64[2] or uint64[1] depending on the algorithm). If a larger vector is given, only the needed portion on the left (i.e. [:N]) will be used. @@ -1176,7 +1130,6 @@ public ThreadUnsafeUnigramCandidateSampler threadUnsafeUnigramCandidateSampler( * deviation 1, except that values whose magnitude is more than 2 standard * deviations from the mean are dropped and re-picked. * - * @param data type for {@code output} output * @param shape The shape of the output tensor. * @param dtype The type of the output. * @param options carries optional attribute values diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ShapeOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ShapeOps.java index 4b00d892c94..68cb802f86d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ShapeOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/ShapeOps.java @@ -28,7 +28,7 @@ /** * An API for building {@code shape} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class ShapeOps { private final Scope scope; @@ -388,7 +388,8 @@ public Operand tail(Shape shape, Class type) { * shape. * * @param shape the TensorFlow shape - * @param n the number of leading dimensions to get, must be <= than the shape's numDimensions() + * @param n the number of leading dimensions to get, must be less than or equal to the shape's + * numDimensions() * @return a 1-dimensional operand with the dimensions matching the first n dimensions of the * shape */ @@ -401,7 +402,8 @@ public Operand take(Shape shape, Operand n) { * shape. * * @param shape the TensorFlow shape - * @param n the number of leading dimensions to get, must be <= than the shape's numDimensions() + * @param n the number of leading dimensions to get, must be less than or equal to the shape's + * numDimensions() * @param type the shape datatype. * @param the shape datatype. * @return a 1-dimensional operand with the dimensions matching * the first n dimensions of the @@ -416,7 +418,8 @@ public Operand take(Shape shape, Operand n, Class Operand takeLast(Shape shape, Operand * shape. * * @param shape the TensorFlow shape - * @param n the number of leading dimensions to get, must be <= than the shape's numDimensions() + * @param n the number of leading dimensions to get, must be less than or equal to the shape's + * numDimensions() * @param type the shape datatype. * @param the shape datatype. * @return a 1-dimensional operand containing the dimensions matching the last n dimensions of the diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java index 0fb3e8edde0..ac5703c264a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SignalOps.java @@ -48,7 +48,7 @@ /** * An API for building {@code signal} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class SignalOps { private final Scope scope; @@ -125,7 +125,6 @@ public BatchIfft3d batchIfft3d(Operand input) { * Computes the 1-dimensional discrete Fourier transform over the inner-most * dimension of {@code input}. * - * @param data type for {@code output} output * @param input A complex tensor. * @param data type for {@code FFT} output and operands * @return a new instance of Fft @@ -139,7 +138,6 @@ public Fft fft(Operand input) { * Computes the 2-dimensional discrete Fourier transform over the inner-most * 2 dimensions of {@code input}. * - * @param data type for {@code output} output * @param input A complex tensor. * @param data type for {@code FFT2D} output and operands * @return a new instance of Fft2d @@ -153,7 +151,6 @@ public Fft2d fft2d(Operand input) { * Computes the 3-dimensional discrete Fourier transform over the inner-most 3 * dimensions of {@code input}. * - * @param data type for {@code output} output * @param input A complex tensor. * @param data type for {@code FFT3D} output and operands * @return a new instance of Fft3d @@ -173,7 +170,6 @@ public Fft3d fft3d(Operand input) { *

Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor. The FFT length for each dimension. * @param axes An int32 tensor with a same shape as fft_length. Axes to perform the transform. @@ -190,7 +186,6 @@ public FftNd fftNd(Operand input, Operand fftLen * Computes the inverse 1-dimensional discrete Fourier transform over the * inner-most dimension of {@code input}. * - * @param data type for {@code output} output * @param input A complex tensor. * @param data type for {@code IFFT} output and operands * @return a new instance of Ifft @@ -204,7 +199,6 @@ public Ifft ifft(Operand input) { * Computes the inverse 2-dimensional discrete Fourier transform over the * inner-most 2 dimensions of {@code input}. * - * @param data type for {@code output} output * @param input A complex tensor. * @param data type for {@code IFFT2D} output and operands * @return a new instance of Ifft2d @@ -218,7 +212,6 @@ public Ifft2d ifft2d(Operand input) { * Computes the inverse 3-dimensional discrete Fourier transform over the * inner-most 3 dimensions of {@code input}. * - * @param data type for {@code output} output * @param input A complex tensor. * @param data type for {@code IFFT3D} output and operands * @return a new instance of Ifft3d @@ -238,7 +231,6 @@ public Ifft3d ifft3d(Operand input) { *

Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor. The FFT length for each dimension. * @param axes An int32 tensor with a same shape as fft_length. Axes to perform the transform. @@ -264,7 +256,6 @@ public IfftNd ifftNd(Operand input, Operand fftL * than the corresponding dimension of {@code input}, the dimension is cropped. If it is * larger, the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor of shape [1]. The FFT length. * @return a new instance of Irfft, with default output types @@ -287,7 +278,6 @@ public Irfft irfft(Operand input, Operand fft * than the corresponding dimension of {@code input}, the dimension is cropped. If it is * larger, the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor of shape [1]. The FFT length. * @param Treal The value of the Treal attribute @@ -314,7 +304,6 @@ public Irfft irfft(Operand input, * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor of shape [2]. The FFT length for each dimension. * @return a new instance of Irfft2d, with default output types @@ -338,7 +327,6 @@ public Irfft2d irfft2d(Operand input, Operand * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor of shape [2]. The FFT length for each dimension. * @param Treal The value of the Treal attribute @@ -365,7 +353,6 @@ public Irfft2d irfft2d(Operand input, * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor of shape [3]. The FFT length for each dimension. * @return a new instance of Irfft3d, with default output types @@ -389,7 +376,6 @@ public Irfft3d irfft3d(Operand input, Operand * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor of shape [3]. The FFT length for each dimension. * @param Treal The value of the Treal attribute @@ -413,7 +399,6 @@ public Irfft3d irfft3d(Operand input, *

Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor. The FFT length for each dimension. * @param axes An int32 tensor with a same shape as fft_length. Axes to perform the transform. @@ -436,7 +421,6 @@ public IrfftNd irfftNd(Operand input, Operand *

Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor. The FFT length for each dimension. * @param axes An int32 tensor with a same shape as fft_length. Axes to perform the transform. @@ -460,7 +444,6 @@ public IrfftNd irfftNd(Operand input, * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A float32 tensor. * @param fftLength An int32 tensor of shape [1]. The FFT length. * @param Tcomplex The value of the Tcomplex attribute @@ -484,7 +467,6 @@ public Rfft rfft(Operand input, Operand< * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A float32 tensor. * @param fftLength An int32 tensor of shape [2]. The FFT length for each dimension. * @param Tcomplex The value of the Tcomplex attribute @@ -508,7 +490,6 @@ public Rfft2d rfft2d(Operand input, * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. * - * @param data type for {@code output} output * @param input A float32 tensor. * @param fftLength An int32 tensor of shape [3]. The FFT length for each dimension. * @param Tcomplex The value of the Tcomplex attribute @@ -532,7 +513,6 @@ public Rfft3d rfft3d(Operand input, *

Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. * - * @param data type for {@code output} output * @param input A complex tensor. * @param fftLength An int32 tensor. The FFT length for each dimension. * @param axes An int32 tensor with a same shape as fft_length. Axes to perform the transform. diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java index 363421a5125..6660a42449f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SparseOps.java @@ -77,7 +77,7 @@ /** * An API for building {@code sparse} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class SparseOps { private final Scope scope; @@ -155,7 +155,6 @@ public AddSparseToTensorsMap addSparseToTensorsMap(Operand sparseIndices * Performs sparse-output bin counting for a tf.tensor input. * Counts the number of times each value occurs in the input. * - * @param data type for {@code output_values} output * @param values Tensor containing data to count. * @param weights A Tensor of the same shape as indices containing per-index weight values. May * also be the empty tensor if no weights are used. @@ -179,7 +178,6 @@ public DenseCountSparseOutput denseCountSparseOutput( * dimension contains the result of {@code set_operation} applied to the corresponding * {@code [0...n-1]} dimension of {@code set}. * - * @param data type for {@code result_values} output * @param set1 {@code Tensor} with rank {@code n}. 1st {@code n-1} dimensions must be the same as {@code set2}. * Dimension {@code n} contains values in a set, duplicates are allowed but ignored. * @param set2 {@code Tensor} with rank {@code n}. 1st {@code n-1} dimensions must be the same as {@code set1}. @@ -209,7 +207,6 @@ public DenseToDenseSetOperation denseToDenseSetOperation(Op * dimension contains the result of {@code set_operation} applied to the corresponding * {@code [0...n-1]} dimension of {@code set}. * - * @param data type for {@code result_values} output * @param set1 {@code Tensor} with rank {@code n}. 1st {@code n-1} dimensions must be the same as {@code set2}. * Dimension {@code n} contains values in a set, duplicates are allowed but ignored. * @param set2Indices 2D {@code Tensor}, indices of a {@code SparseTensor}. Must be in row-major @@ -272,7 +269,6 @@ public DenseToSparseSetOperation denseToSparseSetOperation( * shape = [2 50] * * - * @param data type for {@code sparse_values} output * @param serializedSparse The serialized {@code SparseTensor} objects. The last dimension * must have 3 columns. * @param dtype The {@code dtype} of the serialized {@code SparseTensor} objects. @@ -317,7 +313,6 @@ public SparseAccumulatorApplyGradient sparseAccumulatorApplyGradient(Operand data type for {@code values} output * @param handle The handle to a SparseConditionalAccumulator. * @param numRequired Number of gradients required before we return an aggregate. * @param dtype The data type of accumulated gradients. Needs to correspond to the type @@ -344,7 +339,6 @@ public SparseAccumulatorTakeGradient sparseAccumulatorTakeG * only for a positive value. *

In the following shapes, {@code nnz} is the count after taking {@code thresh} into account. * - * @param data type for {@code sum_values} output * @param aIndices 2-D. The {@code indices} of the first {@code SparseTensor}, size {@code [nnz, ndims]} Matrix. * @param aValues 1-D. The {@code values} of the first {@code SparseTensor}, size {@code [nnz]} Vector. * @param aShape 1-D. The {@code shape} of the first {@code SparseTensor}, size {@code [ndims]} Vector. @@ -369,7 +363,6 @@ public SparseAdd sparseAdd(Operand aIndices, Operan * non-empty values of the sum, and outputs the gradients w.r.t. the non-empty * values of A and B. * - * @param data type for {@code a_val_grad} output * @param backpropValGrad 1-D with shape {@code [nnz(sum)]}. The gradient with respect to * the non-empty values of the sum. * @param aIndices 2-D. The {@code indices} of the {@code SparseTensor} A, size {@code [nnz(A), ndims]}. @@ -393,7 +386,6 @@ public SparseAddGrad sparseAddGrad(Operand backpropValGr * {@code i}. *

Values in {@code arr} outside of the range [0, size) are ignored. * - * @param data type for {@code output} output * @param indices 2D int64 {@code Tensor}. * @param values 1D int {@code Tensor}. * @param denseShape 1D int64 {@code Tensor}. @@ -452,7 +444,6 @@ public SparseBincount sparseBincount( * [b c ] [ ] [b c ] * * - * @param data type for {@code output_values} output * @param indices 2-D. Indices of each input {@code SparseTensor}. * @param values 1-D. Non-empty values of each {@code SparseTensor}. * @param shapes 1-D. Shapes of each {@code SparseTensor}. @@ -490,7 +481,6 @@ public SparseConditionalAccumulator sparseConditionalAccumulat * Performs sparse-output bin counting for a sparse tensor input. * Counts the number of times each value occurs in the input. * - * @param data type for {@code output_values} output * @param indices Tensor containing the indices of the sparse tensor to count. * @param values Tensor containing values of the sparse tensor to count. * @param denseShape Tensor containing the dense shape of the sparse tensor to count. @@ -624,7 +614,6 @@ public SparseCrossHashed sparseCrossHashed(Iterable> indices, * indices and shape, but possibly with different non-zero values. The output of * this Op is the resultant non-zero values. * - * @param data type for {@code output} output * @param spIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param spValues 1-D. {@code N} non-empty values corresponding to {@code sp_indices}. @@ -643,7 +632,6 @@ public SparseDenseCwiseAdd sparseDenseCwiseAdd(OperandLimitation: this Op only broadcasts the dense side to the sparse side, but not * the other direction. * - * @param data type for {@code output} output * @param spIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param spValues 1-D. {@code N} non-empty values corresponding to {@code sp_indices}. @@ -665,7 +653,6 @@ public SparseDenseCwiseDiv sparseDenseCwiseDiv(OperandLimitation: this Op only broadcasts the dense side to the sparse side, but not * the other direction. * - * @param data type for {@code output} output * @param spIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param spValues 1-D. {@code N} non-empty values corresponding to {@code sp_indices}. @@ -716,7 +703,6 @@ public SparseDenseCwiseMul sparseDenseCwiseMul(Operand * - * @param data type for {@code output_values} output * @param indices 2-D. the indices of the sparse tensor. * @param values 1-D. the values of the sparse tensor. * @param denseShape 1-D. the shape of the sparse tensor. @@ -741,7 +727,6 @@ public SparseFillEmptyRows sparseFillEmptyRows(Operand data type for {@code d_values} output * @param reverseIndexMap 1-D. The reverse index map from SparseFillEmptyRows. * @param gradValues 1-D. The gradients from backprop. * @param data type for {@code SparseFillEmptyRowsGrad} output and operands @@ -786,7 +771,6 @@ public SparseMatMul sparseMatMul(Operand a, Operand data type for {@code output} output * @param inputIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param inputValues 1-D. {@code N} non-empty values corresponding to {@code input_indices}. @@ -815,7 +799,6 @@ public SparseReduceMax sparseReduceMax(Operand in * with a single element is returned. Additionally, the axes can be negative, * which are interpreted according to the indexing rules in Python. * - * @param data type for {@code output_values} output * @param inputIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param inputValues 1-D. {@code N} non-empty values corresponding to {@code input_indices}. @@ -844,7 +827,6 @@ public SparseReduceMaxSparse sparseReduceMaxSparse( * with a single element is returned. Additionally, the axes can be negative, * which are interpreted according to the indexing rules in Python. * - * @param data type for {@code output} output * @param inputIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param inputValues 1-D. {@code N} non-empty values corresponding to {@code input_indices}. @@ -873,7 +855,6 @@ public SparseReduceSum sparseReduceSum(Operand inpu * with a single element is returned. Additionally, the axes can be negative, * which are interpreted according to the indexing rules in Python. * - * @param data type for {@code output_values} output * @param inputIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param inputValues 1-D. {@code N} non-empty values corresponding to {@code input_indices}. @@ -898,7 +879,6 @@ public SparseReduceSumSparse sparseReduceSumSparse( *

If the tensor has rank {@code R} and {@code N} non-empty values, {@code input_indices} has * shape {@code [N, R]}, input_values has length {@code N}, and input_shape has length {@code R}. * - * @param data type for {@code output_values} output * @param inputIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, possibly not in canonical ordering. * @param inputValues 1-D. {@code N} non-empty values corresponding to {@code input_indices}. @@ -943,7 +923,6 @@ public SparseReshape sparseReshape(Operand inputIndices, Operand *

Like {@code SegmentMean}, but {@code segment_ids} can have rank less than {@code data}'s first * dimension, selecting a subset of dimension 0, specified by {@code indices}. * - * @param data type for {@code output} output * @param data The data value * @param indices A 1-D tensor. Has same rank as {@code segment_ids}. * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated. @@ -963,8 +942,6 @@ public SparseSegmentMean sparseSegmentMean(Operand dat * value is the number of unique indexes in "indices". Also returns vector * "sorted_unique_indices" containing the corresponding indexes from "indices". * - * @param data type for {@code output} output - * @param data type for {@code sorted_unique_indices} output * @param grad gradient propagated to the SparseSegmentMean op. * @param indices indices passed to the corresponding SparseSegmentMean op. * @param segmentIds segment_ids passed to the corresponding SparseSegmentMean op. @@ -987,7 +964,6 @@ public SparseSegmentMeanGrad sparse * the section on segmentation * for an explanation of segments. * - * @param data type for {@code output} output * @param data The data value * @param indices A 1-D tensor. Has same rank as {@code segment_ids}. * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated. @@ -1007,7 +983,6 @@ public SparseSegmentMeanWithNumSegments sparseSegmentMean * N is the size of the segment being reduced. *

See {@code tf.sparse.segment_sum} for usage examples. * - * @param data type for {@code output} output * @param data The data value * @param indices A 1-D tensor. Has same rank as {@code segment_ids}. * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated. @@ -1027,8 +1002,6 @@ public SparseSegmentSqrtN sparseSegmentSqrtN(Operand d * value is the number of unique indexes in "indices". Also returns vector * "sorted_unique_indices" containing the corresponding indexes from "indices". * - * @param data type for {@code output} output - * @param data type for {@code sorted_unique_indices} output * @param grad gradient propagated to the SparseSegmentSqrtN op. * @param indices indices passed to the corresponding SparseSegmentSqrtN op. * @param segmentIds segment_ids passed to the corresponding SparseSegmentSqrtN op. @@ -1052,7 +1025,6 @@ public SparseSegmentSqrtNGrad spars * the section on segmentation * for an explanation of segments. * - * @param data type for {@code output} output * @param data The data value * @param indices A 1-D tensor. Has same rank as {@code segment_ids}. * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated. @@ -1097,7 +1069,6 @@ public SparseSegmentSqrtNWithNumSegments sparseSegmentSqr * tf.segment_sum(c, tf.constant([0, 0, 1])) * * - * @param data type for {@code output} output * @param data The data value * @param indices A 1-D tensor. Has same rank as {@code segment_ids}. * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated. @@ -1117,8 +1088,6 @@ public SparseSegmentSum sparseSegmentSum(Operand data, * value is the number of unique indexes in "indices". Also returns vector * "sorted_unique_indices" containing the corresponding indexes from "indices". * - * @param data type for {@code output} output - * @param data type for {@code sorted_unique_indices} output * @param grad gradient propagated to the SparseSegmentSum op. * @param indices indices passed to the corresponding SparseSegmentSum op. * @param segmentIds segment_ids passed to the corresponding SparseSegmentSum op. @@ -1160,7 +1129,6 @@ public SparseSegmentSumGrad sparseS * # [ 0 0 0 0]] * * - * @param data type for {@code output} output * @param data The data value * @param indices A 1-D tensor. Has same rank as {@code segment_ids}. * @param segmentIds A 1-D tensor. Values should be sorted and can be repeated. @@ -1194,7 +1162,6 @@ public SparseSegmentSumWithNumSegments sparseSegmentSumWi * [ ] * * - * @param data type for {@code output_values} output * @param indices 2-D tensor represents the indices of the sparse tensor. * @param values 1-D tensor represents the values of the sparse tensor. * @param shape 1-D. tensor represents the shape of the sparse tensor. @@ -1216,7 +1183,6 @@ public SparseSlice sparseSlice(Operand indices, Ope * the sliced {@code SparseTensor}, and outputs the gradients w.r.t. * the non-empty values of input {@code SparseTensor}. * - * @param data type for {@code val_grad} output * @param backpropValGrad 1-D. The gradient with respect to * the non-empty values of the sliced {@code SparseTensor}. * @param inputIndices 2-D. The {@code indices} of the input {@code SparseTensor}. @@ -1245,7 +1211,6 @@ public SparseSliceGrad sparseSliceGrad(Operand backpropV *

Hence, the {@code SparseTensor} result has exactly the same non-zero indices and * shape. * - * @param data type for {@code output} output * @param spIndices 2-D. {@code NNZ x R} matrix with the indices of non-empty values in a * SparseTensor, in canonical ordering. * @param spValues 1-D. {@code NNZ} non-empty values corresponding to {@code sp_indices}. @@ -1262,7 +1227,6 @@ public SparseSoftmax sparseSoftmax(Operand spIndi * Returns the element-wise max of two SparseTensors. * Assumes the two SparseTensors have the same shape, i.e., no broadcasting. * - * @param data type for {@code output_values} output * @param aIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, in the canonical lexicographic ordering. * @param aValues 1-D. {@code N} non-empty values corresponding to {@code a_indices}. @@ -1283,7 +1247,6 @@ public SparseSparseMaximum sparseSparseMaximum(Operand data type for {@code output_values} output * @param aIndices 2-D. {@code N x R} matrix with the indices of non-empty values in a * SparseTensor, in the canonical lexicographic ordering. * @param aValues 1-D. {@code N} non-empty values corresponding to {@code a_indices}. @@ -1321,7 +1284,6 @@ public SparseSparseMinimum sparseSparseMinimum(Operand * - * @param data type for {@code output_values} output * @param splitDim 0-D. The dimension along which to split. Must be in the range * {@code [0, rank(shape))}. * @param indices 2-D tensor represents the indices of the sparse tensor. @@ -1342,7 +1304,6 @@ public SparseSplit sparseSplit(Operand splitDim, * Adds up a {@code SparseTensor} and a dense {@code Tensor}, producing a dense {@code Tensor}. * This Op does not require {@code a_indices} be sorted in standard lexicographic order. * - * @param data type for {@code output} output * @param aIndices 2-D. The {@code indices} of the {@code SparseTensor}, with shape {@code [nnz, ndims]}. * @param aValues 1-D. The {@code values} of the {@code SparseTensor}, with shape {@code [nnz]}. * @param aShape 1-D. The {@code shape} of the {@code SparseTensor}, with shape {@code [ndims]}. @@ -1367,7 +1328,6 @@ public SparseTensorDenseAdd sparseTensor * A should be sorted in order of increasing dimension 1 (i.e., "column major" * order instead of "row major" order). * - * @param data type for {@code product} output * @param aIndices 2-D. The {@code indices} of the {@code SparseTensor}, size {@code [nnz, 2]} Matrix. * @param aValues 1-D. The {@code values} of the {@code SparseTensor}, size {@code [nnz]} Vector. * @param aShape 1-D. The {@code shape} of the {@code SparseTensor}, size {@code [2]} Vector. @@ -1401,7 +1361,6 @@ public SparseTensorDenseMatMul sparseTensorDenseMatMul( * contain any repeats. If {@code validate_indices} is true, these properties * are checked during execution. * - * @param data type for {@code dense} output * @param sparseIndices 0-D, 1-D, or 2-D. {@code sparse_indices[i]} contains the complete * index where {@code sparse_values[i]} will be placed. * @param outputShape 1-D. Shape of the dense output tensor. @@ -1441,7 +1400,6 @@ public SparseToDense sparseToDense( * dimension contains the result of {@code set_operation} applied to the corresponding * {@code [0...n-1]} dimension of {@code set}. * - * @param data type for {@code result_values} output * @param set1Indices 2D {@code Tensor}, indices of a {@code SparseTensor}. Must be in row-major * order. * @param set1Values 1D {@code Tensor}, values of a {@code SparseTensor}. Must be in row-major @@ -1511,7 +1469,6 @@ public SparseToSparseSetOperation sparseToSparseSetOperatio * shape = [2 50] * * - * @param data type for {@code sparse_values} output * @param sparseHandles 1-D, The {@code N} serialized {@code SparseTensor} objects. * Shape: {@code [N]}. * @param dtype The {@code dtype} of the {@code SparseTensor} objects stored in the diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java index 61b4655473e..56a82c2dbf6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/StringsOps.java @@ -52,7 +52,7 @@ /** * An API for building {@code strings} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class StringsOps { private final Scope scope; @@ -260,7 +260,6 @@ public StringLength stringLength(Operand input, StringLength.Options... * strings and outputs a ragged tensor with 1 ragged dimension containing ngrams * of that string, joined along the innermost axis. * - * @param data type for {@code ngrams_splits} output * @param data The values tensor of the ragged string tensor to make ngrams out of. Must be a * 1D string tensor. * @param dataSplits The splits tensor of the ragged string tensor to make ngrams out of. @@ -510,7 +509,6 @@ public ToHashBucketStrong toHashBucketStrong(Operand input, Long numBuc * * * - * @param data type for {@code output} output * @param stringTensor The stringTensor value * @return a new instance of ToNumber, with default output types */ @@ -533,7 +531,6 @@ public ToNumber toNumber(Operand stringTensor) { * * * - * @param data type for {@code output} output * @param stringTensor The stringTensor value * @param outType The numeric type to interpret each string in {@code string_tensor} as. * @param data type for {@code StringToNumber} output and operands @@ -559,7 +556,6 @@ public ToNumber toNumber(Operand stringTensor, C * string (in row-major order). * * - * @param data type for {@code row_splits} output * @param input The text to be decoded. Can have any shape. Note that the output is flattened * to a vector of char values. * @param inputEncoding Text encoding of the input strings. This is any of the encodings supported @@ -588,7 +584,6 @@ public UnicodeDecode unicodeDecode(Operand input, String inputE * string (in row-major order). * * - * @param data type for {@code row_splits} output * @param input The text to be decoded. Can have any shape. Note that the output is flattened * to a vector of char values. * @param inputEncoding Text encoding of the input strings. This is any of the encodings supported @@ -623,7 +618,6 @@ public UnicodeDecode unicodeDecode(Operand input * string (in row-major order). * * - * @param data type for {@code row_splits} output * @param input The text to be decoded. Can have any shape. Note that the output is flattened * to a vector of char values. * @param inputEncoding Text encoding of the input strings. This is any of the encodings supported @@ -656,7 +650,6 @@ public UnicodeDecodeWithOffsets unicodeDecodeWithOffsets(Operand * * - * @param data type for {@code row_splits} output * @param input The text to be decoded. Can have any shape. Note that the output is flattened * to a vector of char values. * @param inputEncoding Text encoding of the input strings. This is any of the encodings supported diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SummaryOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SummaryOps.java index 0cb2c188fe1..d7690d11d71 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SummaryOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/SummaryOps.java @@ -49,7 +49,7 @@ /** * An API for building {@code summary} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class SummaryOps { private final Scope scope; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TpuOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TpuOps.java index 9fac44a94f3..72356814850 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TpuOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TpuOps.java @@ -130,7 +130,7 @@ /** * An API for building {@code tpu} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class TpuOps { private final Scope scope; @@ -158,7 +158,6 @@ public final class TpuOps { *

replica 0's output: {@code [[A], [C]]} * replica 1's output: {@code [[B], [D]]} * - * @param data type for {@code output} output * @param input The local input to the sum. * @param groupAssignment An int32 tensor with shape * [num_groups, num_replicas_per_group]. {@code group_assignment[i]} represents the @@ -365,7 +364,6 @@ public ConvertToCooTensor convertToCooTensor(Operand indicesOrRowSplits, * and {@code B, D, F, H} as group 1. Thus we get the outputs: * {@code [A+C+E+G, B+D+F+H, A+C+E+G, B+D+F+H, A+C+E+G, B+D+F+H, A+C+E+G, B+D+F+H]}. * - * @param data type for {@code output} output * @param input The local input to the sum. * @param groupAssignment An int32 tensor with shape * [num_groups, num_replicas_per_group]. {@code group_assignment[i]} represents the @@ -801,7 +799,6 @@ public GlobalIterId globalIterId() { /** * A placeholder op for a value that will be fed into the computation. * - * @param data type for {@code output} output * @param dtype The type of elements in the tensor. * @param shape The shape of the tensor. * @param data type for {@code InfeedDequeue} output and operands @@ -1252,7 +1249,6 @@ public OrdinalSelector ordinalSelector() { * Retrieves a single tensor from the computation outfeed. * This operation will block indefinitely until data is available. * - * @param data type for {@code output} output * @param dtype The type of elements in the tensor. * @param shape The shape of the tensor. * @param options carries optional attribute values @@ -1302,7 +1298,6 @@ public OutfeedDequeueTupleV2 outfeedDequeueTupleV2(Operand deviceOrdinal * tensor allowing dynamic outfeed. * This operation will block indefinitely until data is available. * - * @param data type for {@code output} output * @param deviceOrdinal An int scalar tensor, representing the TPU device to use. This should be -1 when * the Op is running on a TPU device, and >= 0 when the Op is running on the CPU * device. @@ -1355,7 +1350,6 @@ public PartitionedCall partitionedCall(Iterable> args, Operand data type for {@code output} output * @param inputs A list of partitioned inputs which must have the same shape. * @param partitionDims A list of integers describing how each dimension is partitioned. Emptiness * indicates the inputs are replicated. @@ -1372,7 +1366,6 @@ public PartitionedInput partitionedInput(Iterable data type for {@code output} output * @param inputs A tensor which represents the full shape of partitioned tensors. * @param numSplits The value of the numSplits attribute * @param partitionDims A list of integers describing how each dimension is partitioned. Emptiness @@ -1454,7 +1447,6 @@ public ReplicateMetadata replicateMetadata(Long numReplicas, * *

The above computation has a replicated input of two replicas. * - * @param data type for {@code output} output * @param inputs The inputs value * @param options carries optional attribute values * @param data type for {@code TPUReplicatedInput} output and operands @@ -1476,7 +1468,6 @@ public ReplicatedInput replicatedInput(Iterable> * *

The above computation has a replicated output of two replicas. * - * @param data type for {@code outputs} output * @param input The input value * @param numReplicas The value of the numReplicas attribute * @param data type for {@code TPUReplicatedOutput} output and operands @@ -1784,8 +1775,6 @@ public ShutdownTPUSystem shutdownTPUSystem() { * values. This op is to split these values into two groups for two types, and * construct each group as one tensor to return. * - * @param data type for {@code integer_tensor} output - * @param data type for {@code float_tensor} output * @param input An XLA tuple including integer and float elements as deduplication data tuple. * @param integerType integer_tensor type. Allowed types: int32, int64, uint32, uint64. * @param floatType float_tensor type. Allowed types: half, bfloat16, float. @@ -1913,7 +1902,6 @@ public TPUReplicateMetadata tPUReplicateMetadata(Long numReplicas, * *

The above computation has a replicated input of two replicas. * - * @param data type for {@code output} output * @deprecated use {@link org.tensorflow.op.tpu.ReplicatedInput} instead * @param inputs The inputs value * @param options carries optional attribute values @@ -1937,7 +1925,6 @@ public TPUReplicatedInput tPUReplicatedInput(Iterable *

The above computation has a replicated output of two replicas. * - * @param data type for {@code outputs} output * @deprecated use {@link org.tensorflow.op.tpu.ReplicatedOutput} instead * @param input The input value * @param numReplicas The value of the numReplicas attribute diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java index fd4a9bbd02b..3ee5b8de813 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/TrainOps.java @@ -108,7 +108,7 @@ /** * An API for building {@code train} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class TrainOps { private final Scope scope; @@ -166,7 +166,6 @@ public AccumulatorSetGlobalStep accumulatorSetGlobalStep(Operand handle * the accumulated gradients. Also automatically increments the recorded * global_step in the accumulator by 1, and resets the aggregate to 0. * - * @param data type for {@code average} output * @param handle The handle to an accumulator. * @param numRequired Number of gradients required before we return an aggregate. * @param dtype The data type of accumulated gradients. Needs to correspond to the type @@ -185,7 +184,6 @@ public AccumulatorTakeGradient accumulatorTakeGradient( * v_t <- max(beta2 * v_{t-1}, abs(g)) * variable <- variable - learning_rate / (1 - beta1^t) * m_t / (v_t + epsilon) * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param m Should be from a Variable(). * @param v Should be from a Variable(). @@ -212,7 +210,6 @@ public ApplyAdaMax applyAdaMax(Operand var, Operand m * update_accum = rho() * update_accum + (1 - rho()) * update.square(); * var -= update; * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param accumUpdate Should be from a Variable(). @@ -235,7 +232,6 @@ public ApplyAdadelta applyAdadelta(Operand var, Operand< * accum += grad * grad * var -= lr * grad * (1 / sqrt(accum)) * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param lr Scaling factor. Must be a scalar. @@ -252,7 +248,6 @@ public ApplyAdagrad applyAdagrad(Operand var, Operand /** * Update '*var' according to the proximal adagrad scheme. * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param gradientAccumulator Should be from a Variable(). * @param gradientSquaredAccumulator Should be from a Variable(). @@ -277,7 +272,6 @@ public ApplyAdagradDa applyAdagradDa(Operand var, * accum += grad * grad * var -= lr * grad * (1 / sqrt(accum)) * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param lr Scaling factor. Must be a scalar. @@ -299,7 +293,6 @@ public ApplyAdagradV2 applyAdagradV2(Operand var, Operan * $$v_t := \beta_2 \cdot v_{t-1} + (1 - \beta_2) \cdot g^2$$ * $$\text{var} := \begin{cases} \text{var} - (m_t \beta_1 + g \cdot (1 - \beta_1))\cdot\text{lr}_t/(\sqrt{v_t} + \epsilon), &\text{if use_nesterov}\\ \text{var} - m_t \cdot \text{lr}_t /(\sqrt{v_t} + \epsilon), &\text{otherwise} \end{cases}$$ * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param m Should be from a Variable(). * @param v Should be from a Variable(). @@ -326,7 +319,6 @@ public ApplyAdam applyAdam(Operand var, Operand m, Op * update <- (alpha + sign_decay * sign(g) *sign(m)) * g * variable <- variable - lr_t * update * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param m Should be from a Variable(). * @param lr Scaling factor. Must be a scalar. @@ -361,7 +353,6 @@ public ApplyAddSign applyAddSign(Operand var, Operand * mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms - mg * mg + epsilon) * var <- var - mom * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param mg Should be from a Variable(). * @param ms Should be from a Variable(). @@ -392,7 +383,6 @@ public ApplyCenteredRmsProp applyCenteredRmsProp(Operand * var = (sign(linear) * l1 - linear) / quadratic if |linear| > l1 else 0.0 * accum = accum_new * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param linear Should be from a Variable(). @@ -415,7 +405,6 @@ public ApplyFtrl applyFtrl(Operand var, Operand accum /** * Update '*var' by subtracting 'alpha' * 'delta' from it. * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param alpha Scaling factor. Must be a scalar. * @param delta The change. @@ -434,7 +423,6 @@ public ApplyGradientDescent applyGradientDescent(Operand *

accum = accum * momentum + grad * var -= lr * accum * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param lr Scaling factor. Must be a scalar. @@ -455,7 +443,6 @@ public ApplyMomentum applyMomentum(Operand var, Operand< * update <- exp(logbase * sign_decay * sign(g) * sign(m_t)) * g * variable <- variable - lr_t * update * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param m Should be from a Variable(). * @param lr Scaling factor. Must be a scalar. @@ -479,7 +466,6 @@ public ApplyPowerSign applyPowerSign(Operand var, Operan * prox_v = var - lr * grad * (1 / sqrt(accum)) * var = sign(prox_v)/(1+lrl2) * max{|prox_v|-lrl1,0} * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param lr Scaling factor. Must be a scalar. @@ -501,7 +487,6 @@ public ApplyProximalAdagrad applyProximalAdagrad(Operand * prox_v = var - alpha * delta * var = sign(prox_v)/(1+alphal2) * max{|prox_v|-alphal1,0} * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param alpha Scaling factor. Must be a scalar. * @param l1 L1 regularization. Must be a scalar. @@ -528,7 +513,6 @@ public ApplyProximalGradientDescent applyProximalGradientDe * mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon) * var <- var - mom * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param ms Should be from a Variable(). * @param mom Should be from a Variable(). @@ -570,7 +554,6 @@ public ApplyRmsProp applyRmsProp(Operand var, Operand * about broadcasting * here . * - * @param data type for {@code output} output * @param x 2-D or higher with shape {@code [..., r_x, c_x]}. * @param y 2-D or higher with shape {@code [..., r_y, c_y]}. * @param Tout If not spcified, Tout is the same type to input type. @@ -717,7 +700,6 @@ public NegTrain negTrain(Operand wIn, Operand wOut, Operand< * op exists to prevent subtle bugs from silently returning unimplemented * gradients in some corner cases. * - * @param data type for {@code output} output * @param input any tensor. * @param options carries optional attribute values * @param data type for {@code PreventGradient} output and operands @@ -776,7 +758,6 @@ public ResourceAccumulatorSetGlobalStep resourceAccumulatorSetGlobalStep( * the accumulated gradients. Also automatically increments the recorded * global_step in the accumulator by 1, and resets the aggregate to 0. * - * @param data type for {@code average} output * @param handle The handle to an accumulator. * @param numRequired Number of gradients required before we return an aggregate. * @param dtype The data type of accumulated gradients. Needs to correspond to the type @@ -1535,7 +1516,6 @@ public Restore restore(Operand prefix, Operand tensorNames, *

The {@code shape_and_slice} input has the same format as the * elements of the {@code shapes_and_slices} input of the {@code SaveSlices} op. * - * @param data type for {@code tensor} output * @param filePattern Must have a single element. The pattern of the files from * which we read the tensor. * @param tensorName Must have a single element. The name of the tensor to be @@ -1687,7 +1667,6 @@ public SdcaShrinkL1 sdcaShrinkL1(Iterable> weights, Float l1, /** * var: Should be from a Variable(). * - * @param data type for {@code out} output * @param var The var value * @param accum Should be from a Variable(). * @param accumUpdate : Should be from a Variable(). @@ -1712,7 +1691,6 @@ public SparseApplyAdadelta sparseApplyAdadelta(Operand v * $$accum += grad * grad$$ * $$var -= lr * grad * (1 / sqrt(accum))$$ * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param lr Learning rate. Must be a scalar. @@ -1732,7 +1710,6 @@ public SparseApplyAdagrad sparseApplyAdagrad(Operand var /** * Update entries in '*var' and '*accum' according to the proximal adagrad scheme. * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param gradientAccumulator Should be from a Variable(). * @param gradientSquaredAccumulator Should be from a Variable(). @@ -1769,7 +1746,6 @@ public SparseApplyAdagradDa sparseApplyAdagradDa(Operand * $$mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)$$ * $$var <- var - mom$$ * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param mg Should be from a Variable(). * @param ms Should be from a Variable(). @@ -1802,7 +1778,6 @@ public SparseApplyCenteredRmsProp sparseApplyCenteredRmsPro * var = (sign(linear) * l1 - linear) / quadratic if |linear| > l1 else 0.0 * accum = accum_new * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param linear Should be from a Variable(). @@ -1831,7 +1806,6 @@ public SparseApplyFtrl sparseApplyFtrl(Operand var, Oper *

$$accum = accum * momentum + grad$$ * $$var -= lr * accum$$ * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param lr Learning rate. Must be a scalar. @@ -1856,7 +1830,6 @@ public SparseApplyMomentum sparseApplyMomentum(Operand v * $$prox_v -= lr * grad * (1 / sqrt(accum))$$ * $$var = sign(prox_v)/(1+lrl2) * max{|prox_v|-lrl1,0}$$ * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param accum Should be from a Variable(). * @param lr Learning rate. Must be a scalar. @@ -1880,7 +1853,6 @@ public SparseApplyProximalAdagrad sparseApplyProximalAdagra * $$prox_v = var - alpha * grad$$ * $$var = sign(prox_v)/(1+alphal2) * max{|prox_v|-alphal1,0}$$ * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param alpha Scaling factor. Must be a scalar. * @param l1 L1 regularization. Must be a scalar. @@ -1908,7 +1880,6 @@ public SparseApplyProximalGradientDescent sparseApplyProxim * $$mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)$$ * $$var <- var - mom$$ * - * @param data type for {@code out} output * @param var Should be from a Variable(). * @param ms Should be from a Variable(). * @param mom Should be from a Variable(). @@ -1960,7 +1931,6 @@ public SymbolicGradient symbolicGradient(Iterable> input, * along each dimension, {@code train.TileGrad} takes in {@code multiples} and aggregates * each repeated tile of {@code input} into {@code output}. * - * @param data type for {@code output} output * @param input The input value * @param multiples The multiples value * @param data type for {@code TileGrad} output and operands diff --git a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java index c1a5a97d146..3d303810698 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/annotations/org/tensorflow/op/XlaOps.java @@ -50,7 +50,7 @@ /** * An API for building {@code xla} operations as {@link Op Op}s * - * @see {@link Ops} + * @see Ops */ public final class XlaOps { private final Scope scope; @@ -149,7 +149,6 @@ public AssignVariableConcatND assignVariableConcatND(Operand re * [8, 9, 10]] * * - * @param data type for {@code output} output * @param inputs Input tensor slices in row-major order to merge across all dimensions. All * inputs must have the same shape. * } @@ -199,7 +198,6 @@ public ConcatND concatND(Iterable> inputs, List< * [0, 0]] * * - * @param data type for {@code outputs} output * @param resource Resource variable of input tensor to split across all dimensions. * } * out_arg { @@ -252,7 +250,6 @@ public ReadVariableSplitND readVariableSplitND( * [0, 0]] * * - * @param data type for {@code outputs} output * @param input Input tensor to split across all dimensions. * } * out_arg { @@ -298,7 +295,6 @@ public XlaHostCompute xlaHostCompute(Iterable> inputs, * shape: shape for output. * key: A unique identifier for this region used to match up host transfers. * - * @param data type for {@code output} output * @param Toutput The value of the Toutput attribute * @param shape The value of the shape attribute * @param key The value of the key attribute diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java index 34789dce80c..7fea36a03b3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseAnd.java @@ -52,8 +52,6 @@ * res = bitwise_ops.bitwise_and(lhs, rhs) * tf.assert_equal(tf.cast(res, tf.float32), exp) # TRUE * - * - * @param data type for {@code z} output */ @OpMetadata( opType = BitwiseAnd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java index afa384f6e38..1e57451698b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseOr.java @@ -52,8 +52,6 @@ * res = bitwise_ops.bitwise_or(lhs, rhs) * tf.assert_equal(tf.cast(res, tf.float32), exp) # TRUE * - * - * @param data type for {@code z} output */ @OpMetadata( opType = BitwiseOr.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java index dc26dc145aa..52953422482 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/BitwiseXor.java @@ -52,8 +52,6 @@ * res = bitwise_ops.bitwise_xor(lhs, rhs) * tf.assert_equal(tf.cast(res, tf.float32), exp) # TRUE * - * - * @param data type for {@code z} output */ @OpMetadata( opType = BitwiseXor.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java index a2d9a985bae..8dcb5a72de7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/Invert.java @@ -73,8 +73,6 @@ * expected = tf.constant([dtype.max - x for x in inputs], dtype=tf.float32) * tf.assert_equal(tf.cast(inverted, tf.float32), tf.cast(expected, tf.float32)) * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Invert.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java index 5874dc12979..ccf41c473f8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/LeftShift.java @@ -63,8 +63,6 @@ * bitwise_ops.left_shift(lhs, rhs) * # <tf.Tensor: shape=(4,), dtype=int8, numpy=array([ -2, 64, 101, 32], dtype=int8)> * - * - * @param data type for {@code z} output */ @OpMetadata( opType = LeftShift.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java index 22c95c81136..6c1407b9d19 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/bitwise/RightShift.java @@ -65,8 +65,6 @@ * bitwise_ops.right_shift(lhs, rhs) * # <tf.Tensor: shape=(4,), dtype=int8, numpy=array([ -2, 64, 101, 32], dtype=int8)> * - * - * @param data type for {@code z} output */ @OpMetadata( opType = RightShift.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveAllToAll.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveAllToAll.java index 99ccff79289..9c513486b9b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveAllToAll.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveAllToAll.java @@ -37,8 +37,6 @@ /** * Mutually exchanges multiple tensors of identical type and shape. - * - * @param data type for {@code data} output */ @OpMetadata( opType = CollectiveAllToAll.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastRecv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastRecv.java index 332b5dcf9ab..a66995e4d4e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastRecv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastRecv.java @@ -38,8 +38,6 @@ /** * Receives a tensor value broadcast from another device. - * - * @param data type for {@code data} output */ @OpMetadata( opType = CollectiveBcastRecv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastSend.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastSend.java index ee495b56951..df7a315413f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastSend.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveBcastSend.java @@ -36,8 +36,6 @@ /** * Broadcasts a tensor value to one or more other devices. - * - * @param data type for {@code data} output */ @OpMetadata( opType = CollectiveBcastSend.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveGather.java index d3997e8743f..57a2b134ff6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveGather.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveGather.java @@ -41,8 +41,6 @@ * {@code is_stateless} means each op does not need control dependencies to other * collective ops. In this case, keys that are unique at runtime * (e.g. {@code instance_key}) should be used to distinguish collective groups. - * - * @param data type for {@code data} output */ @OpMetadata( opType = CollectiveGather.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectivePermute.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectivePermute.java index 9fd029facf3..380a949a664 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectivePermute.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectivePermute.java @@ -40,8 +40,6 @@ *

For example, suppose there are 4 TPU instances: {@code [A, B, C, D]}. Passing * source_target_pairs={@code [[0,1],[1,2],[2,3],[3,0]]} gets the outputs: * {@code [D, A, B, C]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CollectivePermute.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduce.java index 7eab3bb0f17..8f6c26778e1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduce.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduce.java @@ -37,8 +37,6 @@ /** * Mutually reduces multiple tensors of identical type and shape. - * - * @param data type for {@code data} output */ @OpMetadata( opType = CollectiveReduce.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduceScatter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduceScatter.java index 5ab06edf273..8b89dbaf183 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduceScatter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/collective/CollectiveReduceScatter.java @@ -41,8 +41,6 @@ * {@code is_stateless} means each op does not need control dependencies to other * collective ops. In this case, keys that are unique at runtime * (e.g. {@code instance_key}) should be used to distinguish collective groups. - * - * @param data type for {@code data} output */ @OpMetadata( opType = CollectiveReduceScatter.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ApproxTopK.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ApproxTopK.java index ad97098d481..48f4f94315b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ApproxTopK.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ApproxTopK.java @@ -38,8 +38,6 @@ * Returns min/max k values and their indices of the input operand in an approximate manner. * See https://arxiv.org/abs/2206.14286 for the algorithm details. * This op is only optimized on TPU currently. - * - * @param data type for {@code values} output */ @OpMetadata( opType = ApproxTopK.OP_NAME, @@ -291,17 +289,17 @@ public static class Inputs extends RawOpInputs> /** * When set to a positive value, it overrides the size determined by - * `input[reduction_dim]` for evaluating the recall. This option is useful when - * the given `input` is only a subset of the overall computation in SPMD or + * {@code input[reduction_dim]} for evaluating the recall. This option is useful when + * the given {@code input} is only a subset of the overall computation in SPMD or * distributed pipelines, where the true input size cannot be deferred by the - * `input` shape. + * {@code input} shape. */ public final long reductionInputSizeOverride; /** * When true, aggregates approximate results to top-k. When false, returns the * approximate results. The number of the approximate results is implementation - * defined and is greater equals to the specified `k`. + * defined and is greater equals to the specified {@code k}. */ public final boolean aggregateToTopk; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Assign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Assign.java index a8001c6103a..e49f3eafacc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Assign.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Assign.java @@ -37,8 +37,6 @@ * Update 'ref' by assigning 'value' to it. * This operation outputs "ref" after the assignment is done. * This makes it easier to chain operations that need to use the reset value. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = Assign.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAdd.java index 2b6f78046ca..848231d569a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignAdd.java @@ -37,8 +37,6 @@ * Update 'ref' by adding 'value' to it. * This operation outputs "ref" after the update is done. * This makes it easier to chain operations that need to use the reset value. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = AssignAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSub.java index 162fc069e92..cc96d634945 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSub.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/AssignSub.java @@ -37,8 +37,6 @@ * Update 'ref' by subtracting 'value' from it. * This operation outputs "ref" after the update is done. * This makes it easier to chain operations that need to use the reset value. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = AssignSub.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchFunction.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchFunction.java index 6399060fb08..d544fdeca5a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchFunction.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchFunction.java @@ -588,7 +588,7 @@ public static class Inputs extends RawOpInputs { /** * input with a large size (i.e., larger than the largest value of - * `allowed_batch_sizes`) will be splitted into multiple batches with batch size. + * {@code allowed_batch_sizes}) will be splitted into multiple batches with batch size. */ public final boolean enableLargeBatchSplitting; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpace.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpace.java index 889bd521e0d..09fa1d49bcb 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpace.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpace.java @@ -42,8 +42,6 @@ * this op outputs a copy of the input tensor where values from the {@code batch} * dimension are moved in spatial blocks to the {@code height} and {@code width} dimensions, * followed by cropping along the {@code height} and {@code width} dimensions. - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchToSpace.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpaceNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpaceNd.java index c7cf592d517..65a98188342 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpaceNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BatchToSpaceNd.java @@ -42,8 +42,6 @@ * the input. The spatial dimensions of this intermediate result are then * optionally cropped according to {@code crops} to produce the output. This is the * reverse of SpaceToBatch. See below for a precise description. - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchToSpaceNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java index c1bd2421b15..82a2a99d295 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Bitcast.java @@ -96,8 +96,6 @@ * endian orderings will give different results. A copy from input buffer to output * buffer is made on BE machines when types are of different sizes in order to get * the same casting results as on LE machines. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Bitcast.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java index 96cfa009842..165e7e12b9a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastDynamicShape.java @@ -37,8 +37,6 @@ * Return the shape of s0 op s1 with broadcast. * Given {@code s0} and {@code s1}, tensors that represent shapes, compute {@code r0}, the * broadcasted shape. {@code s0}, {@code s1} and {@code r0} are all integer vectors. - * - * @param data type for {@code r0} output */ @OpMetadata( opType = BroadcastDynamicShape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java index fe9cf0e7039..f29d66c8de6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastGradientArgs.java @@ -36,8 +36,6 @@ /** * Return the reduction indices for computing gradients of s0 op s1 with broadcast. * This is typically used by gradient computations for a broadcasting operation. - * - * @param data type for {@code r0} output */ @OpMetadata( opType = BroadcastGradientArgs.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastTo.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastTo.java index d9ada9ae323..f27247cd37a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastTo.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/BroadcastTo.java @@ -72,8 +72,6 @@ * The newly-created tensor takes the full memory of the broadcasted * shape. (In a graph context, {@code broadcast_to} might be fused to * subsequent operation and then be optimized away, however.) - * - * @param data type for {@code output} output */ @OpMetadata( opType = BroadcastTo.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ClipByValue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ClipByValue.java index 4477b0d4924..2ae7185a7e5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ClipByValue.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ClipByValue.java @@ -39,8 +39,6 @@ * shape as {@code t} with its values clipped to {@code clip_value_min} and {@code clip_value_max}. * Any values less than {@code clip_value_min} are set to {@code clip_value_min}. Any values * greater than {@code clip_value_max} are set to {@code clip_value_max}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ClipByValue.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CompositeTensorVariantToComponents.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CompositeTensorVariantToComponents.java index 40f7209a04a..e8288c59607 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CompositeTensorVariantToComponents.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CompositeTensorVariantToComponents.java @@ -113,7 +113,7 @@ public static class Inputs extends RawOpInputs data type for {@code output} output */ @OpMetadata( opType = Concat.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ConcatOffset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ConcatOffset.java index df14b30a11b..d8082c3b6ef 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ConcatOffset.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ConcatOffset.java @@ -53,8 +53,6 @@ * * *

This is typically used by gradient computations for a concat operation. - * - * @param data type for {@code offset} output */ @OpMetadata( opType = ConcatOffset.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Copy.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Copy.java index 234663012a6..a04de48877b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Copy.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Copy.java @@ -42,8 +42,6 @@ * deep-copying. See the documentation of Debug* ops for more details. *

Unlike the CopyHost Op, this op does not have HostMemory constraint on its * input or output. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Copy.OP_NAME, @@ -223,9 +221,9 @@ public static class Inputs extends RawOpInputs> { /** * A list of debug op spec (op, url, gated_grpc) for attached debug * ops. Each element of the list has the format - * ;;, wherein gated_grpc is boolean represented - * as 0/1. E.g., "DebugIdentity;grpc://foo:3333;1", - * "DebugIdentity;file:///tmp/tfdbg_1;0". + * <debug_op>;<grpc_url>;<gated_grpc>, wherein gated_grpc is boolean represented + * as 0/1. E.g., "DebugIdentity;grpc://foo:3333;1", + * "DebugIdentity;file:///tmp/tfdbg_1;0". */ public final String[] debugOpsSpec; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyHost.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyHost.java index 4a650c8bc0a..055c9d878bf 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyHost.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyHost.java @@ -40,8 +40,6 @@ * gRPC gating status, the output will simply forward the input tensor without * deep-copying. See the documentation of Debug* ops for more details. *

Unlike the Copy Op, this op has HostMemory constraint on its input or output. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CopyHost.OP_NAME, @@ -221,9 +219,9 @@ public static class Inputs extends RawOpInputs> { /** * A list of debug op spec (op, url, gated_grpc) for attached debug * ops. Each element of the list has the format - * ;;, wherein gated_grpc is boolean represented - * as 0/1. E.g., "DebugIdentity;grpc://foo:3333;1", - * "DebugIdentity;file:///tmp/tfdbg_1;0". + * <debug_op>;<grpc_url>;<gated_grpc>, wherein gated_grpc is boolean represented + * as 0/1. E.g., "DebugIdentity;grpc://foo:3333;1", + * "DebugIdentity;file:///tmp/tfdbg_1;0". */ public final String[] debugOpsSpec; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMesh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMesh.java index f83d6c6ad61..166d4613d54 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMesh.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMesh.java @@ -35,8 +35,6 @@ /** * The CopyToMesh operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = CopyToMesh.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMeshGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMeshGrad.java index fa3467cd849..095d5b5d7ce 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMeshGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CopyToMeshGrad.java @@ -35,8 +35,6 @@ /** * The CopyToMeshGrad operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = CopyToMeshGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java index 7a81a4419e6..0f404fa1419 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/CountUpTo.java @@ -35,8 +35,6 @@ /** * Increments 'ref' until it reaches 'limit'. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CountUpTo.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DecodeProto.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DecodeProto.java index ab5d32b01cc..be36191dd31 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DecodeProto.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DecodeProto.java @@ -298,13 +298,13 @@ public static class Inputs extends RawOpInputs { public final DataType[] outputTypes; /** - * Either the special value `local://` or a path to a file containing - * a serialized `FileDescriptorSet`. + * Either the special value {@code local://} or a path to a file containing + * a serialized {@code FileDescriptorSet}. */ public final String descriptorSource; /** - * Either `binary` or `text`. + * Either {@code binary} or {@code text}. */ public final String messageFormat; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeepCopy.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeepCopy.java index ca15dbb9a55..f0b9b3927a8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeepCopy.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DeepCopy.java @@ -35,8 +35,6 @@ /** * Makes a copy of {@code x}. - * - * @param data type for {@code y} output */ @OpMetadata( opType = DeepCopy.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyTemporaryVariable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyTemporaryVariable.java index cc8f2bafb2f..876a1e46ee5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyTemporaryVariable.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DestroyTemporaryVariable.java @@ -41,8 +41,6 @@ * This is typically achieved by chaining the ref through each assign op, or by * using control dependencies. *

Outputs the final value of the tensor pointed to by 'ref'. - * - * @param data type for {@code value} output */ @OpMetadata( opType = DestroyTemporaryVariable.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicPartition.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicPartition.java index b851e0cccdf..d7d7bf7c328 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicPartition.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicPartition.java @@ -78,8 +78,6 @@ * * * - * - * @param data type for {@code outputs} output */ @OpMetadata( opType = DynamicPartition.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicStitch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicStitch.java index 9aba2968627..d160ab8255c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicStitch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/DynamicStitch.java @@ -90,8 +90,6 @@ *

* *
- * - * @param data type for {@code merged} output */ @OpMetadata( opType = DynamicStitch.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EditDistance.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EditDistance.java index 959f61975ea..228743f17cd 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EditDistance.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EditDistance.java @@ -222,8 +222,7 @@ public static class Inputs extends RawOpInputs { /** * boolean (if true, edit distances are normalized by length of truth). - * - * The output is: + *

The output is: */ public final boolean normalize; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java index 02c76780ba2..6f7d74d94e5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Empty.java @@ -38,8 +38,6 @@ /** * Creates a tensor with the given shape. *

This operation creates a tensor of {@code shape} and {@code dtype}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Empty.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EnsureShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EnsureShape.java index 131285dc0e6..bbada3714ac 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EnsureShape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/EnsureShape.java @@ -38,8 +38,6 @@ * Ensures that the tensor's shape matches the expected shape. * Raises an error if the input tensor's shape does not match the specified shape. * Returns the input tensor otherwise. - * - * @param data type for {@code output} output */ @OpMetadata( opType = EnsureShape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Enter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Enter.java index baed3b18053..309e5700eb1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Enter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Enter.java @@ -40,8 +40,6 @@ * {@code is_constant} is true, {@code output} is a constant in the child frame; otherwise * it may be changed in the child frame. At most {@code parallel_iterations} iterations * are run in parallel in the child frame. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Enter.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Exit.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Exit.java index c1535016b59..8dea6a66fe6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Exit.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Exit.java @@ -36,8 +36,6 @@ /** * Exits the current frame to its parent frame. * Exit makes its input {@code data} available to the parent frame. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Exit.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExpandDims.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExpandDims.java index bf17427d228..0f0e030b71d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExpandDims.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExpandDims.java @@ -59,8 +59,6 @@ *

{@code -1-input.dims() <= dim <= input.dims()} *

This operation is related to {@code squeeze()}, which removes dimensions of * size 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ExpandDims.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java index cd19ad800ff..350c416e235 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ExtractVolumePatches.java @@ -36,8 +36,6 @@ /** * Extract {@code patches} from {@code input} and put them in the {@code "depth"} output dimension. 3D extension of {@code extract_image_patches}. - * - * @param data type for {@code patches} output */ @OpMetadata( opType = ExtractVolumePatches.OP_NAME, @@ -123,13 +121,13 @@ public static class Inputs extends RawOpInputs input; /** - * The size of the sliding window for each dimension of `input`. + * The size of the sliding window for each dimension of {@code input}. */ public final long[] ksizes; /** * 1-D of length 5. How far the centers of two consecutive patches are in - * `input`. Must be: `[1, stride_planes, stride_rows, stride_cols, 1]`. + * {@code input}. Must be: {@code [1, stride_planes, stride_rows, stride_cols, 1]}. */ public final long[] strides; @@ -140,13 +138,11 @@ public static class Inputs extends RawOpInputsThe size-related attributes are specified as follows: + * 

      * ksizes = [1, ksize_planes, ksize_rows, ksize_cols, 1]
      * strides = [1, stride_planes, strides_rows, strides_cols, 1]
-     * ```
+     *
*/ public final String padding; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/FakeParam.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/FakeParam.java index 1f6ceeecc16..79e63958dda 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/FakeParam.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/FakeParam.java @@ -40,8 +40,6 @@ * valid output when run, so must either be removed (e.g. replaced with a * function input) or guaranteed not to be used (e.g. if mirroring an * intermediate output needed for the gradient computation of the other branch). - * - * @param data type for {@code output} output */ @OpMetadata( opType = FakeParam.OP_NAME, @@ -110,8 +108,10 @@ public static class Inputs extends RawOpInputs> { public final DataType dtype; /** - * The purported shape of the output. This is only used for shape inference; - * the output will not necessarily have this shape. Can be a partial shape. + * 
+     * The purported shape of the output. This is only used for shape inference;
+     * the output will not necessarily have this shape. Can be a partial shape.
+     *
*/ public final Shape shape; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fill.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fill.java index 5ba5931795e..8634981f57c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fill.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Fill.java @@ -53,8 +53,6 @@ *
  • Because {@code tf.fill} evaluates at graph runtime, it supports dynamic shapes * based on other runtime Tensors, unlike {@code tf.constant}.
    • * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Fill.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Gather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Gather.java index 1b1e3f888ee..cbd71fe5e36 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Gather.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Gather.java @@ -58,8 +58,6 @@ * On GPU, if an out of bound index is found, a 0 is stored in the * corresponding output value. *

    See also {@code tf.batch_gather} and {@code tf.gather_nd}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Gather.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GatherNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GatherNd.java index b1a05118129..406323aea9c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GatherNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GatherNd.java @@ -125,8 +125,6 @@ * output = [['b0', 'b1'], ['d0', 'c1']] * *

    See also {@code tf.gather} and {@code tf.batch_gather}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = GatherNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java index a2445004e6d..0cccfb42045 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GetSessionTensor.java @@ -37,8 +37,6 @@ /** * Get the value of the tensor specified by its handle. - * - * @param data type for {@code value} output */ @OpMetadata( opType = GetSessionTensor.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GuaranteeConst.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GuaranteeConst.java index 8839f77471f..c4235de8ff2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GuaranteeConst.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/GuaranteeConst.java @@ -39,8 +39,6 @@ *

    Only accepts value typed tensors as inputs and rejects resource variable handles * as input. *

    Returns the input tensor without modification. - * - * @param data type for {@code output} output */ @OpMetadata( opType = GuaranteeConst.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java index 0846ac056c0..782cfc69f05 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HistogramFixedWidth.java @@ -51,8 +51,6 @@ * variables.global_variables_initializer().run() * sess.run(hist) => [2, 1, 1, 0, 2] * - * - * @param data type for {@code out} output */ @OpMetadata( opType = HistogramFixedWidth.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HostConst.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HostConst.java index b655a120ae6..82f5ef8f295 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HostConst.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/HostConst.java @@ -37,8 +37,6 @@ /** * Returns a constant tensor on the host. Only for writing C++ tests. - * - * @param data type for {@code output} output */ @OpMetadata( opType = HostConst.OP_NAME, @@ -97,7 +95,7 @@ public Output asOutput() { ) public static class Inputs extends RawOpInputs> { /** - * Attr `value` is the tensor to return. + * Attr {@code value} is the tensor to return. */ public final Tensor value; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Identity.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Identity.java index 12c84344373..d0729ab93da 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Identity.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Identity.java @@ -35,8 +35,6 @@ /** * Return a tensor with the same shape and contents as the input tensor or value. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Identity.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java index 47cbe749ee9..12d647268ba 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ImmutableConst.java @@ -38,8 +38,6 @@ /** * Returns immutable tensor from memory region. * The current implementation memmaps the tensor from a file. - * - * @param data type for {@code tensor} output */ @OpMetadata( opType = ImmutableConst.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InitializeTableFromTextFile.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InitializeTableFromTextFile.java index 1da5f008223..d8a78e24266 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InitializeTableFromTextFile.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InitializeTableFromTextFile.java @@ -192,13 +192,13 @@ public static class Inputs extends RawOpInputs { public final Operand filename; /** - * Column index in a line to get the table `key` values from. + * Column index in a line to get the table {@code key} values from. */ public final long keyIndex; /** * Column index that represents information of a line to get the table - * `value` values from. + * {@code value} values from. */ public final long valueIndex; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceAdd.java index c42388fc55c..78f37851589 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceAdd.java @@ -39,8 +39,6 @@ * 

      * Computes y = x; y[i, :] += v; return y.
  *
    - * - * @param data type for {@code y} output */ @OpMetadata( opType = InplaceAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceSub.java index a39bf6d741b..31d0287aab2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceSub.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceSub.java @@ -40,8 +40,6 @@ * * Computes y = x; y[i, :] -= v; return y. * - * - * @param data type for {@code y} output */ @OpMetadata( opType = InplaceSub.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceUpdate.java index 8aecb6edf8c..d34e0f15011 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceUpdate.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/InplaceUpdate.java @@ -39,8 +39,6 @@ * Computes {@code x[i, :] = v; return x}. *

    Originally this function is mutative however for compilation we make this * operation create / operate on a copy of {@code x}. - * - * @param data type for {@code y} output */ @OpMetadata( opType = InplaceUpdate.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java index 3473ddf487e..317eb054e29 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LinSpace.java @@ -42,8 +42,6 @@ * 

      * tf.linspace(10.0, 12.0, 3, name="linspace") => [ 10.0  11.0  12.0]
  *
    - * - * @param data type for {@code output} output */ @OpMetadata( opType = LinSpace.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java index 7406671423c..7546b26f8f4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableExport.java @@ -36,10 +36,6 @@ /** * Outputs all keys and values in the table. - * - * @param data type for {@code keys} output - * - * @param data type for {@code values} output */ @OpMetadata( opType = LookupTableExport.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableFind.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableFind.java index b097f2ee81d..1155c94662f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableFind.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LookupTableFind.java @@ -39,8 +39,6 @@ * The output {@code values} is of the type of the table values. *

    The scalar {@code default_value} is the value output for keys not present in the * table. It must also be of the same type as the table values. - * - * @param data type for {@code values} output */ @OpMetadata( opType = LookupTableFind.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java index 8cf633e2d7f..2a4b761a8fd 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/LowerBound.java @@ -51,8 +51,6 @@ *

    result = LowerBound(sorted_sequence, values) *

    result == [[1, 2, 2], * [0, 1, 5]] - * - * @param data type for {@code output} output */ @OpMetadata( opType = LowerBound.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapStage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapStage.java index 8242cfaa5c1..19d9c0e99f9 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapStage.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MapStage.java @@ -220,7 +220,7 @@ public static class Inputs extends RawOpInputs { public final Iterable> values; /** - * Maximum number of elements in the Staging Area. If > 0, inserts + * Maximum number of elements in the Staging Area. If > 0, inserts * on the container will block when the capacity is reached. */ public final long capacity; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Max.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Max.java index fb03ee5c942..04c4f1481d3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Max.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Max.java @@ -39,8 +39,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Max.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Merge.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Merge.java index 7e4c77434b9..f5a189c9c58 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Merge.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Merge.java @@ -41,8 +41,6 @@ * It is usually combined with {@code Switch} to implement branching. *

    {@code Merge} forwards the first tensor to become available to {@code output}, and sets * {@code value_index} to its index in {@code inputs}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Merge.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Min.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Min.java index f3db8fedac0..89ac31b5854 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Min.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Min.java @@ -39,8 +39,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Min.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPad.java index 172a9a91c32..751bec8fd66 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPad.java @@ -57,8 +57,6 @@ * [5, 4, 4, 5, 6, 6, 5] * [5, 4, 4, 5, 6, 6, 5]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = MirrorPad.OP_NAME, @@ -146,11 +144,11 @@ public static class Inputs extends RawOpInputs> { public final DataType Tpaddings; /** - * Either `REFLECT` or `SYMMETRIC`. In reflect mode the padded regions + * Either {@code REFLECT} or {@code SYMMETRIC}. In reflect mode the padded regions * do not include the borders, while in symmetric mode the padded regions - * do include the borders. For example, if `input` is `[1, 2, 3]` and `paddings` - * is `[0, 2]`, then the output is `[1, 2, 3, 2, 1]` in reflect mode, and - * it is `[1, 2, 3, 3, 2]` in symmetric mode. + * do include the borders. For example, if {@code input} is {@code [1, 2, 3]} and {@code paddings} + * is {@code [0, 2]}, then the output is {@code [1, 2, 3, 2, 1]} in reflect mode, and + * it is {@code [1, 2, 3, 3, 2]} in symmetric mode. */ public final String mode; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPadGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPadGrad.java index 6e8c0d0680f..d1286e4bd89 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPadGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/MirrorPadGrad.java @@ -50,8 +50,6 @@ * pad(t, paddings) ==> [[ 1, 5] * [11, 28]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = MirrorPadGrad.OP_NAME, @@ -135,7 +133,7 @@ public static class Inputs extends RawOpInputs public final DataType Tpaddings; /** - * The mode used in the `MirrorPad` op. + * The mode used in the {@code MirrorPad} op. */ public final String mode; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java index d49045a1bad..5e8f5709b65 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclAllReduce.java @@ -46,8 +46,6 @@ * num_devices: The number of devices participating in this reduction. * shared_name: Identifier that shared between ops of the same reduction. * - * @param data type for {@code data} output - * * @deprecated use {@link org.tensorflow.op.distribute.NcclAllReduce} instead */ @OpMetadata( diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java index 4d5c2d771de..5e6c2a583ef 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclBroadcast.java @@ -43,8 +43,6 @@ * output: The same as input. * shape: The shape of the input tensor. * - * @param data type for {@code output} output - * * @deprecated use {@link org.tensorflow.op.distribute.NcclBroadcast} instead */ @OpMetadata( diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java index 8b050aba7e3..cd3dea3af6f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NcclReduce.java @@ -43,8 +43,6 @@ * data: the value of the reduction across all {@code num_devices} devices. * reduction: the reduction operation to perform. * - * @param data type for {@code data} output - * * @deprecated use {@link org.tensorflow.op.distribute.NcclReduce} instead */ @OpMetadata( diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NextIteration.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NextIteration.java index 33e50ce1b5d..1f0f73c672f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NextIteration.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/NextIteration.java @@ -35,8 +35,6 @@ /** * Makes its input available to the next iteration. - * - * @param data type for {@code output} output */ @OpMetadata( opType = NextIteration.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OneHot.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OneHot.java index 09f55f7eaff..8ed3c25bd8e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OneHot.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OneHot.java @@ -111,8 +111,6 @@ * [0.0, 0.0, 0.0] // one_hot(-1) * ] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = OneHot.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OnesLike.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OnesLike.java index b69df0d0952..51178e062f4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OnesLike.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OnesLike.java @@ -35,8 +35,6 @@ /** * Returns a tensor of ones with the same shape and type as x. - * - * @param data type for {@code y} output */ @OpMetadata( opType = OnesLike.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapStage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapStage.java index 7ce2df9f31b..cd5c7dfdec3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapStage.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/OrderedMapStage.java @@ -221,7 +221,7 @@ public static class Inputs extends RawOpInputs { public final Iterable> values; /** - * Maximum number of elements in the Staging Area. If > 0, inserts + * Maximum number of elements in the Staging Area. If > 0, inserts * on the container will block when the capacity is reached. */ public final long capacity; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Pad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Pad.java index d80e87f0f2d..60ddbcf6817 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Pad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Pad.java @@ -56,8 +56,6 @@ * [0, 0, 2, 2, 0, 0] * [0, 0, 0, 0, 0, 0]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Pad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelConcat.java index c5cbde1618c..b12c3b896aa 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelConcat.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelConcat.java @@ -50,8 +50,6 @@ * that the input shapes be known during graph construction. Parallel concat * will copy pieces of the input into the output as they become available, in * some situations this can provide a performance benefit. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ParallelConcat.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelDynamicStitch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelDynamicStitch.java index a23c3d135a8..c9fd16880ca 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelDynamicStitch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ParallelDynamicStitch.java @@ -89,8 +89,6 @@ *

    * *
    - * - * @param data type for {@code merged} output */ @OpMetadata( opType = ParallelDynamicStitch.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java index 634500dcfc0..f4c450973da 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Placeholder.java @@ -40,8 +40,6 @@ * N.B. This operation will fail with an error if it is executed. It is * intended as a way to represent a value that will always be fed, and to * provide attrs that enable the fed value to be checked at runtime. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Placeholder.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/PlaceholderWithDefault.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/PlaceholderWithDefault.java index 9604ea0a92a..202d4cc476c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/PlaceholderWithDefault.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/PlaceholderWithDefault.java @@ -36,8 +36,6 @@ /** * A placeholder op that passes through {@code input} when its output is not fed. - * - * @param data type for {@code output} output */ @OpMetadata( opType = PlaceholderWithDefault.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Prod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Prod.java index 71c7f986eb6..3f1c696a0bc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Prod.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Prod.java @@ -40,8 +40,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Prod.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/QuantizedReshape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/QuantizedReshape.java index 6e92b83bf89..84816c6893f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/QuantizedReshape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/QuantizedReshape.java @@ -37,8 +37,6 @@ /** * Reshapes a quantized tensor as per the Reshape op. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedReshape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RandomIndexShuffle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RandomIndexShuffle.java index 5ac291f867d..76538abf9cb 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RandomIndexShuffle.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RandomIndexShuffle.java @@ -39,8 +39,6 @@ *

    If multiple inputs are vectors (matrix in case of seed) then the size of the * first dimension must match. *

    The outputs are deterministic. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomIndexShuffle.OP_NAME, @@ -166,7 +164,7 @@ public static class Inputs extends RawOpInputs - * - * @param data type for {@code output} output */ @OpMetadata( opType = Range.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java index 236991942ee..f57c2781c3f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReadVariableOp.java @@ -41,8 +41,6 @@ * writes on which this operation depends directly or indirectly, and to not be * influenced by any of the writes which depend directly or indirectly on this * operation. - * - * @param data type for {@code value} output */ @OpMetadata( opType = ReadVariableOp.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java index 1853328543d..5b3caab37b8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Recv.java @@ -36,8 +36,6 @@ /** * Receives the named tensor from send_device on recv_device. - * - * @param data type for {@code tensor} output */ @OpMetadata( opType = Recv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMax.java index 529841fd5fa..dca6c6a5ffc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMax.java @@ -39,8 +39,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ReduceMax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMin.java index f349357096b..a7e544cfaab 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceMin.java @@ -39,8 +39,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ReduceMin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceProd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceProd.java index 49008ad1a36..3dc53ad9c58 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceProd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceProd.java @@ -40,8 +40,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ReduceProd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceSum.java index 05851e60764..bbe161f9210 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceSum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReduceSum.java @@ -40,8 +40,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ReduceSum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefEnter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefEnter.java index 888c0ee977b..218092a2563 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefEnter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefEnter.java @@ -39,8 +39,6 @@ * {@code is_constant} is true, {@code output} is a constant in the child frame; otherwise * it may be changed in the child frame. At most {@code parallel_iterations} iterations * are run in parallel in the child frame. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RefEnter.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefExit.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefExit.java index c23ff2d03d7..9a840da2c3d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefExit.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefExit.java @@ -36,8 +36,6 @@ /** * Exits the current frame to its parent frame. * Exit makes its input {@code data} available to the parent frame. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RefExit.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefIdentity.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefIdentity.java index 53d515be8e1..c3bb004b548 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefIdentity.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefIdentity.java @@ -35,8 +35,6 @@ /** * Return the same ref tensor as the input ref tensor. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RefIdentity.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefMerge.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefMerge.java index 9354cb2847b..4baf6cc6260 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefMerge.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefMerge.java @@ -41,8 +41,6 @@ * It is usually combined with {@code Switch} to implement branching. *

    {@code Merge} forwards the first tensor for become available to {@code output}, and sets * {@code value_index} to its index in {@code inputs}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RefMerge.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefNextIteration.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefNextIteration.java index 5c7f1d2c4b7..ef647c70cd6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefNextIteration.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefNextIteration.java @@ -35,8 +35,6 @@ /** * Makes its input available to the next iteration. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RefNextIteration.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSelect.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSelect.java index 02c6ddc8e2f..d7ffa33956e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSelect.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSelect.java @@ -37,8 +37,6 @@ /** * Forwards the {@code index}th element of {@code inputs} to {@code output}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RefSelect.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSwitch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSwitch.java index 04a2d4811ab..2e97b2bbcad 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSwitch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RefSwitch.java @@ -39,8 +39,6 @@ * If {@code pred} is true, the {@code data} input is forwarded to {@code output_true}. Otherwise, * the data goes to {@code output_false}. *

    See also {@code Switch} and {@code Merge}. - * - * @param data type for {@code output_false} output */ @OpMetadata( opType = RefSwitch.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Relayout.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Relayout.java index 959987e6200..503d3cfe42a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Relayout.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Relayout.java @@ -35,8 +35,6 @@ /** * The Relayout operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = Relayout.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RelayoutLike.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RelayoutLike.java index 7fd8a91fb8b..499cb8d6c72 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RelayoutLike.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/RelayoutLike.java @@ -35,8 +35,6 @@ /** * The RelayoutLike operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = RelayoutLike.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reshape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reshape.java index 4b1ce466a7d..54c0aba057e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reshape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reshape.java @@ -90,8 +90,6 @@ * # shape `[]` reshapes to a scalar * reshape(t, []) ==> 7 * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Reshape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java index f8e5cf5abef..0ca0faa179e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceCountUpTo.java @@ -37,8 +37,6 @@ /** * Increments variable pointed to by 'resource' until it reaches 'limit'. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ResourceCountUpTo.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java index 5dff2d95dc2..c458bacea4c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGather.java @@ -49,8 +49,6 @@ * # Higher rank indices * output[i, ..., j, :, ... :] = params[indices[i, ..., j], :, ..., :] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = ResourceGather.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java index 1a86a282ab9..f9c6b72b544 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ResourceGatherNd.java @@ -37,8 +37,6 @@ /** * The ResourceGatherNd operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = ResourceGatherNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reverse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reverse.java index 65a6ac9ab0c..711b7148209 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reverse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Reverse.java @@ -76,8 +76,6 @@ * [16, 17, 18, 19], * [12, 13, 14, 15]]]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Reverse.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReverseSequence.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReverseSequence.java index b7eb3fb25a2..e18f16874f0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReverseSequence.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ReverseSequence.java @@ -84,8 +84,6 @@ * output[3:, :, 2, :, ...] = input[3:, :, 2, :, ...] * output[2:, :, 3, :, ...] = input[2:, :, 3, :, ...] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = ReverseSequence.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Roll.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Roll.java index a2f04750d53..e190730b970 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Roll.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Roll.java @@ -54,8 +54,6 @@ * # 't' is [[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]] * roll(t, shift=[2, -3], axis=[1, 1]) ==> [[1, 2, 3, 4, 0], [6, 7, 8, 9, 5]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Roll.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterAdd.java index bc66b56b3d1..9f0bc6a526f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterAdd.java @@ -55,8 +55,6 @@ *

    * *
    - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterDiv.java index 083f4de2a81..902d11400e5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterDiv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterDiv.java @@ -52,8 +52,6 @@ *

    Duplicate entries are handled correctly: if multiple {@code indices} reference * the same location, their contributions divide. *

    Requires {@code updates.shape = indices.shape + ref.shape[1:]} or {@code updates.shape = []}. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterDiv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java index 162556fb11c..9b761e52419 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMax.java @@ -54,8 +54,6 @@ *

    * *
    - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterMax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java index 4264f92bc7e..7f725ad19d0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMin.java @@ -54,8 +54,6 @@ *
    * *
    - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterMin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMul.java index 7fb20e9d36e..ae8bbca9670 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterMul.java @@ -52,8 +52,6 @@ *

    Duplicate entries are handled correctly: if multiple {@code indices} reference * the same location, their contributions multiply. *

    Requires {@code updates.shape = indices.shape + ref.shape[1:]} or {@code updates.shape = []}. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterMul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNd.java index 34487ebf9d7..45b242e6259 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNd.java @@ -109,8 +109,6 @@ * *

    Note that on CPU, if an out of bound index is found, an error is returned. * On GPU, if an out of bound index is found, the index is ignored. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ScatterNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdAdd.java index aef9eed4a32..f427c60fe5e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdAdd.java @@ -62,8 +62,6 @@ * *

    See {@code tf.scatter_nd} for more details about how to make updates to * slices. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterNdAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMax.java index 0adccafee2a..1acea47e149 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMax.java @@ -36,8 +36,6 @@ /** * Computes element-wise maximum. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterNdMax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMin.java index d2780381fcb..357ba576649 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdMin.java @@ -36,8 +36,6 @@ /** * Computes element-wise minimum. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterNdMin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdNonAliasingAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdNonAliasingAdd.java index 4d29ef748d8..2945b588d8a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdNonAliasingAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdNonAliasingAdd.java @@ -63,8 +63,6 @@ * [1, 13, 3, 14, 14, 6, 7, 20] * *

    See {@code tf.scatter_nd} for more details about how to make updates to slices. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ScatterNdNonAliasingAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdSub.java index b2018d27511..54a8a410f78 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdSub.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdSub.java @@ -63,8 +63,6 @@ * *

    See {@code tf.scatter_nd} for more details about how to make updates to * slices. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterNdSub.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdUpdate.java index 56427f20fac..716b09592cc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdUpdate.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterNdUpdate.java @@ -62,8 +62,6 @@ *

    See {@code tf.scatter_nd} for more details about how to make updates to * slices. *

    See also {@code tf.scatter_update} and {@code tf.batch_scatter_update}. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterNdUpdate.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterSub.java index 06d274ff356..4686a81470f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterSub.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterSub.java @@ -54,8 +54,6 @@ *

    * *
    - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterSub.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterUpdate.java index 711cbf7485f..60e22039589 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterUpdate.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ScatterUpdate.java @@ -57,8 +57,6 @@ * * *

    See also {@code tf.batch_scatter_update} and {@code tf.scatter_nd_update}. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = ScatterUpdate.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Select.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Select.java index 71caff86d14..c88ea468f39 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Select.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Select.java @@ -36,8 +36,6 @@ /** * The SelectV2 operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = Select.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java index 61af8e762a2..562b2088b93 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SetDiff1d.java @@ -54,10 +54,6 @@ * out ==> [2, 4, 6] * idx ==> [1, 3, 5] * - * - * @param data type for {@code out} output - * - * @param data type for {@code idx} output */ @OpMetadata( opType = SetDiff1d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java index 4f9f9115847..2f7592fbc03 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Shape.java @@ -44,8 +44,6 @@ * # 't' is [[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]] * shape(t) ==> [2, 2, 3] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Shape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java index b56a39452d5..b53a00a1a82 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ShapeN.java @@ -41,8 +41,6 @@ /** * Returns shape of tensors. * This operation returns N 1-D integer tensors representing shape of {@code input[i]s}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ShapeN.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java index 1ad02bc0f9b..2be90850900 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Size.java @@ -45,8 +45,6 @@ * # 't' is [[[1, 1,, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]]] * size(t) ==> 12 * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Size.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Slice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Slice.java index b53cae539a0..37a168fb6f7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Slice.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Slice.java @@ -41,8 +41,6 @@ * 'begin'. *

    Requirements: * 0 <= begin[i] <= begin[i] + size[i] <= Di for i in [0, n) - * - * @param data type for {@code output} output */ @OpMetadata( opType = Slice.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Snapshot.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Snapshot.java index d8b1ed563d9..bafca31221f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Snapshot.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Snapshot.java @@ -35,8 +35,6 @@ /** * Returns a copy of the input tensor. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Snapshot.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SpaceToBatchNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SpaceToBatchNd.java index d56e6ef8709..2a366e46641 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SpaceToBatchNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SpaceToBatchNd.java @@ -132,8 +132,6 @@ * *

    Among others, this operation is useful for reducing atrous convolution into * regular convolution. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SpaceToBatchNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Split.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Split.java index f6a01ed1950..dc4fad88677 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Split.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Split.java @@ -38,8 +38,6 @@ /** * Splits a tensor into {@code num_split} tensors along one dimension. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Split.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SplitV.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SplitV.java index 8d1beb3fc5b..cc0525e9645 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SplitV.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SplitV.java @@ -39,8 +39,6 @@ /** * Splits a tensor into {@code num_split} tensors along one dimension. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SplitV.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Squeeze.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Squeeze.java index c904d7e7cda..52155b47d43 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Squeeze.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Squeeze.java @@ -50,8 +50,6 @@ * # 't' is a tensor of shape [1, 2, 1, 3, 1, 1] * shape(squeeze(t, [2, 4])) ==> [1, 2, 3, 1] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Squeeze.OP_NAME, @@ -194,7 +192,7 @@ public static class Inputs extends RawOpInputs> { /** * If specified, only squeezes the dimensions listed. The dimension * index starts at 0. It is an error to squeeze a dimension that is not 1. Must - * be in the range `[-rank(input), rank(input))`. + * be in the range {@code [-rank(input), rank(input))}. */ public final long[] axis; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stack.java index 81b4adc7f5e..976a86955b3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stack.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stack.java @@ -51,8 +51,6 @@ * pack([x, y, z], axis=1) => [[1, 2, 3], [4, 5, 6]] * *

    This is the opposite of {@code unpack}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Stack.OP_NAME, @@ -162,7 +160,7 @@ public static class Inputs extends RawOpInputs> { /** * Dimension along which to pack. Negative values wrap around, so the - * valid range is `[-(R+1), R+1)`. + * valid range is {@code [-(R+1), R+1)}. */ public final long axis; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPop.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPop.java index a6a3021ce14..502cfcc8c06 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPop.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPop.java @@ -36,8 +36,6 @@ /** * Pop the element at the top of the stack. - * - * @param data type for {@code elem} output */ @OpMetadata( opType = StackPop.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPush.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPush.java index 33a9ecf85a1..f9f05ff1912 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPush.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StackPush.java @@ -35,8 +35,6 @@ /** * Push an element onto the stack. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StackPush.OP_NAME, @@ -150,7 +148,7 @@ public static class Inputs extends RawOpInputs> { public final DataType T; /** - * Swap `elem` to CPU. Default to false. + * Swap {@code elem} to CPU. Default to false. */ public final boolean swapMemory; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stage.java index 3b68db75d98..11adc169e0d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stage.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Stage.java @@ -203,14 +203,14 @@ public static class Inputs extends RawOpInputs { public final Iterable> values; /** - * Maximum number of elements in the Staging Area. If > 0, inserts + * Maximum number of elements in the Staging Area. If > 0, inserts * on the container will block when the capacity is reached. */ public final long capacity; /** * The maximum number of bytes allowed for Tensors in the Staging Area. - * If > 0, inserts will block until sufficient space is available. + * If > 0, inserts will block until sufficient space is available. */ public final long memoryLimit; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StochasticCastToInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StochasticCastToInt.java index 29da2cb9a53..a06a2c8017d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StochasticCastToInt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StochasticCastToInt.java @@ -40,8 +40,6 @@ * Stochastically cast a given tensor from floats to ints. * The values are cast with a deterministic pseudo-random tensor from a uniform distribution generated from user given key, counter, algorithm. Values will saturate if out of the specified integer type range, and will become zero if inputs are NaN. *

    The outputs are a deterministic function of {@code input}, {@code key}, {@code counter}, {@code alg}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StochasticCastToInt.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StopGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StopGradient.java index c2086cb3e92..fb486c42253 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StopGradient.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StopGradient.java @@ -85,8 +85,6 @@ *

  • Adversarial training, where no backprop should happen through the adversarial * example generation process.
    • * - * - * @param data type for {@code output} output */ @OpMetadata( opType = StopGradient.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSlice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSlice.java index fd8a07ebe47..ec55dae1c24 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSlice.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSlice.java @@ -133,8 +133,6 @@ *

    Requirements: * {@code 0 != strides[i] for i in [0, m)} * {@code ellipsis_mask must be a power of two (only one ellipsis)} - * - * @param data type for {@code output} output */ @OpMetadata( opType = StridedSlice.OP_NAME, @@ -422,40 +420,40 @@ public static class Inputs extends RawOpInpu /** * a bitmask where a bit i being 1 means to ignore the begin * value and instead use the largest interval possible. At runtime - * begin[i] will be replaced with `[0, n-1)` if `stride[i] > 0` or - * `[-1, n-1]` if `stride[i] < 0` + * begin[i] will be replaced with {@code [0, n-1)} if {@code stride[i] > 0} or + * {@code [-1, n-1]} if {@code stride[i] < 0} */ public final long beginMask; /** - * analogous to `begin_mask` + * analogous to {@code begin_mask} */ public final long endMask; /** - * a bitmask where bit `i` being 1 means the `i`th + * a bitmask where bit {@code i} being 1 means the {@code i}th * position is actually an ellipsis. One bit at most can be 1. - * If `ellipsis_mask == 0`, then an implicit ellipsis mask of `1 << (m+1)` - * is provided. This means that `foo[3:5] == foo[3:5, ...]`. An ellipsis + * If {@code ellipsis_mask == 0}, then an implicit ellipsis mask of {@code 1 << (m+1)} + * is provided. This means that {@code foo[3:5] == foo[3:5, ...]}. An ellipsis * implicitly creates as many range specifications as necessary to fully * specify the sliced range for every dimension. For example for a 4-dimensional - * tensor `foo` the slice `foo[2, ..., 5:8]` implies `foo[2, :, :, 5:8]`. + * tensor {@code foo} the slice {@code foo[2, ..., 5:8]} implies {@code foo[2, :, :, 5:8]}. */ public final long ellipsisMask; /** - * a bitmask where bit `i` being 1 means the `i`th + * a bitmask where bit {@code i} being 1 means the {@code i}th * specification creates a new shape 1 dimension. For example - * `foo[:4, tf.newaxis, :2]` would produce a shape `(4, 1, 2)` tensor. + * {@code foo[:4, tf.newaxis, :2]} would produce a shape {@code (4, 1, 2)} tensor. */ public final long newAxisMask; /** - * a bitmask where bit `i` implies that the `i`th + * a bitmask where bit {@code i} implies that the {@code i}th * specification should shrink the dimensionality. begin and end * must imply a slice of size 1 in the dimension. For example in - * python one might do `foo[:, 3, :]` which would result in - * `shrink_axis_mask` being 2. + * python one might do {@code foo[:, 3, :]} which would result in + * {@code shrink_axis_mask} being 2. */ public final long shrinkAxisMask; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceAssign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceAssign.java index b2ab8d606e2..2911a675905 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceAssign.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceAssign.java @@ -41,8 +41,6 @@ * {@code begin}, {@code end}, {@code strides}, etc. work exactly as in {@code StridedSlice}. *

    NOTE this op currently does not support broadcasting and so {@code value}'s * shape must be exactly the shape produced by the slice of {@code ref}. - * - * @param data type for {@code output_ref} output */ @OpMetadata( opType = StridedSliceAssign.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceGrad.java index 2a234c9ab7a..fcd7518dd87 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/StridedSliceGrad.java @@ -43,8 +43,6 @@ *

    Arguments are the same as StridedSliceGrad with the exception that * {@code dy} is the input gradient to be propagated and {@code shape} is the * shape of {@code StridedSlice}'s {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StridedSliceGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Sum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Sum.java index 15957ea2189..abcdb1ee9ef 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Sum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Sum.java @@ -40,8 +40,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Sum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SwitchCond.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SwitchCond.java index c6a8f810467..c6842c9ab87 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SwitchCond.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/SwitchCond.java @@ -39,8 +39,6 @@ * If {@code pred} is true, the {@code data} input is forwarded to {@code output_true}. Otherwise, * the data goes to {@code output_false}. *

    See also {@code RefSwitch} and {@code Merge}. - * - * @param data type for {@code output_false} output */ @OpMetadata( opType = SwitchCond.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java index 3e8c8a70ec8..d66021bb728 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TemporaryVariable.java @@ -48,8 +48,6 @@ * var = state_ops.assign(var, [[4.0, 5.0]]) * var = state_ops.assign_add(var, [[6.0, 7.0]]) * final = state_ops._destroy_temporary_variable(var, var_name=var_name) - * - * @param data type for {@code ref} output */ @OpMetadata( opType = TemporaryVariable.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java index b3dbc08ef3e..75ba48a0102 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayConcat.java @@ -48,8 +48,6 @@ * (n0 + n1 + ... + n(T-1) x d0 x d1 x ...) * *

    All elements must have the same shape (excepting the first dimension). - * - * @param data type for {@code value} output */ @OpMetadata( opType = TensorArrayConcat.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java index 0f7fd351089..60d8b437b00 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayGather.java @@ -40,8 +40,6 @@ /** * Gather specific elements from the TensorArray into output {@code value}. * All elements selected by {@code indices} must have the same shape. - * - * @param data type for {@code value} output */ @OpMetadata( opType = TensorArrayGather.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java index 6e52e6ef906..d1cf5c89e65 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayPack.java @@ -39,8 +39,6 @@ /** * The TensorArrayPack operation - * - * @param data type for {@code value} output */ @OpMetadata( opType = TensorArrayPack.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java index 6765205c463..f5a0aa073a7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorArrayRead.java @@ -38,8 +38,6 @@ /** * Read an element from the TensorArray into output {@code value}. - * - * @param data type for {@code value} output */ @OpMetadata( opType = TensorArrayRead.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java index 664783a09c5..70ef65f9314 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListConcat.java @@ -48,8 +48,6 @@ * is not already set. * tensor: The concated result. * lengths: Output tensor containing sizes of the 0th dimension of tensors in the list, used for computing the gradient. - * - * @param data type for {@code tensor} output */ @OpMetadata( opType = TensorListConcat.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java index d955a6a636d..6190f9c1c01 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListElementShape.java @@ -39,8 +39,6 @@ * The shape of the elements of the given list, as a tensor. * input_handle: the list * element_shape: the shape of elements of the list - * - * @param data type for {@code element_shape} output */ @OpMetadata( opType = TensorListElementShape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java index 27a627b4759..ac725c72b97 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGather.java @@ -42,8 +42,6 @@ *

    input_handle: The input tensor list. * indices: The indices used to index into the list. * values: The tensor. - * - * @param data type for {@code values} output */ @OpMetadata( opType = TensorListGather.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java index 1ea76d2101e..244704b5754 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListGetItem.java @@ -40,8 +40,6 @@ * input_handle: the list * index: the position in the list from which an element will be retrieved * item: the element at that position - * - * @param data type for {@code item} output */ @OpMetadata( opType = TensorListGetItem.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java index ee7a5cde1c9..af805e71f9b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListPopBack.java @@ -42,8 +42,6 @@ * tensor: the withdrawn last element of the list * element_dtype: the type of elements in the list * element_shape: the shape of the output tensor - * - * @param data type for {@code tensor} output */ @OpMetadata( opType = TensorListPopBack.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java index fec4f942658..2d058b8e00d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorListStack.java @@ -41,8 +41,6 @@ *

    input_handle: the input list * tensor: the gathered result * num_elements: optional. If not -1, the number of elements in the list. - * - * @param data type for {@code tensor} output */ @OpMetadata( opType = TensorListStack.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapLookup.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapLookup.java index dccdc1ee996..a3e8b54e888 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapLookup.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapLookup.java @@ -39,8 +39,6 @@ * input_handle: the input map * key: the key to be looked up * value: the value found from the given key - * - * @param data type for {@code value} output */ @OpMetadata( opType = TensorMapLookup.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapStackKeys.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapStackKeys.java index b2a217c98e6..8942b2f9f8b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapStackKeys.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorMapStackKeys.java @@ -38,8 +38,6 @@ * Returns a Tensor stack of all keys in a tensor map. * input_handle: the input map * keys: the returned Tensor of all keys in the map - * - * @param data type for {@code keys} output */ @OpMetadata( opType = TensorMapStackKeys.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdAdd.java index a72a1defde1..38cfdb3a764 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdAdd.java @@ -96,8 +96,6 @@ * *

    Note: on CPU, if an out of bound index is found, an error is returned. * On GPU, if an out of bound index is found, the index is ignored. - * - * @param data type for {@code output} output */ @OpMetadata( opType = TensorScatterNdAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMax.java index ceddda24a20..48adcec0d0b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMax.java @@ -50,8 +50,6 @@ * * *

    Refer to {@code tf.tensor_scatter_nd_update} for more details. - * - * @param data type for {@code output} output */ @OpMetadata( opType = TensorScatterNdMax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMin.java index b6da07b4c31..b69849d62ee 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdMin.java @@ -36,8 +36,6 @@ /** * The TensorScatterMin operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = TensorScatterNdMin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdSub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdSub.java index 3623707e77e..a7fd984a513 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdSub.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdSub.java @@ -91,8 +91,6 @@ * *

    Note that on CPU, if an out of bound index is found, an error is returned. * On GPU, if an out of bound index is found, the index is ignored. - * - * @param data type for {@code output} output */ @OpMetadata( opType = TensorScatterNdSub.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdUpdate.java index 3c53fca7eab..10e10aea036 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdUpdate.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorScatterNdUpdate.java @@ -65,8 +65,6 @@ * indices.shape[:-1] + tensor.shape[indices.shape[-1]:] * *

    For usage examples see the python tf.tensor_scatter_nd_update {@link org.tensorflow.op.Ops#tensorScatterNdUpdate} function - * - * @param data type for {@code output} output */ @OpMetadata( opType = TensorScatterNdUpdate.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorStridedSliceUpdate.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorStridedSliceUpdate.java index 23b2d386a05..de80c141d72 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorStridedSliceUpdate.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/TensorStridedSliceUpdate.java @@ -41,8 +41,6 @@ * {@code strides} etc. work exactly as in {@code StridedSlice}. *

    NOTE this op currently does not support broadcasting and so {@code value}'s shape * must be exactly the shape produced by the slice of {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = TensorStridedSliceUpdate.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Tile.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Tile.java index c9a58b9158c..7339fdbb3de 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Tile.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Tile.java @@ -67,8 +67,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Tile.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unbatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unbatch.java index a49747c48ca..fa4c04f3c27 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unbatch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unbatch.java @@ -53,8 +53,6 @@ * shared_name: Instances of Unbatch with the same container and shared_name are * assumed to possibly belong to the same batch. If left empty, the op name will * be used as the shared name. - * - * @param data type for {@code unbatched_tensor} output */ @OpMetadata( opType = Unbatch.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnbatchGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnbatchGrad.java index 912e08c3a6b..25418f3986f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnbatchGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnbatchGrad.java @@ -49,8 +49,6 @@ * shared_name: Instances of UnbatchGrad with the same container and shared_name * are assumed to possibly belong to the same batch. If left empty, the op name * will be used as the shared name. - * - * @param data type for {@code batched_grad} output */ @OpMetadata( opType = UnbatchGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniformQuantizedClipByValue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniformQuantizedClipByValue.java index ca3c5dfdd14..f1a4eb739d1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniformQuantizedClipByValue.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniformQuantizedClipByValue.java @@ -40,8 +40,6 @@ * Given quantized {@code operand} which was quantized using {@code scales} and {@code zero_points}, performs clip by value using {@code min} and {@code max} values. * If quantization_axis is -1 (per-tensor quantized), the entire operand is clipped using scalar min, max. * Otherwise (per-channel quantized), the clipping is also done per-channel. - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformQuantizedClipByValue.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java index c4324a9f324..4d17cf9f141 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unique.java @@ -74,10 +74,6 @@ * [2, 0]] * idx ==> [0, 1, 1] * - * - * @param data type for {@code y} output - * - * @param data type for {@code idx} output */ @OpMetadata( opType = Unique.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java index 80a1804887f..8046082f95b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UniqueWithCounts.java @@ -78,10 +78,6 @@ * idx ==> [0, 1, 1] * count ==> [1, 2] * - * - * @param data type for {@code y} output - * - * @param data type for {@code idx} output */ @OpMetadata( opType = UniqueWithCounts.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java index 5393635bc69..ec7c8f8c6e9 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UnravelIndex.java @@ -52,8 +52,6 @@ *

    {@literal @}compatibility(numpy)
    * Equivalent to np.unravel_index *
    {@literal @}end_compatibility - * - * @param data type for {@code output} output */ @OpMetadata( opType = UnravelIndex.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstack.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstack.java index 3d04ec1ebc7..64c8de23911 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstack.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Unstack.java @@ -46,8 +46,6 @@ * and each tensor in {@code output} will have shape {@code (A, C, D)}. * Etc. *

    This is the opposite of {@code pack}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Unstack.OP_NAME, @@ -163,7 +161,7 @@ public static class Inputs extends RawOpInputs> { /** * Dimension along which to unpack. Negative values wrap around, so the - * valid range is `[-R, R)`. + * valid range is {@code [-R, R)}. */ public final long axis; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java index d5e939ffde6..78e45391c8a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/UpperBound.java @@ -51,8 +51,6 @@ *

    result = UpperBound(sorted_sequence, values) *

    result == [[1, 2, 4], * [0, 2, 5]] - * - * @param data type for {@code output} output */ @OpMetadata( opType = UpperBound.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java index a0febf9c223..d8b09bfddde 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/Variable.java @@ -40,8 +40,6 @@ * Outputs a ref to the tensor state so it may be read or modified. * TODO(zhifengc/mrry): Adds a pointer to a more detail document * about sharing states in tensorflow. - * - * @param data type for {@code ref} output */ @OpMetadata( opType = Variable.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java index 3f94b9efbd6..abfd8d7c504 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/VariableShape.java @@ -44,8 +44,6 @@ * # 't' is [[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]] * shape(t) ==> [2, 2, 3] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = VariableShape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ZerosLike.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ZerosLike.java index 792a37d112c..497cf5128b8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ZerosLike.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/core/ZerosLike.java @@ -35,8 +35,6 @@ /** * Returns a tensor of zeros with the same shape and type as x. - * - * @param data type for {@code y} output */ @OpMetadata( opType = ZerosLike.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java index a42cc0f51d2..131903f2fc1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/LeakyReluGrad.java @@ -35,8 +35,6 @@ /** * Computes rectified linear gradients for a LeakyRelu operation. - * - * @param data type for {@code backprops} output */ @OpMetadata( opType = LeakyReluGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionsDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionsDataset.java index 596ed69844b..529b1b93eaa 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionsDataset.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/OptionsDataset.java @@ -153,7 +153,7 @@ public static class Inputs extends RawOpInputs { public final Operand inputDataset; /** - * A `tf.string` scalar `tf.Tensor` of serialized `tf.data.Options` protocol buffer. + * A {@code tf.string} scalar {@code tf.Tensor} of serialized {@code tf.data.Options} protocol buffer. */ public final String serializedOptions; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelFilterDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelFilterDataset.java index 5dece763295..f87d2a27269 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelFilterDataset.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelFilterDataset.java @@ -219,8 +219,8 @@ public static class Inputs extends RawOpInputs { * A string indicating the op-level determinism to use. Deterministic controls * whether the interleave is allowed to return elements out of order if the next * element to be returned isn't available, but a later element is. Options are - * "true", "false", and "default". "default" indicates that determinism should be - * decided by the `experimental_deterministic` parameter of `tf.data.Options`. + * "true", "false", and "default". "default" indicates that determinism should be + * decided by the {@code experimental_deterministic} parameter of {@code tf.data.Options}. */ public final String deterministic; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelInterleaveDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelInterleaveDataset.java index 17ae267ff18..d46fd839fc4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelInterleaveDataset.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParallelInterleaveDataset.java @@ -265,13 +265,13 @@ public static class Inputs extends RawOpInputs { * A string indicating the op-level determinism to use. Deterministic controls * whether the interleave is allowed to return elements out of order if the next * element to be returned isn't available, but a later element is. Options are - * "true", "false", and "default". "default" indicates that determinism should be - * decided by the `experimental_deterministic` parameter of `tf.data.Options`. + * "true", "false", and "default". "default" indicates that determinism should be + * decided by the {@code experimental_deterministic} parameter of {@code tf.data.Options}. */ public final String deterministic; /** - * Types of the elements of `other_arguments`. + * Types of the elements of {@code other_arguments}. */ public final DataType[] Targuments; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParseExampleDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParseExampleDataset.java index 64662ec8ce3..c50ec51e906 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParseExampleDataset.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/ParseExampleDataset.java @@ -268,7 +268,7 @@ public static class Inputs extends RawOpInputs { /** * A list of string keys in the examples features. - * The results for these keys will be returned as `SparseTensor` objects. + * The results for these keys will be returned as {@code SparseTensor} objects. */ public final String[] sparseKeys; @@ -279,23 +279,23 @@ public static class Inputs extends RawOpInputs { public final String[] denseKeys; /** - * A list of `DTypes` of the same length as `sparse_keys`. - * Only `tf.float32` (`FloatList`), `tf.int64` (`Int64List`), - * and `tf.string` (`BytesList`) are supported. + * A list of {@code DTypes} of the same length as {@code sparse_keys}. + * Only {@code tf.float32} ({@code FloatList}), {@code tf.int64} ({@code Int64List}), + * and {@code tf.string} ({@code BytesList}) are supported. */ public final DataType[] sparseTypes; /** - * A list of DTypes of the same length as `dense_keys`. - * Only `tf.float32` (`FloatList`), `tf.int64` (`Int64List`), - * and `tf.string` (`BytesList`) are supported. + * A list of DTypes of the same length as {@code dense_keys}. + * Only {@code tf.float32} ({@code FloatList}), {@code tf.int64} ({@code Int64List}), + * and {@code tf.string} ({@code BytesList}) are supported. */ public final DataType[] Tdense; /** - * List of tuples with the same length as `dense_keys`. - * The shape of the data for each dense feature referenced by `dense_keys`. - * Required for any input tensors identified by `dense_keys`. Must be + * List of tuples with the same length as {@code dense_keys}. + * The shape of the data for each dense feature referenced by {@code dense_keys}. + * Required for any input tensors identified by {@code dense_keys}. Must be * either fully defined, or may contain an unknown first dimension. * An unknown first dimension means the feature is treated as having * a variable number of blocks, and the output shape along this dimension @@ -319,8 +319,8 @@ public static class Inputs extends RawOpInputs { * A string indicating the op-level determinism to use. Deterministic controls * whether the dataset is allowed to return elements out of order if the next * element to be returned isn't available, but a later element is. Options are - * "true", "false", and "default". "default" indicates that determinism should be - * decided by the `experimental_deterministic` parameter of `tf.data.Options`. + * "true", "false", and "default". "default" indicates that determinism should be + * decided by the {@code experimental_deterministic} parameter of {@code tf.data.Options}. */ public final String deterministic; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParseExampleDataset.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParseExampleDataset.java index 9ba31aa0995..28c138c0032 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParseExampleDataset.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/data/experimental/ParseExampleDataset.java @@ -202,7 +202,7 @@ public static class Inputs extends RawOpInputs { /** * A list of string keys in the examples features. - * The results for these keys will be returned as `SparseTensor` objects. + * The results for these keys will be returned as {@code SparseTensor} objects. */ public final String[] sparseKeys; @@ -213,23 +213,23 @@ public static class Inputs extends RawOpInputs { public final String[] denseKeys; /** - * A list of `DTypes` of the same length as `sparse_keys`. - * Only `tf.float32` (`FloatList`), `tf.int64` (`Int64List`), - * and `tf.string` (`BytesList`) are supported. + * A list of {@code DTypes} of the same length as {@code sparse_keys}. + * Only {@code tf.float32} ({@code FloatList}), {@code tf.int64} ({@code Int64List}), + * and {@code tf.string} ({@code BytesList}) are supported. */ public final DataType[] sparseTypes; /** - * A list of DTypes of the same length as `dense_keys`. - * Only `tf.float32` (`FloatList`), `tf.int64` (`Int64List`), - * and `tf.string` (`BytesList`) are supported. + * A list of DTypes of the same length as {@code dense_keys}. + * Only {@code tf.float32} ({@code FloatList}), {@code tf.int64} ({@code Int64List}), + * and {@code tf.string} ({@code BytesList}) are supported. */ public final DataType[] Tdense; /** - * List of tuples with the same length as `dense_keys`. - * The shape of the data for each dense feature referenced by `dense_keys`. - * Required for any input tensors identified by `dense_keys`. Must be + * List of tuples with the same length as {@code dense_keys}. + * The shape of the data for each dense feature referenced by {@code dense_keys}. + * Required for any input tensors identified by {@code dense_keys}. Must be * either fully defined, or may contain an unknown first dimension. * An unknown first dimension means the feature is treated as having * a variable number of blocks, and the output shape along this dimension diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java index d1aae3e74ad..86215fa9a9c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/CheckNumerics.java @@ -39,8 +39,6 @@ * that are not a number (NaN) or infinity (Inf). Otherwise, returns the input * tensor. Unlike CheckNumerics (V1), CheckNumericsV2 distinguishes -Inf and +Inf * in the errors it throws. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CheckNumerics.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientIdentity.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientIdentity.java index 37f2fec7d91..776a971ef27 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientIdentity.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientIdentity.java @@ -37,8 +37,6 @@ * This op is hidden from public in Python. It is used by TensorFlow Debugger to * register gradient tensors for gradient debugging. * This op operates on non-reference-type tensors. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DebugGradientIdentity.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientRefIdentity.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientRefIdentity.java index 5071299a66a..76a9e9029ca 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientRefIdentity.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugGradientRefIdentity.java @@ -37,8 +37,6 @@ * This op is hidden from public in Python. It is used by TensorFlow Debugger to * register gradient tensors for gradient debugging. * This op operates on reference-type tensors. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DebugGradientRefIdentity.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugIdentity.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugIdentity.java index 89854abdc1d..10edd71d4b1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugIdentity.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugIdentity.java @@ -36,8 +36,6 @@ /** * Provides an identity mapping of the non-Ref type input tensor for debugging. * Provides an identity mapping of the non-Ref type input tensor for debugging. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DebugIdentity.OP_NAME, @@ -364,17 +362,17 @@ public static class Inputs extends RawOpInputs /** * List of URLs to debug targets, e.g., - * file:///foo/tfdbg_dump, grpc:://localhost:11011 + * file:///foo/tfdbg_dump, grpc:://localhost:11011 */ public final String[] debugUrls; /** * Whether this op will be gated. If any of the debug_urls of this - * debug node is of the grpc:// scheme, when the value of this attribute is set - * to True, the data will not actually be sent via the grpc stream unless this - * debug op has been enabled at the debug_url. If all of the debug_urls of this - * debug node are of the grpc:// scheme and the debug op is enabled at none of - * them, the output will be an empty Tensor. + * debug node is of the grpc:// scheme, when the value of this attribute is set + * to True, the data will not actually be sent via the grpc stream unless this + * debug op has been enabled at the debug_url. If all of the debug_urls of this + * debug node are of the grpc:// scheme and the debug op is enabled at none of + * them, the output will be an empty Tensor. */ public final boolean gatedGrpc; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNanCount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNanCount.java index 4bc52436f35..2d0e2f5fe94 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNanCount.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNanCount.java @@ -269,17 +269,17 @@ public static class Inputs extends RawOpInputs { /** * List of URLs to debug targets, e.g., - * file:///foo/tfdbg_dump, grpc:://localhost:11011. + * file:///foo/tfdbg_dump, grpc:://localhost:11011. */ public final String[] debugUrls; /** - * Whether this op will be gated. If any of the debug_urls of this - * debug node is of the grpc:// scheme, when the value of this attribute is set - * to True, the data will not actually be sent via the grpc stream unless this - * debug op has been enabled at the debug_url. If all of the debug_urls of this - * debug node are of the grpc:// scheme and the debug op is enabled at none of - * them, the output will be an empty Tensor. + * Whether this op will be gated. If any of the debug_urls of this + * debug node is of the grpc:// scheme, when the value of this attribute is set + * to True, the data will not actually be sent via the grpc stream unless this + * debug op has been enabled at the debug_url. If all of the debug_urls of this + * debug node are of the grpc:// scheme and the debug op is enabled at none of + * them, the output will be an empty Tensor. */ public final boolean gatedGrpc; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java index 416438128d2..4ff0f11c7bc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/debugging/DebugNumericsSummary.java @@ -40,8 +40,6 @@ * Computes a numeric summary of the input tensor. The shape of the output * depends on the tensor_debug_mode attribute. * This op is used internally by TensorFlow Debugger (tfdbg) v2. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DebugNumericsSummary.OP_NAME, @@ -291,59 +289,53 @@ public static class Inputs extends RawOpInputs> { /** * Tensor debug mode: the mode in which the input tensor is summarized - * by the op. See the TensorDebugMode enum in - * tensorflow/core/protobuf/debug_event.proto for details. - * - * Supported values: - * 2 (CURT_HEALTH): Output a float32/64 tensor of shape [2]. The 1st - * element is the tensor_id, if provided, and -1 otherwise. The 2nd - * element is a bit which is set to 1 if the input tensor has an - * infinity or nan value, or zero otherwise. - * - * 3 (CONCISE_HEALTH): Output a float32/64 tensor of shape [5]. The 1st - * element is the tensor_id, if provided, and -1 otherwise. The - * remaining four slots are the total number of elements, -infs, - * +infs, and nans in the input tensor respectively. - * - * 4 (FULL_HEALTH): Output a float32/64 tensor of shape [11]. The 1st - * element is the tensor_id, if provided, and -1 otherwise. The 2nd - * element is the device_id, if provided, and -1 otherwise. The 3rd - * element holds the datatype value of the input tensor as according - * to the enumerated type in tensorflow/core/framework/types.proto. - * The remaining elements hold the total number of elements, -infs, - * +infs, nans, negative finite numbers, zeros, and positive finite - * numbers in the input tensor respectively. - * - * 5 (SHAPE): Output a float32/64 tensor of shape [10]. The 1st - * element is the tensor_id, if provided, and -1 otherwise. The 2nd - * element holds the datatype value of the input tensor as according - * to the enumerated type in tensorflow/core/framework/types.proto. - * The 3rd element holds the rank of the tensor. The 4th element holds - * the number of elements within the tensor. Finally the remaining 6 - * elements hold the shape of the tensor. If the rank of the tensor - * is lower than 6, the shape is right padded with zeros. If the rank - * is greater than 6, the head of the shape is truncated. - * - * 6 (FULL_NUMERICS): Output a float32/64 tensor of shape [22]. The 1st - * element is the tensor_id, if provided, and -1 otherwise. The 2nd - * element is the device_id, if provided, and -1 otherwise. The 3rd - * element holds the datatype value of the input tensor as according - * to the enumerated type in tensorflow/core/framework/types.proto. - * The 4th element holds the rank of the tensor. The 5th to 11th - * elements hold the shape of the tensor. If the rank of the tensor - * is lower than 6, the shape is right padded with zeros. If the rank - * is greater than 6, the head of the shape is truncated. The 12th to - * 18th elements hold the number of elements, -infs, +infs, nans, - * denormal floats, negative finite numbers, zeros, and positive - * finite numbers in the input tensor respectively. The final four - * elements hold the min value, max value, mean, and variance of the - * input tensor. - * - * 8 (REDUCE_INF_NAN_THREE_SLOTS): Output a float32/64 tensor of shape - * [3]. The 1st element is -inf if any elements of the input tensor - * is -inf, or zero otherwise. The 2nd element is +inf if any elements - * of the input tensor is +inf, or zero otherwise. The 3rd element is - * nan if any element of the input tensor is nan, or zero otherwise. + * by the op. See the TensorDebugMode enum in + * tensorflow/core/protobuf/debug_event.proto for details. + *

    Supported values: + * 2 (CURT_HEALTH): Output a float32/64 tensor of shape [2]. The 1st + * element is the tensor_id, if provided, and -1 otherwise. The 2nd + * element is a bit which is set to 1 if the input tensor has an + * infinity or nan value, or zero otherwise. + *

    3 (CONCISE_HEALTH): Output a float32/64 tensor of shape [5]. The 1st + * element is the tensor_id, if provided, and -1 otherwise. The + * remaining four slots are the total number of elements, -infs, + * +infs, and nans in the input tensor respectively. + *

    4 (FULL_HEALTH): Output a float32/64 tensor of shape [11]. The 1st + * element is the tensor_id, if provided, and -1 otherwise. The 2nd + * element is the device_id, if provided, and -1 otherwise. The 3rd + * element holds the datatype value of the input tensor as according + * to the enumerated type in tensorflow/core/framework/types.proto. + * The remaining elements hold the total number of elements, -infs, + * +infs, nans, negative finite numbers, zeros, and positive finite + * numbers in the input tensor respectively. + *

    5 (SHAPE): Output a float32/64 tensor of shape [10]. The 1st + * element is the tensor_id, if provided, and -1 otherwise. The 2nd + * element holds the datatype value of the input tensor as according + * to the enumerated type in tensorflow/core/framework/types.proto. + * The 3rd element holds the rank of the tensor. The 4th element holds + * the number of elements within the tensor. Finally the remaining 6 + * elements hold the shape of the tensor. If the rank of the tensor + * is lower than 6, the shape is right padded with zeros. If the rank + * is greater than 6, the head of the shape is truncated. + *

    6 (FULL_NUMERICS): Output a float32/64 tensor of shape [22]. The 1st + * element is the tensor_id, if provided, and -1 otherwise. The 2nd + * element is the device_id, if provided, and -1 otherwise. The 3rd + * element holds the datatype value of the input tensor as according + * to the enumerated type in tensorflow/core/framework/types.proto. + * The 4th element holds the rank of the tensor. The 5th to 11th + * elements hold the shape of the tensor. If the rank of the tensor + * is lower than 6, the shape is right padded with zeros. If the rank + * is greater than 6, the head of the shape is truncated. The 12th to + * 18th elements hold the number of elements, -infs, +infs, nans, + * denormal floats, negative finite numbers, zeros, and positive + * finite numbers in the input tensor respectively. The final four + * elements hold the min value, max value, mean, and variance of the + * input tensor. + *

    8 (REDUCE_INF_NAN_THREE_SLOTS): Output a float32/64 tensor of shape + * [3]. The 1st element is -inf if any elements of the input tensor + * is -inf, or zero otherwise. The 2nd element is +inf if any elements + * of the input tensor is +inf, or zero otherwise. The 3rd element is + * nan if any element of the input tensor is nan, or zero otherwise. */ public final long tensorDebugMode; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclAllReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclAllReduce.java index c5416746198..7cc17dd9d36 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclAllReduce.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclAllReduce.java @@ -45,8 +45,6 @@ * reduction: the reduction operation to perform. * num_devices: The number of devices participating in this reduction. * shared_name: Identifier that shared between ops of the same reduction. - * - * @param data type for {@code data} output */ @OpMetadata( opType = NcclAllReduce.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclBroadcast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclBroadcast.java index 3824d6a10dd..41a2050e44f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclBroadcast.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclBroadcast.java @@ -42,8 +42,6 @@ *

    input: The input to the broadcast. * output: The same as input. * shape: The shape of the input tensor. - * - * @param data type for {@code output} output */ @OpMetadata( opType = NcclBroadcast.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclReduce.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclReduce.java index 2a80593be6c..8fcf62bf4cc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclReduce.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/distribute/NcclReduce.java @@ -42,8 +42,6 @@ *

    input: The input to the reduction. * data: the value of the reduction across all {@code num_devices} devices. * reduction: the reduction operation to perform. - * - * @param data type for {@code data} output */ @OpMetadata( opType = NcclReduce.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/AsString.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/AsString.java index 77ba7493eb7..1f9b0285c6c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/AsString.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/AsString.java @@ -272,7 +272,7 @@ public static class Inputs extends RawOpInputs { /** * The post-decimal precision to use for floating point numbers. - * Only used if precision > -1. + * Only used if precision > -1. */ public final long precision; @@ -290,12 +290,12 @@ public static class Inputs extends RawOpInputs { /** * Pad pre-decimal numbers to this width. * Applies to both floating point and integer numbers. - * Only used if width > -1. + * Only used if width > -1. */ public final long width; /** - * The value to pad if width > -1. If empty, pads with spaces. + * The value to pad if width > -1. If empty, pads with spaces. * Another typical value is '0'. String cannot be longer than 1 character. */ public final String fill; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java index 806ad99e2ea..af516490d88 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Cast.java @@ -36,8 +36,6 @@ /** * Cast x of type SrcT to y of DstT. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Cast.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java index 6b0a717157c..0da2678549f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/dtypes/Complex.java @@ -48,8 +48,6 @@ * # tensor `imag` is [4.75, 5.75] * tf.complex(real, imag) ==> [[2.25 + 4.75j], [3.25 + 5.75j]] * - * - * @param data type for {@code out} output */ @OpMetadata( opType = Complex.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java index 0a6a141c036..123c74afd50 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustContrast.java @@ -43,8 +43,6 @@ *

    For each channel, the Op first computes the mean of the image pixels in the * channel and then adjusts each component of each pixel to * {@code (x - mean) * contrast_factor + mean}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = AdjustContrast.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java index 45fe50175c4..b0001085638 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustHue.java @@ -41,8 +41,6 @@ *

    The input image is considered in the RGB colorspace. Conceptually, the RGB * colors are first mapped into HSV. A delta is then applied all the hue values, * and then remapped back to RGB colorspace. - * - * @param data type for {@code output} output */ @OpMetadata( opType = AdjustHue.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java index a7fea42d8fb..5f0c063dc1d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/AdjustSaturation.java @@ -41,8 +41,6 @@ *

    The input image is considered in the RGB colorspace. Conceptually, the RGB * colors are first mapped into HSV. A scale is then applied all the saturation * values, and then remapped back to RGB colorspace. - * - * @param data type for {@code output} output */ @OpMetadata( opType = AdjustSaturation.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CombinedNonMaxSuppression.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CombinedNonMaxSuppression.java index 3f0811e69cc..d3dff6d2a2a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CombinedNonMaxSuppression.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CombinedNonMaxSuppression.java @@ -278,10 +278,10 @@ public static class Inputs extends RawOpInputs { /** * If false, the output nmsed boxes, scores and classes - * are padded/clipped to `max_total_size`. If true, the + * are padded/clipped to {@code max_total_size}. If true, the * output nmsed boxes, scores and classes are padded to be of length - * `max_size_per_class`*`num_classes`, unless it exceeds `max_total_size` in - * which case it is clipped to `max_total_size`. Defaults to false. + * {@code max_size_per_class}*{@code num_classes}, unless it exceeds {@code max_total_size} in + * which case it is clipped to {@code max_total_size}. Defaults to false. */ public final boolean padPerClass; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResize.java index 371015feb31..68289e7cdb3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResize.java @@ -239,7 +239,7 @@ public static class Inputs extends RawOpInputs { /** * A string specifying the sampling method for resizing. It can be either - * `"bilinear"` or `"nearest"` and default to `"bilinear"`. Currently two sampling + * {@code "bilinear"} or {@code "nearest"} and default to {@code "bilinear"}. Currently two sampling * methods are supported: Bilinear and Nearest Neighbor. */ public final String method; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java index 59e98a3252d..e639b0f2cb7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/CropAndResizeGradImage.java @@ -38,8 +38,6 @@ /** * Computes the gradient of the crop_and_resize op wrt the input image tensor. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CropAndResizeGradImage.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeAndCropJpeg.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeAndCropJpeg.java index dbc4a9e33b3..9cf114193b3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeAndCropJpeg.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeAndCropJpeg.java @@ -332,9 +332,9 @@ public static class Inputs extends RawOpInputs { /** * string specifying a hint about the algorithm used for - * decompression. Defaults to "" which maps to a system-specific - * default. Currently valid values are ["INTEGER_FAST", - * "INTEGER_ACCURATE"]. The hint may be ignored (e.g., the internal + * decompression. Defaults to "" which maps to a system-specific + * default. Currently valid values are ["INTEGER_FAST", + * "INTEGER_ACCURATE"]. The hint may be ignored (e.g., the internal * jpeg library changes to a version that does not have that specific * option.) */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java index ae91e89973a..a5c7ee7845e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeImage.java @@ -53,8 +53,6 @@ * unoccupied areas (in the first frame) with zeros (black). For frames after the * first frame that does not occupy the entire canvas, it uses the previous * frame to fill the unoccupied areas. - * - * @param data type for {@code image} output */ @OpMetadata( opType = DecodeImage.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeJpeg.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeJpeg.java index a6c1f60fc24..4deb6ce61e7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeJpeg.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodeJpeg.java @@ -323,9 +323,9 @@ public static class Inputs extends RawOpInputs { /** * string specifying a hint about the algorithm used for - * decompression. Defaults to "" which maps to a system-specific - * default. Currently valid values are ["INTEGER_FAST", - * "INTEGER_ACCURATE"]. The hint may be ignored (e.g., the internal + * decompression. Defaults to "" which maps to a system-specific + * default. Currently valid values are ["INTEGER_FAST", + * "INTEGER_ACCURATE"]. The hint may be ignored (e.g., the internal * jpeg library changes to a version that does not have that specific * option.) */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java index db44c3b3146..dd6384caf7c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DecodePng.java @@ -51,8 +51,6 @@ * of color channels. *

    This op also supports decoding JPEGs and non-animated GIFs since the interface * is the same, though it is cleaner to use {@code tf.io.decode_image}. - * - * @param data type for {@code image} output */ @OpMetadata( opType = DecodePng.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java index 8033cecb4c9..56c64a5e50c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/DrawBoundingBoxes.java @@ -45,8 +45,6 @@ * box is {@code [0.1, 0.2, 0.5, 0.9]}, the upper-left and bottom-right coordinates of * the bounding box will be {@code (40, 10)} to {@code (100, 50)} (in (x,y) coordinates). *

    Parts of the bounding box may fall outside the image. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DrawBoundingBoxes.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodeJpeg.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodeJpeg.java index 6f3468d21d0..7ff1e224e6a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodeJpeg.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/EncodeJpeg.java @@ -387,8 +387,8 @@ public static class Inputs extends RawOpInputs { public final boolean chromaDownsampling; /** - * Unit used to specify `x_density` and `y_density`: - * pixels per inch (`'in'`) or centimeter (`'cm'`). + * Unit used to specify {@code x_density} and {@code y_density}: + * pixels per inch ({@code 'in'}) or centimeter ({@code 'cm'}). */ public final String densityUnit; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractGlimpse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractGlimpse.java index ee24391b920..44daff67647 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractGlimpse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractGlimpse.java @@ -285,9 +285,9 @@ public static class Inputs extends RawOpInputs { public final boolean uniformNoise; /** - * indicates if the noise should `uniform`, `gaussian`, or - * `zero`. The default is `uniform` which means the noise type - * will be decided by `uniform_noise`. + * indicates if the noise should {@code uniform}, {@code gaussian}, or + * {@code zero}. The default is {@code uniform} which means the noise type + * will be decided by {@code uniform_noise}. */ public final String noise; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractImagePatches.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractImagePatches.java index 375abcd8371..54395a44acc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractImagePatches.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractImagePatches.java @@ -36,8 +36,6 @@ /** * Extract {@code patches} from {@code images} and put them in the "depth" output dimension. - * - * @param data type for {@code patches} output */ @OpMetadata( opType = ExtractImagePatches.OP_NAME, @@ -130,23 +128,23 @@ public static class Inputs extends RawOpInputs images; /** - * The size of the sliding window for each dimension of `images`. + * The size of the sliding window for each dimension of {@code images}. */ public final long[] ksizes; /** * How far the centers of two consecutive patches are in - * the images. Must be: `[1, stride_rows, stride_cols, 1]`. + * the images. Must be: {@code [1, stride_rows, stride_cols, 1]}. */ public final long[] strides; /** - * Must be: `[1, rate_rows, rate_cols, 1]`. This is the + * Must be: {@code [1, rate_rows, rate_cols, 1]}. This is the * input stride, specifying how far two consecutive patch samples are in the * input. Equivalent to extracting patches with - * `patch_sizes_eff = patch_sizes + (patch_sizes - 1) * (rates - 1)`, followed by - * subsampling them spatially by a factor of `rates`. This is equivalent to - * `rate` in dilated (a.k.a. Atrous) convolutions. + * {@code patch_sizes_eff = patch_sizes + (patch_sizes - 1) * (rates - 1)}, followed by + * subsampling them spatially by a factor of {@code rates}. This is equivalent to + * {@code rate} in dilated (a.k.a. Atrous) convolutions. */ public final long[] rates; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java index 368fe5cfd02..4ca887e7e72 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ExtractJpegShape.java @@ -39,8 +39,6 @@ /** * Extract the shape information of a JPEG-encoded image. * This op only parses the image header, so it is much faster than DecodeJpeg. - * - * @param data type for {@code image_shape} output */ @OpMetadata( opType = ExtractJpegShape.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java index 6e32b95ca11..abd3d53d884 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/HsvToRgb.java @@ -39,8 +39,6 @@ * value of the pixels. The output is only well defined if the value in {@code images} * are in {@code [0,1]}. *

    See {@code rgb_to_hsv} for a description of the HSV encoding. - * - * @param data type for {@code output} output */ @OpMetadata( opType = HsvToRgb.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java index f18c2ebd219..cef590ad519 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ImageProjectiveTransformV2.java @@ -42,8 +42,6 @@ * {@code (x', y') = ((a0 x + a1 y + a2) / k, (b0 x + b1 y + b2) / k)}, where * {@code k = c0 x + c1 y + 1}. If the transformed point lays outside of the input * image, the output pixel is set to 0. - * - * @param data type for {@code transformed_images} output */ @OpMetadata( opType = ImageProjectiveTransformV2.OP_NAME, @@ -174,12 +172,12 @@ public static class Inputs extends RawOpInputs data type for {@code transformed_images} output */ @OpMetadata( opType = ImageProjectiveTransformV3.OP_NAME, @@ -181,12 +179,12 @@ public static class Inputs extends RawOpInputs data type for {@code selected_scores} output */ @OpMetadata( opType = NonMaxSuppression.OP_NAME, @@ -242,8 +240,8 @@ public static class Inputs extends RawOpInputs data type for {@code resized_images} output */ @OpMetadata( opType = QuantizedResizeBilinear.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java index 966401d271c..063b7b8f529 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RandomCrop.java @@ -41,8 +41,6 @@ *

    This Op picks a random location in {@code image} and crops a {@code height} by {@code width} * rectangle from that location. The random location is picked so the cropped * area will fit inside the original image. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomCrop.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java index 16d5af61802..c04fe6d13e0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBicubicGrad.java @@ -36,8 +36,6 @@ /** * Computes the gradient of bicubic interpolation. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ResizeBicubicGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java index dbd172bfbf2..166d6b46de6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeBilinearGrad.java @@ -36,8 +36,6 @@ /** * Computes the gradient of bilinear interpolation. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ResizeBilinearGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java index 1fc40174782..355ac564de1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighbor.java @@ -36,8 +36,6 @@ /** * Resize {@code images} to {@code size} using nearest neighbor interpolation. - * - * @param data type for {@code resized_images} output */ @OpMetadata( opType = ResizeNearestNeighbor.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java index 485aa4ba63b..36df9e12b2d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/ResizeNearestNeighborGrad.java @@ -36,8 +36,6 @@ /** * Computes the gradient of nearest neighbor interpolation. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ResizeNearestNeighborGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java index 3709f0bd4f7..be3c84d9b66 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/RgbToHsv.java @@ -56,8 +56,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = RgbToHsv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java index f19ccb004e2..a7378278309 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/SampleDistortedBoundingBox.java @@ -70,8 +70,6 @@ * {@code use_image_if_no_bounding_boxes = true} will assume there is a single implicit * bounding box covering the whole image. If {@code use_image_if_no_bounding_boxes} is * false and no bounding boxes are supplied, an error is raised. - * - * @param data type for {@code begin} output */ @OpMetadata( opType = SampleDistortedBoundingBox.OP_NAME, @@ -425,8 +423,8 @@ public static class Inputs extends RawOpInputs extends RawOpInputs data type for {@code output} output */ @OpMetadata( opType = ScaleAndTranslateGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/StatelessSampleDistortedBoundingBox.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/StatelessSampleDistortedBoundingBox.java index 49955247c14..31c4de5388d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/StatelessSampleDistortedBoundingBox.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/image/StatelessSampleDistortedBoundingBox.java @@ -95,8 +95,6 @@ * {@code use_image_if_no_bounding_boxes = true} will assume there is a single implicit * bounding box covering the whole image. If {@code use_image_if_no_bounding_boxes} is * false and no bounding boxes are supplied, an error is raised. - * - * @param data type for {@code begin} output */ @OpMetadata( opType = StatelessSampleDistortedBoundingBox.OP_NAME, @@ -421,7 +419,7 @@ public static class Inputs extends RawOpInputs { /** * A scalar containing either (i) the empty string (no - * compression), (ii) "ZLIB", or (iii) "GZIP". + * compression), (ii) "ZLIB", or (iii) "GZIP". */ public final String compressionType; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java index 90a8b357b66..07eac6679d4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodePaddedRaw.java @@ -38,8 +38,6 @@ /** * Reinterpret the bytes of a string as a vector of numbers. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DecodePaddedRaw.OP_NAME, @@ -164,8 +162,8 @@ public static class Inputs extends RawOpInputs> { public final DataType outType; /** - * Whether the input `input_bytes` is in little-endian order. Ignored for - * `out_type` values that are stored in a single byte, like `uint8` + * Whether the input {@code input_bytes} is in little-endian order. Ignored for + * {@code out_type} values that are stored in a single byte, like {@code uint8} */ public final boolean littleEndian; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java index f1405659a91..217c843796f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DecodeRaw.java @@ -37,8 +37,6 @@ /** * Reinterpret the bytes of a string as a vector of numbers. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DecodeRaw.OP_NAME, @@ -155,9 +153,9 @@ public static class Inputs extends RawOpInputs> { public final DataType outType; /** - * Whether the input `bytes` are in little-endian order. - * Ignored for `out_type` values that are stored in a single byte like - * `uint8`. + * Whether the input {@code bytes} are in little-endian order. + * Ignored for {@code out_type} values that are stored in a single byte like + * {@code uint8}. */ public final boolean littleEndian; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java index d86def49dd2..9704bd78d15 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/DeserializeManySparse.java @@ -77,8 +77,6 @@ * values = [1, 2, 3, 4, 5] * shape = [2 50] * - * - * @param data type for {@code sparse_values} output */ @OpMetadata( opType = DeserializeManySparse.OP_NAME, @@ -166,7 +164,7 @@ public static class Inputs extends RawOpInputs> { public final Operand serializedSparse; /** - * The `dtype` of the serialized `SparseTensor` objects. + * The {@code dtype} of the serialized {@code SparseTensor} objects. */ public final DataType dtype; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseExample.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseExample.java index 6104c068643..624d698e828 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseExample.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseExample.java @@ -286,7 +286,7 @@ public static class Inputs extends RawOpInputs { public final DataType[] Tdense; /** - * A list of `num_sparse` types; the data types of data in each Feature + * A list of {@code num_sparse} types; the data types of data in each Feature * given in sparse_keys. * Currently the ParseExample supports DT_FLOAT (FloatList), * DT_INT64 (Int64List), and DT_STRING (BytesList). @@ -294,23 +294,23 @@ public static class Inputs extends RawOpInputs { public final DataType[] sparseTypes; /** - * A list of `num_ragged` types; the data types of data in each Feature - * given in ragged_keys (where `num_ragged = sparse_keys.size()`). + * A list of {@code num_ragged} types; the data types of data in each Feature + * given in ragged_keys (where {@code num_ragged = sparse_keys.size()}). * Currently the ParseExample supports DT_FLOAT (FloatList), * DT_INT64 (Int64List), and DT_STRING (BytesList). */ public final DataType[] raggedValueTypes; /** - * A list of `num_ragged` types; the data types of row_splits in each Feature - * given in ragged_keys (where `num_ragged = sparse_keys.size()`). + * A list of {@code num_ragged} types; the data types of row_splits in each Feature + * given in ragged_keys (where {@code num_ragged = sparse_keys.size()}). * May be DT_INT32 or DT_INT64. */ public final DataType[] raggedSplitTypes; /** - * A list of `num_dense` shapes; the shapes of data in each Feature - * given in dense_keys (where `num_dense = dense_keys.size()`). + * A list of {@code num_dense} shapes; the shapes of data in each Feature + * given in dense_keys (where {@code num_dense = dense_keys.size()}). * The number of elements in the Feature corresponding to dense_key[j] * must always equal dense_shapes[j].NumEntries(). * If dense_shapes[j] == (D0, D1, ..., DN) then the shape of output diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleExample.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleExample.java index cf9588ddf89..ace0959c7ad 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleExample.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseSingleExample.java @@ -205,7 +205,7 @@ public static class Inputs extends RawOpInputs { public final Iterable> denseDefaults; /** - * A list of `num_sparse` strings. + * A list of {@code num_sparse} strings. * The keys expected in the Examples' features associated with sparse values. */ public final String[] sparseKeys; @@ -217,7 +217,7 @@ public static class Inputs extends RawOpInputs { public final String[] denseKeys; /** - * A list of `num_sparse` types; the data types of data in each + * A list of {@code num_sparse} types; the data types of data in each * Feature given in sparse_keys. * Currently the ParseSingleExample op supports DT_FLOAT (FloatList), * DT_INT64 (Int64List), and DT_STRING (BytesList). @@ -226,7 +226,7 @@ public static class Inputs extends RawOpInputs { /** * The data types of data in each Feature given in dense_keys. - * The length of this list must match the length of `dense_keys`. + * The length of this list must match the length of {@code dense_keys}. * Currently the ParseSingleExample op supports DT_FLOAT (FloatList), * DT_INT64 (Int64List), and DT_STRING (BytesList). */ @@ -234,7 +234,7 @@ public static class Inputs extends RawOpInputs { /** * The shapes of data in each Feature given in dense_keys. - * The length of this list must match the length of `dense_keys`. The + * The length of this list must match the length of {@code dense_keys}. The * number of elements in the Feature corresponding to dense_key[j] must * always equal dense_shapes[j].NumEntries(). If dense_shapes[j] == * (D0, D1, ..., DN) then the shape of output Tensor dense_values[j] diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java index 66a64b13c0b..039ff1546f0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/ParseTensor.java @@ -37,8 +37,6 @@ /** * Transforms a serialized tensorflow.TensorProto proto into a Tensor. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ParseTensor.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java index 253662f2cec..70f9327d112 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeManySparse.java @@ -44,8 +44,6 @@ * {@code SparseTensor} objects going into each row of {@code serialized_sparse} will have * rank {@code R-1}. *

    The minibatch size {@code N} is extracted from {@code sparse_shape[0]}. - * - * @param data type for {@code serialized_sparse} output */ @OpMetadata( opType = SerializeManySparse.OP_NAME, @@ -150,8 +148,8 @@ public static class Inputs extends RawOpInputs> { public final DataType T; /** - * The `dtype` to use for serialization; the supported types are `string` - * (default) and `variant`. + * The {@code dtype} to use for serialization; the supported types are {@code string} + * (default) and {@code variant}. */ public final DataType outType; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java index 500b0e055d5..b0c2b5935bf 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/io/SerializeSparse.java @@ -38,8 +38,6 @@ /** * Serialize a {@code SparseTensor} into a {@code [3]} {@code Tensor} object. - * - * @param data type for {@code serialized_sparse} output */ @OpMetadata( opType = SerializeSparse.OP_NAME, @@ -144,8 +142,8 @@ public static class Inputs extends RawOpInputs> { public final DataType T; /** - * The `dtype` to use for serialization; the supported types are `string` - * (default) and `variant`. + * The {@code dtype} to use for serialization; the supported types are {@code string} + * (default) and {@code variant}. */ public final DataType outType; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandPart.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandPart.java index 34f179ed2b0..a521e77b040 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandPart.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandPart.java @@ -65,8 +65,6 @@ * tf.linalg.band_part(input, -1, 0) ==> Lower triangular part. * tf.linalg.band_part(input, 0, 0) ==> Diagonal. * - * - * @param data type for {@code band} output */ @OpMetadata( opType = BandPart.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandedTriangularSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandedTriangularSolve.java index 9dc6dba4348..532d4fe148b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandedTriangularSolve.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BandedTriangularSolve.java @@ -35,8 +35,6 @@ /** * The BandedTriangularSolve operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BandedTriangularSolve.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java index 0016839b211..b43cf15b48e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholesky.java @@ -35,8 +35,6 @@ /** * The BatchCholesky operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchCholesky.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java index d9ce332f7e2..5e917e740b8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchCholeskyGrad.java @@ -35,8 +35,6 @@ /** * The BatchCholeskyGrad operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchCholeskyGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixBandPart.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixBandPart.java index 55e8a0d6a75..99cb57ff97f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixBandPart.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixBandPart.java @@ -36,8 +36,6 @@ /** * The BatchMatrixBandPart operation - * - * @param data type for {@code band} output */ @OpMetadata( opType = BatchMatrixBandPart.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDeterminant.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDeterminant.java index c50a706e073..7f1bd32a749 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDeterminant.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDeterminant.java @@ -35,8 +35,6 @@ /** * The BatchMatrixDeterminant operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchMatrixDeterminant.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiag.java index bba3cae6292..edc731b1f36 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiag.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiag.java @@ -35,8 +35,6 @@ /** * The BatchMatrixDiag operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchMatrixDiag.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiagPart.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiagPart.java index 63e7e0e3026..ac379b960aa 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiagPart.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixDiagPart.java @@ -35,8 +35,6 @@ /** * The BatchMatrixDiagPart operation - * - * @param data type for {@code diagonal} output */ @OpMetadata( opType = BatchMatrixDiagPart.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java index 081dab67e8b..5ecaf005f3d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixInverse.java @@ -35,8 +35,6 @@ /** * The BatchMatrixInverse operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchMatrixInverse.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSetDiag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSetDiag.java index 67a97a485c0..eaea0c7db31 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSetDiag.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSetDiag.java @@ -35,8 +35,6 @@ /** * The BatchMatrixSetDiag operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchMatrixSetDiag.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java index dc65bb1dce1..5b6749c53e4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolve.java @@ -35,8 +35,6 @@ /** * The BatchMatrixSolve operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchMatrixSolve.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java index 801c5262946..7cb6714696f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixSolveLs.java @@ -36,8 +36,6 @@ /** * The BatchMatrixSolveLs operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchMatrixSolveLs.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java index ae63e405dd7..d7b326bae21 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchMatrixTriangularSolve.java @@ -35,8 +35,6 @@ /** * The BatchMatrixTriangularSolve operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchMatrixTriangularSolve.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java index 1d6588ac785..637625bd5db 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSelfAdjointEig.java @@ -35,8 +35,6 @@ /** * The BatchSelfAdjointEigV2 operation - * - * @param data type for {@code e} output */ @OpMetadata( opType = BatchSelfAdjointEig.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSvd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSvd.java index cf723ceeedc..a2411601e63 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSvd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/BatchSvd.java @@ -35,8 +35,6 @@ /** * The BatchSvd operation - * - * @param data type for {@code s} output */ @OpMetadata( opType = BatchSvd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cholesky.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cholesky.java index 294a41889da..ef6d0ca1a3d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cholesky.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cholesky.java @@ -45,8 +45,6 @@ *

    Note: The gradient computation on GPU is faster for large matrices but * not for large batch dimensions when the submatrices are small. In this * case it might be faster to use the CPU. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Cholesky.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java index f2529b61318..ce7975bbb29 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/CholeskyGrad.java @@ -37,8 +37,6 @@ * Computes the reverse mode backpropagated gradient of the Cholesky algorithm. * For an explanation see "Differentiation of the Cholesky algorithm" by * Iain Murray http://arxiv.org/abs/1602.07527. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CholeskyGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/ConjugateTranspose.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/ConjugateTranspose.java index e14f2e71ef9..561e4fecbf1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/ConjugateTranspose.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/ConjugateTranspose.java @@ -39,8 +39,6 @@ * The output {@code y} has the same rank as {@code x}. The shapes of {@code x} and {@code y} satisfy: * {@code y.shape[i] == x.shape[perm[i]] for i in [0, 1, ..., rank(x) - 1]} * {@code y[i,j,k,...,s,t,u] == conj(x[perm[i], perm[j], perm[k],...,perm[s], perm[t], perm[u]])} - * - * @param data type for {@code y} output */ @OpMetadata( opType = ConjugateTranspose.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java index 68ee2a65439..5c942c1e41b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Cross.java @@ -38,8 +38,6 @@ * {@code a} and {@code b} must be the same shape; they can either be simple 3-element vectors, * or any shape where the innermost dimension is 3. In the latter case, each pair * of corresponding 3-element vectors is cross-multiplied independently. - * - * @param data type for {@code product} output */ @OpMetadata( opType = Cross.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Det.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Det.java index 62aafcde736..d63118c9f73 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Det.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Det.java @@ -38,8 +38,6 @@ * The input is a tensor of shape {@code [..., M, M]} whose inner-most 2 dimensions * form square matrices. The output is a tensor containing the determinants * for all input submatrices {@code [..., :, :]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Det.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java index fb820e00ddf..3276bbb78fe 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Eig.java @@ -46,8 +46,6 @@ * e, v = eig(a) * e = eig(a, compute_v=False) * - * - * @param data type for {@code e} output */ @OpMetadata( opType = Eig.OP_NAME, @@ -162,7 +160,7 @@ public static class Inputs extends RawOpInputs> { public final Operand input; /** - * If `True` then eigenvectors will be computed and returned in `v`. + * If {@code True} then eigenvectors will be computed and returned in {@code v}. * Otherwise, only the eigenvalues will be computed. */ public final boolean computeV; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Einsum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Einsum.java index 51d3eeb3fa6..5b57bad8aa4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Einsum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Einsum.java @@ -99,8 +99,6 @@ * supported by {@code numpy.einsum}. *
    {@literal @}end_compatibility * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Einsum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/EuclideanNorm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/EuclideanNorm.java index ab6f58f4885..f544381e1a7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/EuclideanNorm.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/EuclideanNorm.java @@ -40,8 +40,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = EuclideanNorm.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Inv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Inv.java index 6b02bc2a059..93338f1df07 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Inv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Inv.java @@ -42,8 +42,6 @@ *

    If a matrix is not invertible there is no guarantee what the op does. It * may detect the condition and raise an exception or it may simply return a * garbage result. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Inv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LogMatrixDeterminant.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LogMatrixDeterminant.java index 298e01306db..a144ac2d31c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LogMatrixDeterminant.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/LogMatrixDeterminant.java @@ -43,8 +43,6 @@ * The {@code log_abs_determinant} is computed as {@code det(P)*sum(log(diag(LU)))} where {@code LU} * is the {@code LU} decomposition of the input and {@code P} is the corresponding * permutation matrix. - * - * @param data type for {@code sign} output */ @OpMetadata( opType = LogMatrixDeterminant.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java index 480ed23e696..9063fab1875 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Lu.java @@ -51,10 +51,6 @@ *

    P represents a permutation matrix encoded as a list of indices each between {@code 0} * and {@code M-1}, inclusive. If P_mat denotes the permutation matrix corresponding to * P, then the L, U and P satisfies P_mat * input = L * U. - * - * @param data type for {@code lu} output - * - * @param data type for {@code p} output */ @OpMetadata( opType = Lu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatMul.java index a984a502a7a..c817cbc9037 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatMul.java @@ -41,8 +41,6 @@ * true). *

    Note: The default kernel implementation for MatMul on GPUs uses * cublas. - * - * @param data type for {@code product} output */ @OpMetadata( opType = MatMul.OP_NAME, @@ -231,12 +229,12 @@ public static class Inputs extends RawOpInputs> { public final Operand b; /** - * If true, "a" is transposed before multiplication. + * If true, "a" is transposed before multiplication. */ public final boolean transposeA; /** - * If true, "b" is transposed before multiplication. + * If true, "b" is transposed before multiplication. */ public final boolean transposeB; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiag.java index 0a292c9d1b1..5241708f71a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiag.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiag.java @@ -116,8 +116,6 @@ * [1, 9], * [9, 2]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = MatrixDiag.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPart.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPart.java index 084c946193e..a818b134cbe 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPart.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPart.java @@ -96,8 +96,6 @@ * [3, 4, 9], * [4, 3, 8]]] * - * - * @param data type for {@code diagonal} output */ @OpMetadata( opType = MatrixDiagPart.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPartV3.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPartV3.java index 931a277ad1a..c6ecab46bab 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPartV3.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixDiagPartV3.java @@ -126,8 +126,6 @@ * [4, 3, 8]]] * * - * - * @param data type for {@code diagonal} output */ @OpMetadata( opType = MatrixDiagPartV3.OP_NAME, @@ -270,12 +268,12 @@ public static class Inputs extends RawOpInputs - * - * @param data type for {@code output} output */ @OpMetadata( opType = MatrixDiagV3.OP_NAME, @@ -311,12 +309,12 @@ public static class Inputs extends RawOpInputs> public final DataType T; /** - * Some diagonals are shorter than `max_diag_len` and need to be padded. `align` is + * Some diagonals are shorter than {@code max_diag_len} and need to be padded. {@code align} is * a string specifying how superdiagonals and subdiagonals should be aligned, - * respectively. There are four possible alignments: "RIGHT_LEFT" (default), - * "LEFT_RIGHT", "LEFT_LEFT", and "RIGHT_RIGHT". "RIGHT_LEFT" aligns superdiagonals + * respectively. There are four possible alignments: "RIGHT_LEFT" (default), + * "LEFT_RIGHT", "LEFT_LEFT", and "RIGHT_RIGHT". "RIGHT_LEFT" aligns superdiagonals * to the right (left-pads the row) and subdiagonals to the left (right-pads the - * row). It is the packing format LAPACK uses. cuSPARSE uses "LEFT_RIGHT", which is + * row). It is the packing format LAPACK uses. cuSPARSE uses "LEFT_RIGHT", which is * the opposite alignment. */ public final String align; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixExponential.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixExponential.java index 961f57037f4..9332cd02b3e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixExponential.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixExponential.java @@ -35,8 +35,6 @@ /** * Deprecated, use python implementation tf.linalg.matrix_exponential. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MatrixExponential.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixLogarithm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixLogarithm.java index b3876d3a572..f1529a1c264 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixLogarithm.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixLogarithm.java @@ -46,8 +46,6 @@ *

    The input is a tensor of shape {@code [..., M, M]} whose inner-most 2 dimensions * form square matrices. The output is a tensor of the same shape as the input * containing the exponential for all input submatrices {@code [..., :, :]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MatrixLogarithm.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSetDiag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSetDiag.java index 059ac9cbe72..1ec3a1444f5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSetDiag.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSetDiag.java @@ -132,8 +132,6 @@ * [7, 4, 2, 4]]] * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = MatrixSetDiag.OP_NAME, @@ -276,12 +274,12 @@ public static class Inputs extends RawOpInputs public final DataType T; /** - * Some diagonals are shorter than `max_diag_len` and need to be padded. `align` is + * Some diagonals are shorter than {@code max_diag_len} and need to be padded. {@code align} is * a string specifying how superdiagonals and subdiagonals should be aligned, - * respectively. There are four possible alignments: "RIGHT_LEFT" (default), - * "LEFT_RIGHT", "LEFT_LEFT", and "RIGHT_RIGHT". "RIGHT_LEFT" aligns superdiagonals + * respectively. There are four possible alignments: "RIGHT_LEFT" (default), + * "LEFT_RIGHT", "LEFT_LEFT", and "RIGHT_RIGHT". "RIGHT_LEFT" aligns superdiagonals * to the right (left-pads the row) and subdiagonals to the left (right-pads the - * row). It is the packing format LAPACK uses. cuSPARSE uses "LEFT_RIGHT", which is + * row). It is the packing format LAPACK uses. cuSPARSE uses "LEFT_RIGHT", which is * the opposite alignment. */ public final String align; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSolveLs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSolveLs.java index 3b340034827..d0601c6ee57 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSolveLs.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/MatrixSolveLs.java @@ -66,8 +66,6 @@ * least-squares solution, even when \(A\) is rank deficient. This path is * typically 6-7 times slower than the fast path. If {@code fast} is {@code False} then * {@code l2_regularizer} is ignored. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MatrixSolveLs.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Qr.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Qr.java index da577b51660..037f024d04b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Qr.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Qr.java @@ -47,8 +47,6 @@ * q, r = qr(a) * q_full, r_full = qr(a, full_matrices=True) * - * - * @param data type for {@code q} output */ @OpMetadata( opType = Qr.OP_NAME, @@ -165,8 +163,8 @@ public static class Inputs extends RawOpInputs> { public final Operand input; /** - * If true, compute full-sized `q` and `r`. If false - * (the default), compute only the leading `P` columns of `q`. + * If true, compute full-sized {@code q} and {@code r}. If false + * (the default), compute only the leading {@code P} columns of {@code q}. */ public final boolean fullMatrices; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java index 871e9bb5590..d3136668a39 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMul.java @@ -41,8 +41,6 @@ * {@code a} (after being transposed if {@code transpose_a} is non-zero) must match the * outer dimension of {@code b} (after being transposed if {@code transposed_b} is * non-zero). - * - * @param data type for {@code out} output */ @OpMetadata( opType = QuantizedMatMul.OP_NAME, @@ -249,12 +247,12 @@ public static class Inputs extends RawOpInputs> { public final DataType Toutput; /** - * If true, `a` is transposed before multiplication. + * If true, {@code a} is transposed before multiplication. */ public final boolean transposeA; /** - * If true, `b` is transposed before multiplication. + * If true, {@code b} is transposed before multiplication. */ public final boolean transposeB; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java index 9e9f8fa1653..0cc43361bf4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBias.java @@ -43,8 +43,6 @@ * match the outer dimension of {@code b} (after being transposed if {@code transposed_b} is * non-zero). Then do broadcast add operation with bias values on the matrix * multiplication result. The bias size must match inner dimension of {@code b}. - * - * @param data type for {@code out} output */ @OpMetadata( opType = QuantizedMatMulWithBias.OP_NAME, @@ -287,12 +285,12 @@ public static class Inputs extends RawOpInputs> { public final DataType Toutput; /** - * If true, `a` is transposed before multiplication. + * If true, {@code a} is transposed before multiplication. */ public final boolean transposeA; /** - * If true, `b` is transposed before multiplication. + * If true, {@code b} is transposed before multiplication. */ public final boolean transposeB; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java index f8496d61bc8..eee116597b9 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndRelu.java @@ -44,8 +44,6 @@ * non-zero). Then do broadcast add operation with bias values on the matrix * multiplication result. The bias size must match inner dimension of {@code b}. Then do * relu activation to get non-negative result. - * - * @param data type for {@code out} output */ @OpMetadata( opType = QuantizedMatMulWithBiasAndRelu.OP_NAME, @@ -283,12 +281,12 @@ public static class Inputs extends RawOpInputs public final DataType Toutput; /** - * If true, `a` is transposed before multiplication. + * If true, {@code a} is transposed before multiplication. */ public final boolean transposeA; /** - * If true, `b` is transposed before multiplication. + * If true, {@code b} is transposed before multiplication. */ public final boolean transposeB; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java index f2042376788..82bdde439f1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/QuantizedMatMulWithBiasAndReluAndRequantize.java @@ -45,8 +45,6 @@ * multiplication result. The bias size must match inner dimension of {@code b}. Then do * relu activation to get non-negative result. Then do requantize operation to get * final uint8 result. - * - * @param data type for {@code out} output */ @OpMetadata( opType = QuantizedMatMulWithBiasAndReluAndRequantize.OP_NAME, @@ -304,12 +302,12 @@ public static class Inputs extends RawOpInputs - * - * @param data type for {@code e} output */ @OpMetadata( opType = SelfAdjointEig.OP_NAME, @@ -159,7 +157,7 @@ public static class Inputs extends RawOpInputs input; /** - * If `True` then eigenvectors will be computed and returned in `v`. + * If {@code True} then eigenvectors will be computed and returned in {@code v}. * Otherwise, only the eigenvalues will be computed. */ public final boolean computeV; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Solve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Solve.java index b21d43f82a9..d1057183227 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Solve.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Solve.java @@ -41,8 +41,6 @@ * satisfies {@code matrix[..., :, :] * output[..., :, :] = rhs[..., :, :]}. * If {@code adjoint} is {@code True} then each output matrix satisfies * {@code adjoint(matrix[..., :, :]) * output[..., :, :] = rhs[..., :, :]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Solve.OP_NAME, @@ -155,7 +153,7 @@ public static class Inputs extends RawOpInputs> { public final Operand rhs; /** - * Boolean indicating whether to solve with `matrix` or its (block-wise) + * Boolean indicating whether to solve with {@code matrix} or its (block-wise) * adjoint. */ public final boolean adjoint; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Sqrtm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Sqrtm.java index 224688c8e1d..cf48c52605a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Sqrtm.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Sqrtm.java @@ -47,8 +47,6 @@ *

    The input is a tensor of shape {@code [..., M, M]} whose inner-most 2 dimensions * form square matrices. The output is a tensor of the same shape as the input * containing the matrix square root for all input submatrices {@code [..., :, :]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Sqrtm.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Svd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Svd.java index 7142f9fbe25..b11eafdccfc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Svd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Svd.java @@ -45,8 +45,6 @@ * s, u, v = svd(a) * s, _, _ = svd(a, compute_uv=False) * - * - * @param data type for {@code s} output */ @OpMetadata( opType = Svd.OP_NAME, @@ -209,15 +207,15 @@ public static class Inputs extends RawOpInputs> { /** * If true, left and right singular vectors will be - * computed and returned in `u` and `v`, respectively. - * If false, `u` and `v` are not set and should never referenced. + * computed and returned in {@code u} and {@code v}, respectively. + * If false, {@code u} and {@code v} are not set and should never referenced. */ public final boolean computeUv; /** - * If true, compute full-sized `u` and `v`. If false - * (the default), compute only the leading `P` singular vectors. - * Ignored if `compute_uv` is `False`. + * If true, compute full-sized {@code u} and {@code v}. If false + * (the default), compute only the leading {@code P} singular vectors. + * Ignored if {@code compute_uv} is {@code False}. */ public final boolean fullMatrices; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiag.java index 6292194a118..69ee9258392 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiag.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiag.java @@ -48,8 +48,6 @@ * [0, 0, 3, 0] * [0, 0, 0, 4]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = TensorDiag.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiagPart.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiagPart.java index ae21a73b071..838a036f84b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiagPart.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TensorDiagPart.java @@ -49,8 +49,6 @@ * * tf.diag_part(input) ==> [1, 2, 3, 4] * - * - * @param data type for {@code diagonal} output */ @OpMetadata( opType = TensorDiagPart.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Transpose.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Transpose.java index 65f22dfe32b..712576c0989 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Transpose.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/Transpose.java @@ -38,8 +38,6 @@ * Shuffle dimensions of x according to a permutation. * The output {@code y} has the same rank as {@code x}. The shapes of {@code x} and {@code y} satisfy: * {@code y.shape[i] == x.shape[perm[i]] for i in [0, 1, ..., rank(x) - 1]} - * - * @param data type for {@code y} output */ @OpMetadata( opType = Transpose.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TriangularSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TriangularSolve.java index cab9bc283a4..026fbfb70bf 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TriangularSolve.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TriangularSolve.java @@ -77,8 +77,6 @@ * # [4. ], * # [1.9999999]], dtype=float32)> * - * - * @param data type for {@code output} output */ @OpMetadata( opType = TriangularSolve.OP_NAME, @@ -225,18 +223,17 @@ public static class Inputs extends RawOpInputs rhs; /** - * Boolean indicating whether the innermost matrices in `matrix` are + * Boolean indicating whether the innermost matrices in {@code matrix} are * lower or upper triangular. */ public final boolean lower; /** - * Boolean indicating whether to solve with `matrix` or its (block-wise) - * adjoint. - * - * @compatibility(numpy) + * Boolean indicating whether to solve with {@code matrix} or its (block-wise) + * adjoint. + *

    {@literal @}compatibility(numpy)
    * Equivalent to scipy.linalg.solve_triangular - * @end_compatibility + *
    {@literal @}end_compatibility */ public final boolean adjoint; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalMatMul.java index bd69ed483e4..a6122dabc83 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalMatMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalMatMul.java @@ -36,8 +36,6 @@ /** * Calculate product with tridiagonal matrix. * Calculates product of two matrices, where left matrix is a tridiagonal matrix. - * - * @param data type for {@code output} output */ @OpMetadata( opType = TridiagonalMatMul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalSolve.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalSolve.java index 57c0864ef7d..6b0a890d12e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalSolve.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/TridiagonalSolve.java @@ -42,8 +42,6 @@ * pivoting, depending on {@code partial_pivoting} attribute. On GPU, Nvidia's cuSPARSE * library is used: https://docs.nvidia.com/cuda/cusparse/index.html#gtsv * Partial pivoting is not yet supported by XLA backends. - * - * @param data type for {@code output} output */ @OpMetadata( opType = TridiagonalSolve.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java index 27d77557bfb..7fd47c7c6f5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixComponents.java @@ -39,8 +39,6 @@ * Reads out the CSR components at batch {@code index}. * This op is meant only for debugging / testing, and its interface is not expected * to be stable. - * - * @param data type for {@code values} output */ @OpMetadata( opType = CSRSparseMatrixComponents.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java index 51bed06f6ba..97fb87d7250 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToDense.java @@ -36,8 +36,6 @@ /** * Convert a (possibly batched) CSRSparseMatrix to dense. - * - * @param data type for {@code dense_output} output */ @OpMetadata( opType = CSRSparseMatrixToDense.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java index 5c111887894..ad365783cea 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/CSRSparseMatrixToSparseTensor.java @@ -37,8 +37,6 @@ /** * Converts a (possibly batched) CSRSparesMatrix to a SparseTensor. - * - * @param data type for {@code values} output */ @OpMetadata( opType = CSRSparseMatrixToSparseTensor.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMatMul.java index 5fafe452b17..5d9ed9bbbf2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMatMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixMatMul.java @@ -56,8 +56,6 @@ * C = conjugate(transpose(A . B)) = conjugate(transpose(B)) . * conjugate(transpose(A)) * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseMatrixMatMul.OP_NAME, @@ -303,32 +301,32 @@ public static class Inputs extends RawOpInputs { public final DataType type; /** - * Indicates whether `a` should be transposed. + * Indicates whether {@code a} should be transposed. */ public final boolean transposeA; /** - * Indicates whether `b` should be transposed. + * Indicates whether {@code b} should be transposed. */ public final boolean transposeB; /** - * Indicates whether `a` should be conjugate-transposed. + * Indicates whether {@code a} should be conjugate-transposed. */ public final boolean adjointA; /** - * Indicates whether `b` should be conjugate-transposed. + * Indicates whether {@code b} should be conjugate-transposed. */ public final boolean adjointB; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixTranspose.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixTranspose.java index dc1c3bb6833..783fb5c2ebc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixTranspose.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/linalg/sparse/SparseMatrixTranspose.java @@ -145,7 +145,7 @@ public static class Inputs extends RawOpInputs { public final Operand input; /** - * Indicates whether `input` should be conjugated. + * Indicates whether {@code input} should be conjugated. */ public final boolean conjugate; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java index ef53c5f5693..0f4ee840704 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Abs.java @@ -38,8 +38,6 @@ * Given a tensor {@code x}, this operation returns a tensor containing the absolute * value of each element in {@code x}. For example, if x is an input element and y is * an output element, this operation computes \(y = |x|\). - * - * @param data type for {@code y} output */ @OpMetadata( opType = Abs.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AccumulateN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AccumulateN.java index fd1eaeafc4a..3a0e466e8cd 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AccumulateN.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AccumulateN.java @@ -43,8 +43,6 @@ * storage is proportional to the output size rather than the inputs size. *

    Unlike the original {@code accumulate_n}, {@code accumulate_n_v2} is differentiable. *

    Returns a {@code Tensor} of same shape and type as the elements of {@code inputs}. - * - * @param data type for {@code sum} output */ @OpMetadata( opType = AccumulateN.OP_NAME, @@ -116,7 +114,7 @@ public static class Inputs extends RawOpInputs> public final DataType T; /** - * Shape of elements of `inputs`. + * Shape of elements of {@code inputs}. */ public final Shape shape; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acos.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acos.java index 078326e1891..915e5b98b63 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acos.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acos.java @@ -37,8 +37,6 @@ * Computes acos of x element-wise. * Provided an input tensor, the {@code tf.math.acos} operation returns the inverse cosine of each element of the tensor. If {@code y = tf.math.cos(x)} then, {@code x = tf.math.acos(y)}. *

    Input range is {@code [-1, 1]} and the output has a range of {@code [0, pi]}. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Acos.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acosh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acosh.java index 60edbd7880f..8ade37b1990 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acosh.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Acosh.java @@ -41,8 +41,6 @@ * x = tf.constant([-2, -0.5, 1, 1.2, 200, 10000, float("inf")]) * tf.math.acosh(x) ==> [nan nan 0. 0.62236255 5.9914584 9.903487 inf] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Acosh.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Add.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Add.java index 4f32acd9ee1..61db4d2e4ec 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Add.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Add.java @@ -39,8 +39,6 @@ * here *

    Given two input tensors, the {@code tf.add} operation computes the sum for every element in the tensor. *

    Both input and output have a range {@code (-inf, inf)}. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Add.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AddN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AddN.java index 6cd47212eef..f2ef9209796 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AddN.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/AddN.java @@ -41,8 +41,6 @@ * x = [9, 7, 10] * tf.math.add_n(x) ==> 26 * - * - * @param data type for {@code sum} output */ @OpMetadata( opType = AddN.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java index a9c7814636f..6ad1ff84bba 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Angle.java @@ -51,8 +51,6 @@ *

    {@literal @}compatibility(numpy)
    * Equivalent to np.angle. *
    {@literal @}end_compatibility - * - * @param data type for {@code output} output */ @OpMetadata( opType = Angle.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java index 5a7b5adec69..c222f3d54d5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMax.java @@ -48,8 +48,6 @@ * # c = 4 * # here a[4] = 166.32 which is the largest element of a across axis 0 * - * - * @param data type for {@code output} output */ @OpMetadata( opType = ArgMax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java index ff138655b1f..41aa45a10ad 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ArgMin.java @@ -48,8 +48,6 @@ * # c = 0 * # here a[0] = 1 which is the smallest element of a across axis 0 * - * - * @param data type for {@code output} output */ @OpMetadata( opType = ArgMin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asin.java index 050107db969..810aeb5fa3b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asin.java @@ -47,8 +47,6 @@ * * tf.math.asin(y) # [1.047, 0.785] = x * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Asin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asinh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asinh.java index d4170db292a..918518f2b82 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asinh.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Asinh.java @@ -42,8 +42,6 @@ * x = tf.constant([-float("inf"), -2, -0.5, 1, 1.2, 200, 10000, float("inf")]) * tf.math.asinh(x) ==> [-inf -1.4436355 -0.4812118 0.8813736 1.0159732 5.991471 9.903487 inf] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Asinh.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan.java index aab73783c10..8979ab75d9e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan.java @@ -47,8 +47,6 @@ * * tf.math.atan(y) # [1.047, 0.785] = x * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Atan.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java index dfff4a48676..2d566d3cc22 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atan2.java @@ -51,8 +51,6 @@ * * * - * - * @param data type for {@code z} output */ @OpMetadata( opType = Atan2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atanh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atanh.java index ea5729193bf..c4dd0f1ead2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atanh.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Atanh.java @@ -44,8 +44,6 @@ * x = tf.constant([-float("inf"), -1, -0.5, 1, 0, 0.5, 10, float("inf")]) * tf.math.atanh(x) ==> [nan -inf -0.54930615 inf 0. 0.54930615 nan nan] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Atanh.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java index d3782706f20..945d2107a39 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0.java @@ -35,8 +35,6 @@ /** * The BesselI0 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselI0.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java index eec8b3281a3..7e27d3e4263 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI0e.java @@ -35,8 +35,6 @@ /** * The BesselI0e operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselI0e.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java index bb59dc19f5c..28304567e86 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1.java @@ -35,8 +35,6 @@ /** * The BesselI1 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselI1.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java index fe929e32eb1..df3b3f937e8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/BesselI1e.java @@ -35,8 +35,6 @@ /** * The BesselI1e operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselI1e.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java index f7b9904c100..1a895c89f00 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Betainc.java @@ -41,8 +41,6 @@ *

    \(B(x; a, b) = \int_0^x t^{a-1} (1 - t)^{b-1} dt\) *

    is the incomplete beta function and \(B(a, b)\) is the complete * beta function. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Betainc.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java index 6e78f0799fc..463dc277eae 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Bincount.java @@ -42,8 +42,6 @@ * the value in {@code weights} at each index where the corresponding value in {@code arr} is * {@code i}. *

    Values in {@code arr} outside of the range [0, size) are ignored. - * - * @param data type for {@code bins} output */ @OpMetadata( opType = Bincount.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java index 3db46461d7c..1a69b94a8e4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ceil.java @@ -35,8 +35,6 @@ /** * Returns element-wise smallest integer not less than x. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Ceil.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java index 798b2a9cb1a..9461d599888 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ComplexAbs.java @@ -52,8 +52,6 @@ * * * - * - * @param data type for {@code y} output */ @OpMetadata( opType = ComplexAbs.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Conj.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Conj.java index 266da810658..d46b7f2ae5b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Conj.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Conj.java @@ -45,8 +45,6 @@ * # tensor 'input' is [-2.25 + 4.75j, 3.25 + 5.75j] * tf.conj(input) ==> [-2.25 - 4.75j, 3.25 - 5.75j] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conj.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cos.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cos.java index 0ab0152ff02..b6b5b9595c5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cos.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cos.java @@ -43,8 +43,6 @@ * x = tf.constant([-float("inf"), -9, -0.5, 1, 1.2, 200, 10000, float("inf")]) * tf.math.cos(x) ==> [nan -0.91113025 0.87758255 0.5403023 0.36235774 0.48718765 -0.95215535 nan] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Cos.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cosh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cosh.java index 76a98abe533..391d2efd7ab 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cosh.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cosh.java @@ -42,8 +42,6 @@ * x = tf.constant([-float("inf"), -9, -0.5, 1, 1.2, 2, 10, float("inf")]) * tf.math.cosh(x) ==> [inf 4.0515420e+03 1.1276259e+00 1.5430807e+00 1.8106556e+00 3.7621956e+00 1.1013233e+04 inf] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Cosh.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumprod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumprod.java index b4946c796ed..90bdcdc0038 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumprod.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumprod.java @@ -56,8 +56,6 @@ * 

      * tf.cumprod([a, b, c], exclusive=True, reverse=True)  # => [b * c, c, 1]
  *
    - * - * @param data type for {@code out} output */ @OpMetadata( opType = Cumprod.OP_NAME, @@ -200,12 +198,12 @@ public static class Inputs extends RawOpInputs> { public final Operand axis; /** - * If `True`, perform exclusive cumprod. + * If {@code True}, perform exclusive cumprod. */ public final boolean exclusive; /** - * A `bool` (default: False). + * A {@code bool} (default: False). */ public final boolean reverse; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumsum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumsum.java index 2dea6d0fbde..ff8dca235c9 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumsum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Cumsum.java @@ -56,8 +56,6 @@ * 
      * tf.cumsum([a, b, c], exclusive=True, reverse=True)  # => [b + c, c, 0]
  *
    - * - * @param data type for {@code out} output */ @OpMetadata( opType = Cumsum.OP_NAME, @@ -200,12 +198,12 @@ public static class Inputs extends RawOpInputs> { public final Operand axis; /** - * If `True`, perform exclusive cumsum. + * If {@code True}, perform exclusive cumsum. */ public final boolean exclusive; /** - * A `bool` (default: False). + * A {@code bool} (default: False). */ public final boolean reverse; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java index ac645ccaaab..f7367703a41 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/CumulativeLogsumexp.java @@ -51,8 +51,6 @@ * floating point type is used instead. *

    By setting the {@code reverse} kwarg to {@code True}, the cumulative log-sum-exp is performed in the * opposite direction. - * - * @param data type for {@code out} output */ @OpMetadata( opType = CumulativeLogsumexp.OP_NAME, @@ -191,12 +189,12 @@ public static class Inputs extends RawOpInputs axis; /** - * If `True`, perform exclusive cumulative log-sum-exp. + * If {@code True}, perform exclusive cumulative log-sum-exp. */ public final boolean exclusive; /** - * A `bool` (default: False). + * A {@code bool} (default: False). */ public final boolean reverse; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java index ff9a38ba24d..808be372c5f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DenseBincount.java @@ -41,8 +41,6 @@ * the value in {@code weights} at each index where the corresponding value in {@code arr} is * {@code i}. *

    Values in {@code arr} outside of the range [0, size) are ignored. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DenseBincount.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java index 37117f4e1b8..3a48d548bd4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Digamma.java @@ -36,8 +36,6 @@ /** * Computes Psi, the derivative of Lgamma (the log of the absolute value of * {@code Gamma(x)}), element-wise. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Digamma.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Div.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Div.java index 62a15f37da7..8ad37113d3f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Div.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Div.java @@ -37,8 +37,6 @@ * Returns x / y element-wise. * NOTE: {@code math.Div} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = Div.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DivNoNan.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DivNoNan.java index bb098cfdf14..43047bad3c6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DivNoNan.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/DivNoNan.java @@ -37,8 +37,6 @@ * Returns 0 if the denominator is zero. * NOTE: {@code math.DivNoNan} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = DivNoNan.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java index 1e2046e2892..ef607d7778b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erf.java @@ -35,8 +35,6 @@ /** * Computes the Gauss error function of {@code x} element-wise. In statistics, for non-negative values of $x$, the error function has the following interpretation: for a random variable $Y$ that is normally distributed with mean 0 and variance $1/\sqrt{2}$, $erf(x)$ is the probability that $Y$ falls in the range $[−x, x]$. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Erf.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java index b8d11327b94..25fdbcd648c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Erfc.java @@ -35,8 +35,6 @@ /** * Computes the complementary error function of {@code x} element-wise. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Erfc.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Exp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Exp.java index 1a5c7456b51..fe1d6ed1515 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Exp.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Exp.java @@ -56,8 +56,6 @@ * x = tf.constant(1 + 1j) * tf.math.exp(x) ==> 1.4686939399158851+2.2873552871788423j * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Exp.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Expm1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Expm1.java index a6f8f64ab43..b9c80edf84b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Expm1.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Expm1.java @@ -47,8 +47,6 @@ * x = tf.constant(1 + 1j) * tf.math.expm1(x) ==> (0.46869393991588515+2.2873552871788423j) * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Expm1.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java index bb9dbc4aa32..27ed6af66ac 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Floor.java @@ -35,8 +35,6 @@ /** * Returns element-wise largest integer not greater than x. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Floor.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorDiv.java index 47887e1a4dd..61d57ac8c4f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorDiv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorDiv.java @@ -37,8 +37,6 @@ * Returns x // y element-wise. * NOTE: {@code math.FloorDiv} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = FloorDiv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java index 58c90f87123..b41e5d112b2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/FloorMod.java @@ -40,8 +40,6 @@ * {@code floor(x / y) * y + floormod(x, y) = x}, regardless of the signs of x and y. *

    NOTE: {@code math.FloorMod} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = FloorMod.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java index 4f116ba6e63..224c434af9f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igamma.java @@ -42,8 +42,6 @@ *

    is the lower incomplete Gamma function. *

    Note, above {@code Q(a, x)} ({@code Igammac}) is the upper regularized complete * Gamma function. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Igamma.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java index f9e7aced432..a3c6c4f20ad 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/IgammaGradA.java @@ -35,8 +35,6 @@ /** * Computes the gradient of {@code igamma(a, x)} wrt {@code a}. - * - * @param data type for {@code z} output */ @OpMetadata( opType = IgammaGradA.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java index 1cc0549ad00..80f2545ce69 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Igammac.java @@ -42,8 +42,6 @@ *

    is the upper incomplete Gamma function. *

    Note, above {@code P(a, x)} ({@code Igamma}) is the lower regularized complete * Gamma function. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Igammac.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java index fe04cd17336..509de2b8c7b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Imag.java @@ -47,8 +47,6 @@ * # tensor 'input' is [-2.25 + 4.75j, 3.25 + 5.75j] * tf.imag(input) ==> [4.75, 5.75] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Imag.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java index 3035d46e60c..a466109898c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/InvertPermutation.java @@ -46,8 +46,6 @@ * # tensor `x` is [3, 4, 0, 2, 1] * invert_permutation(x) ==> [2, 4, 3, 0, 1] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = InvertPermutation.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java index d8c6b4889a2..4c5aea1de84 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Lgamma.java @@ -42,8 +42,6 @@ * x = tf.constant([0, 0.5, 1, 4.5, -4, -5.6]) * tf.math.lgamma(x) ==> [inf, 0.5723649, 0., 2.4537368, inf, -4.6477685] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Lgamma.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log.java index 32ee589536a..911ab61ff0c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log.java @@ -41,8 +41,6 @@ * x = tf.constant([0, 0.5, 1, 5]) * tf.math.log(x) ==> [-inf, -0.6931472, 0. , 1.609438] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Log.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log1p.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log1p.java index f280d8b0062..05fe31ad376 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log1p.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Log1p.java @@ -41,8 +41,6 @@ * x = tf.constant([0, 0.5, 1, 5]) * tf.math.log1p(x) ==> [0., 0.4054651, 0.6931472, 1.7917595] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Log1p.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java index c46c8c6e384..0c864b79f5e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Maximum.java @@ -37,8 +37,6 @@ * Returns the max of x and y (i.e. x > y ? x : y) element-wise. * NOTE: {@code math.Maximum} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = Maximum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mean.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mean.java index 94de9fc5bd4..9018aa2bd6d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mean.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mean.java @@ -40,8 +40,6 @@ * {@code keep_dims} is true, the rank of the tensor is reduced by 1 for each entry in * {@code axis}. If {@code keep_dims} is true, the reduced dimensions are * retained with length 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Mean.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java index 588bcb3328b..b516ee5c302 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Minimum.java @@ -37,8 +37,6 @@ * Returns the min of x and y (i.e. x < y ? x : y) element-wise. * NOTE: {@code math.Minimum} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = Minimum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java index d318de97c9c..60ccc32e855 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mod.java @@ -39,8 +39,6 @@ * {@code tf.truncatediv(x, y) * y + truncate_mod(x, y) = x}. *

    NOTE: {@code math.Mod} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = Mod.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mul.java index d7466085ada..d18a48a6472 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Mul.java @@ -37,8 +37,6 @@ * Returns x * y element-wise. * NOTE: {@code math.Mul} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = Mul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/MulNoNan.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/MulNoNan.java index 85429b70ca1..7e85f94c31d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/MulNoNan.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/MulNoNan.java @@ -37,8 +37,6 @@ * Returns x * y element-wise. Returns zero if y is zero, even if x if infinite or NaN. * NOTE: {@code math.MulNoNan} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = MulNoNan.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java index 37d1ffb8fc9..2c9b4f4719f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Ndtri.java @@ -35,8 +35,6 @@ /** * The Ndtri operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = Ndtri.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Neg.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Neg.java index e0ec5783144..e11b274470a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Neg.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Neg.java @@ -36,8 +36,6 @@ /** * Computes numerical negative value element-wise. * I.e., \(y = -x\). - * - * @param data type for {@code y} output */ @OpMetadata( opType = Neg.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java index 45ff3a179ca..fef32810db3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/NextAfter.java @@ -40,8 +40,6 @@ *

    {@literal @}compatibility(cpp)
    * Equivalent to C++ std::nextafter function. *
    {@literal @}end_compatibility - * - * @param data type for {@code output} output */ @OpMetadata( opType = NextAfter.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java index b2fb442489b..f391fef2335 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Polygamma.java @@ -39,8 +39,6 @@ *

    \(\psi^{(a)}(x) = \frac{d^a}{dx^a} \psi(x)\) *

    where \(\psi(x)\) is the digamma function. * The polygamma function is defined only for non-negative integer orders \a\. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Polygamma.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Pow.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Pow.java index f50532e8d62..3a8f8acbb7a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Pow.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Pow.java @@ -42,8 +42,6 @@ * # tensor 'y' is [[8, 16], [2, 3]] * tf.pow(x, y) ==> [[256, 65536], [9, 27]] * - * - * @param data type for {@code z} output */ @OpMetadata( opType = Pow.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java index ad59711dca9..cf02c4ad713 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedAdd.java @@ -37,8 +37,6 @@ /** * Returns x + y element-wise, working on quantized buffers. - * - * @param data type for {@code z} output */ @OpMetadata( opType = QuantizedAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java index 6b5c3d05579..b9f1e5b062c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/QuantizedMul.java @@ -37,8 +37,6 @@ /** * Returns x * y element-wise, working on quantized buffers. - * - * @param data type for {@code z} output */ @OpMetadata( opType = QuantizedMul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java index 6217269b474..c85e0d73861 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Real.java @@ -47,8 +47,6 @@ * # tensor 'input' is [-2.25 + 4.75j, 3.25 + 5.75j] * tf.real(input) ==> [-2.25, 3.25] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = Real.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RealDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RealDiv.java index c1aceba76d3..fb2e7e77d33 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RealDiv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RealDiv.java @@ -38,8 +38,6 @@ * If {@code x} and {@code y} are reals, this will return the floating-point division. *

    NOTE: {@code Div} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = RealDiv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Reciprocal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Reciprocal.java index 97ae15f6015..c0e6b9c573a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Reciprocal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Reciprocal.java @@ -36,8 +36,6 @@ /** * Computes the reciprocal of x element-wise. * I.e., \(y = 1 / x\). - * - * @param data type for {@code y} output */ @OpMetadata( opType = Reciprocal.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ReciprocalGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ReciprocalGrad.java index 13b7b7592ab..9d1c672629f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ReciprocalGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/ReciprocalGrad.java @@ -37,8 +37,6 @@ * Computes the gradient for the inverse of {@code x} wrt its input. * Specifically, {@code grad = -dy * y*y}, where {@code y = 1/x}, and {@code dy} * is the corresponding input gradient. - * - * @param data type for {@code z} output */ @OpMetadata( opType = ReciprocalGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java index c2a71d1d594..f6dcf220ade 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RequantizePerChannel.java @@ -37,8 +37,6 @@ /** * Requantizes input with min and max values known per channel. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RequantizePerChannel.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java index 716bc8be07b..62a48d4ecd0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rint.java @@ -43,8 +43,6 @@ * rint(0.5000001) ==> 1.0 * rint([-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0]) ==> [-2., -2., -0., 0., 2., 2., 2.] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Rint.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Round.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Round.java index d8a5aff3d2d..0e7441efeb1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Round.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Round.java @@ -37,8 +37,6 @@ * Rounds the values of a tensor to the nearest integer, element-wise. * Rounds half to even. Also known as bankers rounding. If you want to round * according to the current system rounding mode use std::cint. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Round.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rsqrt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rsqrt.java index 12ce75ef035..3d438f10f12 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rsqrt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Rsqrt.java @@ -36,8 +36,6 @@ /** * Computes reciprocal of square root of x element-wise. * I.e., \(y = 1 / \sqrt{x}\). - * - * @param data type for {@code y} output */ @OpMetadata( opType = Rsqrt.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RsqrtGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RsqrtGrad.java index f92da40a82b..90fc4892083 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RsqrtGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/RsqrtGrad.java @@ -37,8 +37,6 @@ * Computes the gradient for the rsqrt of {@code x} wrt its input. * Specifically, {@code grad = dy * -0.5 * y^3}, where {@code y = rsqrt(x)}, and {@code dy} * is the corresponding input gradient. - * - * @param data type for {@code z} output */ @OpMetadata( opType = RsqrtGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java index 1939c7a4d3a..44ec468eaf4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMax.java @@ -73,8 +73,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SegmentMax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMean.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMean.java index 7d0e2af1606..2e69b2bb8b5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMean.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMean.java @@ -64,8 +64,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SegmentMean.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java index cb5a312d3ff..9dce52fceed 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentMin.java @@ -73,8 +73,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SegmentMin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentProd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentProd.java index 87738a1ac3a..77fd53d92a0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentProd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentProd.java @@ -66,8 +66,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SegmentProd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentSum.java index 578d159e289..c47c3acd24f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentSum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SegmentSum.java @@ -44,9 +44,6 @@ * that {@code segment_ids[j] == i}. *

    If the sum is empty for a given segment ID {@code i}, {@code output[i] = 0}. *

    Note that this op is currently only supported with jit_compile=True. - * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SegmentSum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sigmoid.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sigmoid.java index bd93a0303eb..8e71006a2c0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sigmoid.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sigmoid.java @@ -36,8 +36,6 @@ /** * Computes sigmoid of {@code x} element-wise. * Specifically, {@code y = 1 / (1 + exp(-x))}. - * - * @param data type for {@code y} output */ @OpMetadata( opType = Sigmoid.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SigmoidGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SigmoidGrad.java index 8f4b7cfe45c..a85b754cc61 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SigmoidGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SigmoidGrad.java @@ -37,8 +37,6 @@ * Computes the gradient of the sigmoid of {@code x} wrt its input. * Specifically, {@code grad = dy * y * (1 - y)}, where {@code y = sigmoid(x)}, and * {@code dy} is the corresponding input gradient. - * - * @param data type for {@code z} output */ @OpMetadata( opType = SigmoidGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sign.java index 15f5e07b597..ee9d2d65154 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sign.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sign.java @@ -46,8 +46,6 @@ * * * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Sign.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sin.java index 06269cb6278..1a13ada1838 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sin.java @@ -42,8 +42,6 @@ * x = tf.constant([-float("inf"), -9, -0.5, 1, 1.2, 200, 10, float("inf")]) * tf.math.sin(x) ==> [nan -0.4121185 -0.47942555 0.84147096 0.9320391 -0.87329733 -0.54402107 nan] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Sin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sinh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sinh.java index 9e1a692df76..b4af201ab99 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sinh.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sinh.java @@ -42,8 +42,6 @@ * x = tf.constant([-float("inf"), -9, -0.5, 1, 1.2, 2, 10, float("inf")]) * tf.math.sinh(x) ==> [-inf -4.0515420e+03 -5.2109528e-01 1.1752012e+00 1.5094614e+00 3.6268604e+00 1.1013232e+04 inf] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Sinh.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java index d6de1a9ada4..5989ca78f57 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SobolSample.java @@ -40,8 +40,6 @@ * Generates points from the Sobol sequence. * Creates a Sobol sequence with {@code num_results} samples. Each sample has dimension * {@code dim}. Skips the first {@code skip} samples. - * - * @param data type for {@code samples} output */ @OpMetadata( opType = SobolSample.OP_NAME, @@ -145,7 +143,7 @@ public static class Inputs extends RawOpInputs> { public final Operand skip; /** - * The type of the sample. One of: `float32` or `float64`. + * The type of the sample. One of: {@code float32} or {@code float64}. */ public final DataType dtype; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java index aa80f8d0840..cdb0aea4f9f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Softplus.java @@ -35,8 +35,6 @@ /** * The Softplus operation - * - * @param data type for {@code activations} output */ @OpMetadata( opType = Softplus.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java index 5a8445dad45..3f2901810ce 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SoftplusGrad.java @@ -35,8 +35,6 @@ /** * Computes softplus gradients for a softplus operation. - * - * @param data type for {@code backprops} output */ @OpMetadata( opType = SoftplusGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sqrt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sqrt.java index ac6cd68b529..8c6edfc6e89 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sqrt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sqrt.java @@ -36,8 +36,6 @@ /** * Computes square root of x element-wise. * I.e., \(y = \sqrt{x} = x^{1/2}\). - * - * @param data type for {@code y} output */ @OpMetadata( opType = Sqrt.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SqrtGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SqrtGrad.java index 451143c16e4..eed0209152b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SqrtGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SqrtGrad.java @@ -37,8 +37,6 @@ * Computes the gradient for the sqrt of {@code x} wrt its input. * Specifically, {@code grad = dy * 0.5 / y}, where {@code y = sqrt(x)}, and {@code dy} * is the corresponding input gradient. - * - * @param data type for {@code z} output */ @OpMetadata( opType = SqrtGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Square.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Square.java index d5811d17c2a..2952af307d2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Square.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Square.java @@ -36,8 +36,6 @@ /** * Computes square of x element-wise. * I.e., \(y = x * x = x^2\). - * - * @param data type for {@code y} output */ @OpMetadata( opType = Square.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SquaredDifference.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SquaredDifference.java index 2af6fe083e3..4d880a79baa 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SquaredDifference.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/SquaredDifference.java @@ -37,8 +37,6 @@ * Returns conj(x - y)(x - y) element-wise. * NOTE: {@code math.SquaredDifference} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = SquaredDifference.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sub.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sub.java index 6313555f9f1..b48b311d80e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sub.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Sub.java @@ -37,8 +37,6 @@ * Returns x - y element-wise. * NOTE: {@code math.Sub} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = Sub.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tan.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tan.java index 566b7d2b03f..c1073f8a5bb 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tan.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tan.java @@ -43,8 +43,6 @@ * x = tf.constant([-float("inf"), -9, -0.5, 1, 1.2, 200, 10000, float("inf")]) * tf.math.tan(x) ==> [nan 0.45231566 -0.5463025 1.5574077 2.572152 -1.7925274 0.32097113 nan] * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Tan.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tanh.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tanh.java index ee24b4085df..706a8d90cd0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tanh.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Tanh.java @@ -49,8 +49,6 @@ * * * - * - * @param data type for {@code y} output */ @OpMetadata( opType = Tanh.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TanhGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TanhGrad.java index c638f78b3fe..273adcf20a6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TanhGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TanhGrad.java @@ -37,8 +37,6 @@ * Computes the gradient for the tanh of {@code x} wrt its input. * Specifically, {@code grad = dy * (1 - y*y)}, where {@code y = tanh(x)}, and {@code dy} * is the corresponding input gradient. - * - * @param data type for {@code z} output */ @OpMetadata( opType = TanhGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateDiv.java index 377eb5848d8..7857bd6221b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateDiv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateDiv.java @@ -41,8 +41,6 @@ * Python Semantics. *

    NOTE: {@code math.TruncateDiv} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = TruncateDiv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java index e80c75e5709..bd7a41fafd2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/TruncateMod.java @@ -38,8 +38,6 @@ * the result here is consistent with a truncating divide. E.g. {@code truncate(x / y) * y + truncate_mod(x, y) = x}. *

    NOTE: {@code math.TruncateMod} supports broadcasting. More about broadcasting * here - * - * @param data type for {@code z} output */ @OpMetadata( opType = TruncateMod.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UniformQuantizedAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UniformQuantizedAdd.java index a3f9a486aad..312c712b44e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UniformQuantizedAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UniformQuantizedAdd.java @@ -52,8 +52,6 @@ * i.e. For both operands {@code lhs} and {@code rhs}, * if {@code operand.quantization_axis} >= 0 and {@code output.quantization_axis} >= 0, * {@code operand.dims} - {@code operand.quantization_axis} must be equal to {@code output.dims} - {@code output.quantization_axis}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformQuantizedAdd.OP_NAME, @@ -314,69 +312,69 @@ public static class Inputs extends RawOpInputs * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = UnsortedSegmentMax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java index db83daaead7..af919665a56 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentMin.java @@ -64,8 +64,6 @@ * result in safe but unspecified behavior, which may include ignoring * out-of-bound indices or outputting a tensor with a 0 stored in the first * dimension of its shape if {@code num_segments} is 0. - * - * @param data type for {@code output} output */ @OpMetadata( opType = UnsortedSegmentMin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentProd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentProd.java index a36c653ef2a..fd3f76bc1e7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentProd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentProd.java @@ -64,8 +64,6 @@ * result in safe but unspecified behavior, which may include ignoring * out-of-bound indices or outputting a tensor with a 0 stored in the first * dimension of its shape if {@code num_segments} is 0. - * - * @param data type for {@code output} output */ @OpMetadata( opType = UnsortedSegmentProd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentSum.java index 14c0bef2293..af4dd57e39f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentSum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/UnsortedSegmentSum.java @@ -67,8 +67,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = UnsortedSegmentSum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xdivy.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xdivy.java index 8be3546a9f0..0ba35ba8a83 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xdivy.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xdivy.java @@ -35,8 +35,6 @@ /** * Returns 0 if x == 0, and x / y otherwise, elementwise. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Xdivy.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlog1py.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlog1py.java index b798c8ef598..c6e6184bed0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlog1py.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlog1py.java @@ -35,8 +35,6 @@ /** * Returns 0 if x == 0, and x * log1p(y) otherwise, elementwise. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Xlog1py.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlogy.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlogy.java index b4ad543093f..e27ef9a210c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlogy.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Xlogy.java @@ -35,8 +35,6 @@ /** * Returns 0 if x == 0, and x * log(y) otherwise, elementwise. - * - * @param data type for {@code z} output */ @OpMetadata( opType = Xlogy.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java index 887fb1af711..593507c4340 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/Zeta.java @@ -37,8 +37,6 @@ * Compute the Hurwitz zeta function \(\zeta(x, q)\). * The Hurwitz zeta function is defined as: *

    \(\zeta(x, q) = \sum_{n=0}^{\infty} (q + n)^{-x}\) - * - * @param data type for {@code z} output */ @OpMetadata( opType = Zeta.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java index a4b68423646..a208c49973f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/erfinv.java @@ -35,8 +35,6 @@ /** * The Erfinv operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = erfinv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java index 6ef1d289c7d..839ca6179b3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ0.java @@ -35,8 +35,6 @@ /** * The BesselJ0 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselJ0.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java index 5e7718f4144..6e125a29821 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselJ1.java @@ -35,8 +35,6 @@ /** * The BesselJ1 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselJ1.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java index 338b5759a10..8ec9f528212 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0.java @@ -35,8 +35,6 @@ /** * The BesselK0 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselK0.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java index f2a01b68ba8..69d5995c59d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK0e.java @@ -35,8 +35,6 @@ /** * The BesselK0e operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselK0e.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java index 8143c8107d5..f26b95a8c53 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1.java @@ -35,8 +35,6 @@ /** * The BesselK1 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselK1.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java index 08ea2073dab..995eaccd9dd 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselK1e.java @@ -35,8 +35,6 @@ /** * The BesselK1e operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselK1e.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java index c82e15022db..1beae63d61f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY0.java @@ -35,8 +35,6 @@ /** * The BesselY0 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselY0.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java index 5b86f1987e3..3985dee42d0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/BesselY1.java @@ -35,8 +35,6 @@ /** * The BesselY1 operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = BesselY1.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java index 045ffc0d94c..e34e0376249 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Dawsn.java @@ -35,8 +35,6 @@ /** * The Dawsn operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = Dawsn.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java index bcdff92cb07..9b61e0fcb90 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Expint.java @@ -35,8 +35,6 @@ /** * The Expint operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = Expint.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java index 790daad9115..dffb6bda0f0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelCos.java @@ -35,8 +35,6 @@ /** * The FresnelCos operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = FresnelCos.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java index a148cb42bff..23e7e1d4bbd 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/FresnelSin.java @@ -35,8 +35,6 @@ /** * The FresnelSin operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = FresnelSin.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java index 7835a2fca79..0a012a3be6c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/math/special/Spence.java @@ -35,8 +35,6 @@ /** * The Spence operation - * - * @param data type for {@code y} output */ @OpMetadata( opType = Spence.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java index 9cbe9d8c9a3..3d6355679c8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool.java @@ -38,8 +38,6 @@ * Performs average pooling on the input. * Each entry in {@code output} is the mean of the corresponding size {@code ksize} * window in {@code value}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = AvgPool.OP_NAME, @@ -165,12 +163,12 @@ public static class Inputs extends RawOpInputs> { public final Operand value; /** - * The size of the sliding window for each dimension of `value`. + * The size of the sliding window for each dimension of {@code value}. */ public final long[] ksize; /** - * The stride of the sliding window for each dimension of `value`. + * The stride of the sliding window for each dimension of {@code value}. */ public final long[] strides; @@ -181,10 +179,10 @@ public static class Inputs extends RawOpInputs> { /** * Specify the data format of the input and output data. With the - * default format "NHWC", the data is stored in the order of: - * [batch, in_height, in_width, in_channels]. - * Alternatively, the format could be "NCHW", the data storage order of: - * [batch, in_channels, in_height, in_width]. + * default format "NHWC", the data is stored in the order of: + * [batch, in_height, in_width, in_channels]. + * Alternatively, the format could be "NCHW", the data storage order of: + * [batch, in_channels, in_height, in_width]. */ public final String dataFormat; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java index 5fd233ad4d6..5f5410d91d5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3d.java @@ -38,8 +38,6 @@ * Performs 3D average pooling on the input. * Each entry in {@code output} is the mean of the corresponding size {@code ksize} window in * {@code value}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = AvgPool3d.OP_NAME, @@ -168,13 +166,13 @@ public static class Inputs extends RawOpInputs> /** * 1-D tensor of length 5. The size of the window for each dimension of - * the input tensor. Must have `ksize[0] = ksize[4] = 1`. + * the input tensor. Must have {@code ksize[0] = ksize[4] = 1}. */ public final long[] ksize; /** * 1-D tensor of length 5. The stride of the sliding window for each - * dimension of `input`. Must have `strides[0] = strides[4] = 1`. + * dimension of {@code input}. Must have {@code strides[0] = strides[4] = 1}. */ public final long[] strides; @@ -185,10 +183,10 @@ public static class Inputs extends RawOpInputs> /** * The data format of the input and output data. With the - * default format "NDHWC", the data is stored in the order of: - * [batch, in_depth, in_height, in_width, in_channels]. - * Alternatively, the format could be "NCDHW", the data storage order is: - * [batch, in_channels, in_depth, in_height, in_width]. + * default format "NDHWC", the data is stored in the order of: + * [batch, in_depth, in_height, in_width, in_channels]. + * Alternatively, the format could be "NCDHW", the data storage order is: + * [batch, in_channels, in_depth, in_height, in_width]. */ public final String dataFormat; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java index 7c4e8005968..4b41a0338b3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/AvgPool3dGrad.java @@ -37,8 +37,6 @@ /** * Computes gradients of average pooling function. - * - * @param data type for {@code output} output */ @OpMetadata( opType = AvgPool3dGrad.OP_NAME, @@ -175,13 +173,13 @@ public static class Inputs extends RawOpInputs extends RawOpInputs data type for {@code output} output */ @OpMetadata( opType = AvgPoolGrad.OP_NAME, @@ -190,10 +188,10 @@ public static class Inputs extends RawOpInputs /** * Specify the data format of the input and output data. With the - * default format "NHWC", the data is stored in the order of: - * [batch, in_height, in_width, in_channels]. - * Alternatively, the format could be "NCHW", the data storage order of: - * [batch, in_channels, in_height, in_width]. + * default format "NHWC", the data is stored in the order of: + * [batch, in_height, in_width, in_channels]. + * Alternatively, the format could be "NCHW", the data storage order of: + * [batch, in_channels, in_height, in_width]. */ public final String dataFormat; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalization.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalization.java index deaec7bdd3d..ef7ead8115e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalization.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalization.java @@ -36,8 +36,6 @@ /** * Batch normalization. * This op is deprecated. Prefer {@code tf.nn.batch_normalization}. - * - * @param data type for {@code result} output */ @OpMetadata( opType = BatchNormWithGlobalNormalization.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalizationGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalizationGrad.java index f75aebb0e4c..03e84d778c4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalizationGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BatchNormWithGlobalNormalizationGrad.java @@ -36,8 +36,6 @@ /** * Gradients for batch normalization. * This op is deprecated. See {@code tf.nn.batch_normalization}. - * - * @param data type for {@code dx} output */ @OpMetadata( opType = BatchNormWithGlobalNormalizationGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAdd.java index d5c80bb1acd..5f826546b07 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAdd.java @@ -37,8 +37,6 @@ * Adds {@code bias} to {@code value}. * This is a special case of {@code tf.add} where {@code bias} is restricted to be 1-D. * Broadcasting is supported, so {@code value} may have any number of dimensions. - * - * @param data type for {@code output} output */ @OpMetadata( opType = BiasAdd.OP_NAME, @@ -167,12 +165,12 @@ public static class Inputs extends RawOpInputs> { /** * Specify the data format of the input and output data. With the - * default format "NHWC", the bias tensor will be added to the last dimension + * default format "NHWC", the bias tensor will be added to the last dimension * of the value tensor. - * Alternatively, the format could be "NCHW", the data storage order of: - * [batch, in_channels, in_height, in_width]. - * The tensor will be added to "in_channels", the third-to-the-last - * dimension. + * Alternatively, the format could be "NCHW", the data storage order of: + * [batch, in_channels, in_height, in_width]. + * The tensor will be added to "in_channels", the third-to-the-last + * dimension. */ public final String dataFormat; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAddGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAddGrad.java index dffab9d2958..33c2829c271 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAddGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BiasAddGrad.java @@ -38,8 +38,6 @@ * It accumulates all the values from out_backprop into the feature dimension. * For NHWC data format, the feature dimension is the last. For NCHW data format, * the feature dimension is the third-to-last. - * - * @param data type for {@code output} output */ @OpMetadata( opType = BiasAddGrad.OP_NAME, @@ -161,12 +159,12 @@ public static class Inputs extends RawOpInputs> /** * Specify the data format of the input and output data. With the - * default format "NHWC", the bias tensor will be added to the last dimension + * default format "NHWC", the bias tensor will be added to the last dimension * of the value tensor. - * Alternatively, the format could be "NCHW", the data storage order of: - * [batch, in_channels, in_height, in_width]. - * The tensor will be added to "in_channels", the third-to-the-last - * dimension. + * Alternatively, the format could be "NCHW", the data storage order of: + * [batch, in_channels, in_height, in_width]. + * The tensor will be added to "in_channels", the third-to-the-last + * dimension. */ public final String dataFormat; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java index 3363a371d20..ef303c35efc 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTM.java @@ -56,8 +56,6 @@ * this op uses IFCO. So in order for the following snippet to be equivalent * all gate-related outputs should be reordered. * - * - * @param data type for {@code i} output */ @OpMetadata( opType = BlockLSTM.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java index 2684ae60017..85bc08f38b6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/BlockLSTMGrad.java @@ -37,8 +37,6 @@ /** * Computes the LSTM cell backward propagation for the entire time sequence. * This implementation is to be used in conjunction of BlockLSTMV2. - * - * @param data type for {@code x_grad} output */ @OpMetadata( opType = BlockLSTMGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CTCLossV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CTCLossV2.java index f09ff645b5a..f64d2f7bc3d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CTCLossV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CTCLossV2.java @@ -244,7 +244,7 @@ public static class Inputs extends RawOpInputs { public final boolean preprocessCollapseRepeated; /** - * Scalar. If set to false, *during* CTC calculation + * Scalar. If set to false, during CTC calculation * repeated non-blank labels will not be merged and are interpreted as * individual labels. This is a simplified version of CTC. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv.java index d1af59aeb93..096c8a3719f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv.java @@ -38,8 +38,6 @@ * Computes a N-D convolution given (N+1+batch_dims)-D {@code input} and (N+2)-D {@code filter} tensors. * General function for computing a N-D convolution. It is required that * {@code 1 <= N <= 3}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv.OP_NAME, @@ -373,8 +371,8 @@ public static class Inputs extends RawOpInputs> { public final DataType T; /** - * 1-D tensor of length `N+2`. The stride of the sliding window for each - * dimension of `input`. Must have `strides[0] = strides[N+1] = 1`. + * 1-D tensor of length {@code N+2}. The stride of the sliding window for each + * dimension of {@code input}. Must have {@code strides[0] = strides[N+1] = 1}. */ public final long[] strides; @@ -384,24 +382,24 @@ public static class Inputs extends RawOpInputs> { public final String padding; /** - * If `padding` is `"EXPLICIT"`, the list of explicit padding amounts. For the ith + * If {@code padding} is {@code "EXPLICIT"}, the list of explicit padding amounts. For the ith * dimension, the amount of padding inserted before and after the dimension is - * `explicit_paddings[2 * i]` and `explicit_paddings[2 * i + 1]`, respectively. If - * `padding` is not `"EXPLICIT"`, `explicit_paddings` must be empty. + * {@code explicit_paddings[2 * i]} and {@code explicit_paddings[2 * i + 1]}, respectively. If + * {@code padding} is not {@code "EXPLICIT"}, {@code explicit_paddings} must be empty. */ public final long[] explicitPaddings; /** - * Used to set the data format. By default `CHANNELS_FIRST`, uses - * `NHWC (2D) / NDHWC (3D)` or if `CHANNELS_LAST`, uses `NCHW (2D) / NCDHW (3D)`. + * Used to set the data format. By default {@code CHANNELS_FIRST}, uses + * {@code NHWC (2D) / NDHWC (3D)} or if {@code CHANNELS_LAST}, uses {@code NCHW (2D) / NCDHW (3D)}. */ public final String dataFormat; /** - * 1-D tensor of length `N+2`. The dilation factor for each dimension of - * `input`. If set to `k > 1`, there will be `k-1` skipped cells between each + * 1-D tensor of length {@code N+2}. The dilation factor for each dimension of + * {@code input}. If set to {@code k > 1}, there will be {@code k-1} skipped cells between each * filter element on that dimension. The dimension order is determined by the - * value of `channels_last_format`, see above for details. Dilations in the batch + * value of {@code channels_last_format}, see above for details. Dilations in the batch * and depth dimensions must be 1. */ public final long[] dilations; @@ -415,7 +413,7 @@ public static class Inputs extends RawOpInputs> { /** * A positive integer specifying the number of groups in which the input is split * along the channel axis. Each group is convolved separately with - * `filters / groups` filters. The output is the concatenation of all the groups + * {@code filters / groups} filters. The output is the concatenation of all the groups * results along the channel axis. Input channels and filters must both be * divisible by groups. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java index b2199188473..6d7eb6e004e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2d.java @@ -56,8 +56,6 @@ * *

    Must have {@code strides[0] = strides[3] = 1}. For the most common case of the same * horizontal and vertices strides, {@code strides = [1, stride, stride, 1]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv2d.OP_NAME, @@ -353,8 +351,8 @@ public static class Inputs extends RawOpInputs> { /** * 1-D tensor of length 4. The stride of the sliding window for each - * dimension of `input`. The dimension order is determined by the value of - * `data_format`, see below for details. + * dimension of {@code input}. The dimension order is determined by the value of + * {@code data_format}, see below for details. */ public final long[] strides; @@ -369,27 +367,27 @@ public static class Inputs extends RawOpInputs> { public final String padding; /** - * If `padding` is `"EXPLICIT"`, the list of explicit padding amounts. For the ith + * If {@code padding} is {@code "EXPLICIT"}, the list of explicit padding amounts. For the ith * dimension, the amount of padding inserted before and after the dimension is - * `explicit_paddings[2 * i]` and `explicit_paddings[2 * i + 1]`, respectively. If - * `padding` is not `"EXPLICIT"`, `explicit_paddings` must be empty. + * {@code explicit_paddings[2 * i]} and {@code explicit_paddings[2 * i + 1]}, respectively. If + * {@code padding} is not {@code "EXPLICIT"}, {@code explicit_paddings} must be empty. */ public final long[] explicitPaddings; /** * Specify the data format of the input and output data. With the - * default format "NHWC", the data is stored in the order of: - * [batch, height, width, channels]. - * Alternatively, the format could be "NCHW", the data storage order of: - * [batch, channels, height, width]. + * default format "NHWC", the data is stored in the order of: + * [batch, height, width, channels]. + * Alternatively, the format could be "NCHW", the data storage order of: + * [batch, channels, height, width]. */ public final String dataFormat; /** * 1-D tensor of length 4. The dilation factor for each dimension of - * `input`. If set to k > 1, there will be k-1 skipped cells between each + * {@code input}. If set to k > 1, there will be k-1 skipped cells between each * filter element on that dimension. The dimension order is determined by the - * value of `data_format`, see above for details. Dilations in the batch and + * value of {@code data_format}, see above for details. Dilations in the batch and * depth dimensions must be 1. */ public final long[] dilations; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java index dbcaaf481cb..2d5af50d5e6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilter.java @@ -37,8 +37,6 @@ /** * Computes the gradients of convolution with respect to the filter. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv2dBackpropFilter.OP_NAME, @@ -361,27 +359,27 @@ public static class Inputs extends RawOpInputs 1, there will be k-1 skipped cells between each filter + * {@code input}. If set to k > 1, there will be k-1 skipped cells between each filter * element on that dimension. The dimension order is determined by the value of - * `data_format`, see above for details. Dilations in the batch and depth + * {@code data_format}, see above for details. Dilations in the batch and depth * dimensions must be 1. */ public final long[] dilations; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilterV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilterV2.java index a71091b235b..1b8a95c8728 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilterV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropFilterV2.java @@ -35,8 +35,6 @@ /** * Computes the gradients of convolution with respect to the filter. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv2dBackpropFilterV2.OP_NAME, @@ -354,27 +352,27 @@ public static class Inputs extends RawOpInputs 1, there will be k-1 skipped cells between each filter + * {@code input}. If set to k > 1, there will be k-1 skipped cells between each filter * element on that dimension. The dimension order is determined by the value of - * `data_format`, see above for details. Dilations in the batch and depth + * {@code data_format}, see above for details. Dilations in the batch and depth * dimensions must be 1. */ public final long[] dilations; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java index ff17146e323..fc0f5f296e1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInput.java @@ -37,8 +37,6 @@ /** * Computes the gradients of convolution with respect to the input. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv2dBackpropInput.OP_NAME, @@ -360,27 +358,27 @@ public static class Inputs extends RawOpInputs 1, there will be k-1 skipped cells between each filter + * {@code input}. If set to k > 1, there will be k-1 skipped cells between each filter * element on that dimension. The dimension order is determined by the value of - * `data_format`, see above for details. Dilations in the batch and depth + * {@code data_format}, see above for details. Dilations in the batch and depth * dimensions must be 1. */ public final long[] dilations; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInputV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInputV2.java index 44e9ef59aa0..04941640016 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInputV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv2dBackpropInputV2.java @@ -35,8 +35,6 @@ /** * Computes the gradients of convolution with respect to the input. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv2dBackpropInputV2.OP_NAME, @@ -355,27 +353,27 @@ public static class Inputs extends RawOpInputs 1, there will be k-1 skipped cells between each filter + * {@code input}. If set to k > 1, there will be k-1 skipped cells between each filter * element on that dimension. The dimension order is determined by the value of - * `data_format`, see above for details. Dilations in the batch and depth + * {@code data_format}, see above for details. Dilations in the batch and depth * dimensions must be 1. */ public final long[] dilations; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java index ebc6170eae0..7de4f93716d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3d.java @@ -40,8 +40,6 @@ * two waveforms as a function of a time-lag applied to one of them. This * is also known as a sliding dot product or sliding inner-product. *

    Our Conv3D implements a form of cross-correlation. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv3d.OP_NAME, @@ -242,7 +240,7 @@ public static class Inputs extends RawOpInputs> { /** * 1-D tensor of length 5. The stride of the sliding window for each - * dimension of `input`. Must have `strides[0] = strides[4] = 1`. + * dimension of {@code input}. Must have {@code strides[0] = strides[4] = 1}. */ public final long[] strides; @@ -253,18 +251,18 @@ public static class Inputs extends RawOpInputs> { /** * The data format of the input and output data. With the - * default format "NDHWC", the data is stored in the order of: - * [batch, in_depth, in_height, in_width, in_channels]. - * Alternatively, the format could be "NCDHW", the data storage order is: - * [batch, in_channels, in_depth, in_height, in_width]. + * default format "NDHWC", the data is stored in the order of: + * [batch, in_depth, in_height, in_width, in_channels]. + * Alternatively, the format could be "NCDHW", the data storage order is: + * [batch, in_channels, in_depth, in_height, in_width]. */ public final String dataFormat; /** * 1-D tensor of length 5. The dilation factor for each dimension of - * `input`. If set to k > 1, there will be k-1 skipped cells between each + * {@code input}. If set to k > 1, there will be k-1 skipped cells between each * filter element on that dimension. The dimension order is determined by the - * value of `data_format`, see above for details. Dilations in the batch and + * value of {@code data_format}, see above for details. Dilations in the batch and * depth dimensions must be 1. */ public final long[] dilations; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java index e7c35fbbe28..79970ac4d15 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropFilter.java @@ -37,8 +37,6 @@ /** * Computes the gradients of 3-D convolution with respect to the filter. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv3dBackpropFilter.OP_NAME, @@ -253,7 +251,7 @@ public static class Inputs extends RawOpInputs extends RawOpInputs 1, there will be k-1 skipped cells between each + * {@code input}. If set to k > 1, there will be k-1 skipped cells between each * filter element on that dimension. The dimension order is determined by the - * value of `data_format`, see above for details. Dilations in the batch and + * value of {@code data_format}, see above for details. Dilations in the batch and * depth dimensions must be 1. */ public final long[] dilations; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java index 4306849324d..d60306ab96d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Conv3dBackpropInput.java @@ -36,8 +36,6 @@ /** * Computes the gradients of 3-D convolution with respect to the input. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Conv3dBackpropInput.OP_NAME, @@ -252,7 +250,7 @@ public static class Inputs extends RawOpInputs extends RawOpInputs 1, there will be k-1 skipped cells between each + * {@code input}. If set to k > 1, there will be k-1 skipped cells between each * filter element on that dimension. The dimension order is determined by the - * value of `data_format`, see above for details. Dilations in the batch and + * value of {@code data_format}, see above for details. Dilations in the batch and * depth dimensions must be 1. */ public final long[] dilations; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java index 56ad8a6d8a3..f270607bb50 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcBeamSearchDecoder.java @@ -43,8 +43,6 @@ * the first of these is emitted. That is, when the top path is "A B B B B", * "A B" is returned if merge_repeated = True but "A B B B B" is * returned if merge_repeated = False. - * - * @param data type for {@code log_probability} output */ @OpMetadata( opType = CtcBeamSearchDecoder.OP_NAME, @@ -204,7 +202,7 @@ public static class Inputs extends RawOpInputs sequenceLength; /** - * A scalar >= 0 (beam search beam width). + * A scalar >= 0 (beam search beam width). */ public final long beamWidth; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java index de01c874c33..688f60ab28e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcGreedyDecoder.java @@ -45,8 +45,6 @@ *

    Regardless of the value of merge_repeated, if the maximum index of a given * time and batch corresponds to the blank, index {@code (num_classes - 1)}, no new * element is emitted. - * - * @param data type for {@code log_probability} output */ @OpMetadata( opType = CtcGreedyDecoder.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java index 3933b6dd5f8..8369dae6c75 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CtcLoss.java @@ -39,8 +39,6 @@ * Calculates the CTC Loss (log probability) for each batch entry. Also calculates * the gradient. This class performs the softmax operation for you, so inputs * should be e.g. linear projections of outputs by an LSTM. - * - * @param data type for {@code loss} output */ @OpMetadata( opType = CtcLoss.OP_NAME, @@ -246,7 +244,7 @@ public static class Inputs extends RawOpInputs> { public final boolean preprocessCollapseRepeated; /** - * Scalar. If set to false, *during* CTC calculation + * Scalar. If set to false, during CTC calculation * repeated non-blank labels will not be merged and are interpreted as * individual labels. This is a simplified version of CTC. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java index 0525df86f45..8845090aa6e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNN.java @@ -73,8 +73,6 @@ * major. * reserve_space: An opaque tensor that can be used in backprop calculation. It * is only produced if is_training is true. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CudnnRNN.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java index d76dd629918..a1e09f597ac 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNBackprop.java @@ -83,8 +83,6 @@ * shape as input_c. * params_backprop: The backprop to the params buffer in the forward pass. Has the * same shape as params. - * - * @param data type for {@code input_backprop} output */ @OpMetadata( opType = CudnnRNNBackprop.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java index a513cf67d66..0c38a68a23e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNCanonicalToParams.java @@ -65,8 +65,6 @@ * seed2: the 2nd part of a seed to initialize dropout. * num_proj: The output dimensionality for the projection matrices. If None or 0, * no projection is performed. - * - * @param data type for {@code params} output */ @OpMetadata( opType = CudnnRNNCanonicalToParams.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java index 6a1e55f34e2..b85a3568412 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRNNParamsToCanonical.java @@ -65,8 +65,6 @@ * seed2: the 2nd part of a seed to initialize dropout. * num_proj: The output dimensionality for the projection matrices. If None or 0, * no projection is performed. - * - * @param data type for {@code weights} output */ @OpMetadata( opType = CudnnRNNParamsToCanonical.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java index 051c792e878..1dbc4d48ad8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/CudnnRnnParamsSize.java @@ -57,8 +57,6 @@ * compatible across GPUs. Please use CudnnRNNParamsWeights and * CudnnRNNParamsBiases to save and restore them in a way that is compatible * across different runs. - * - * @param data type for {@code params_size} output */ @OpMetadata( opType = CudnnRnnParamsSize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java index 3376ad9ed6e..6e83cd0c867 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatDimMap.java @@ -36,8 +36,6 @@ /** * Returns the dimension index in the destination data format given the one in * the source data format. - * - * @param data type for {@code y} output */ @OpMetadata( opType = DataFormatDimMap.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java index e02890a40ce..f719f7cc7ce 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DataFormatVecPermute.java @@ -64,8 +64,6 @@ * 

      * [1, 2]
  *
    - * - * @param data type for {@code y} output */ @OpMetadata( opType = DataFormatVecPermute.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthToSpace.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthToSpace.java index cceb78d27d1..2f1880cda02 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthToSpace.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthToSpace.java @@ -109,8 +109,6 @@ * [ [11], [12], [15], [16]]]] * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = DepthToSpace.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java index 57e6db5154f..93a0b744513 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNative.java @@ -52,8 +52,6 @@ * *

    Must have {@code strides[0] = strides[3] = 1}. For the most common case of the same * horizontal and vertices strides, {@code strides = [1, stride, stride, 1]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DepthwiseConv2dNative.OP_NAME, @@ -305,7 +303,7 @@ public static class Inputs extends RawOpInputs extends RawOpInputs 1, there will be k-1 skipped cells between each filter + * {@code input}. If set to k > 1, there will be k-1 skipped cells between each filter * element on that dimension. The dimension order is determined by the value of - * `data_format`, see above for details. Dilations in the batch and depth + * {@code data_format}, see above for details. Dilations in the batch and depth * dimensions must be 1. */ public final long[] dilations; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java index d53cd3b03b4..66eb190debf 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropFilter.java @@ -37,8 +37,6 @@ /** * Computes the gradients of depthwise convolution with respect to the filter. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DepthwiseConv2dNativeBackpropFilter.OP_NAME, @@ -328,18 +326,18 @@ public static class Inputs extends RawOpInputs 1, there will be k-1 skipped cells between each filter + * {@code input}. If set to k > 1, there will be k-1 skipped cells between each filter * element on that dimension. The dimension order is determined by the value of - * `data_format`, see above for details. Dilations in the batch and depth + * {@code data_format}, see above for details. Dilations in the batch and depth * dimensions must be 1. */ public final long[] dilations; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java index bea9149d3e4..287b29abba1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/DepthwiseConv2dNativeBackpropInput.java @@ -37,8 +37,6 @@ /** * Computes the gradients of depthwise convolution with respect to the input. - * - * @param data type for {@code output} output */ @OpMetadata( opType = DepthwiseConv2dNativeBackpropInput.OP_NAME, @@ -328,18 +326,18 @@ public static class Inputs extends RawOpInputs 1, there will be k-1 skipped cells between each filter + * {@code input}. If set to k > 1, there will be k-1 skipped cells between each filter * element on that dimension. The dimension order is determined by the value of - * `data_format`, see above for details. Dilations in the batch and depth + * {@code data_format}, see above for details. Dilations in the batch and depth * dimensions must be 1. */ public final long[] dilations; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java index 5354aefa6bb..019c786873c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2d.java @@ -57,8 +57,6 @@ * kernel size and contains all zeros. *

    Note on duality: The dilation of {@code input} by the {@code filter} is equal to the * negation of the erosion of {@code -input} by the reflected {@code filter}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Dilation2d.OP_NAME, @@ -152,13 +150,13 @@ public static class Inputs extends RawOpInputs> /** * The stride of the sliding window for each dimension of the input - * tensor. Must be: `[1, stride_height, stride_width, 1]`. + * tensor. Must be: {@code [1, stride_height, stride_width, 1]}. */ public final long[] strides; /** * The input stride for atrous morphological dilation. Must be: - * `[1, rate_height, rate_width, 1]`. + * {@code [1, rate_height, rate_width, 1]}. */ public final long[] rates; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java index b88393b8e73..cae841aee0d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Dilation2dBackpropFilter.java @@ -36,8 +36,6 @@ /** * Computes the gradient of morphological 2-D dilation with respect to the filter. - * - * @param data type for {@code filter_backprop} output */ @OpMetadata( opType = Dilation2dBackpropFilter.OP_NAME, @@ -139,13 +137,13 @@ public static class Inputs extends RawOpInputs data type for {@code in_backprop} output */ @OpMetadata( opType = Dilation2dBackpropInput.OP_NAME, @@ -139,13 +137,13 @@ public static class Inputs extends RawOpInputs *

    See Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) * - * - * @param data type for {@code activations} output */ @OpMetadata( opType = Elu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java index 2df99ce5c8f..4d32b6d365f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/EluGrad.java @@ -35,8 +35,6 @@ /** * Computes gradients for the exponential linear (Elu) operation. - * - * @param data type for {@code backprops} output */ @OpMetadata( opType = EluGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java index fda9bdd66ae..bb525aac295 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPool.java @@ -41,8 +41,6 @@ * region generation step. The only difference is that after pooling regions are * generated, a mean operation is performed instead of a max operation in each * pooling region. - * - * @param data type for {@code output} output */ @OpMetadata( opType = FractionalAvgPool.OP_NAME, @@ -304,8 +302,8 @@ public static class Inputs extends RawOpInputs value; /** - * Pooling ratio for each dimension of `value`, currently only - * supports row and col dimension and should be >= 1.0. For example, a valid + * Pooling ratio for each dimension of {@code value}, currently only + * supports row and col dimension and should be >= 1.0. For example, a valid * pooling ratio looks like [1.0, 1.44, 1.73, 1.0]. The first and last elements * must be 1.0 because we don't allow pooling on batch and channels * dimensions. 1.44 and 1.73 are pooling ratio on height and width dimensions @@ -315,8 +313,8 @@ public static class Inputs extends RawOpInputsBenjamin + * Graham, Fractional Max-Pooling for * difference between pseudorandom and random. */ public final boolean pseudoRandom; @@ -324,12 +322,9 @@ public static class Inputs extends RawOpInputs{@code index 0 1 2 3 4} + *

    {@code value 20 5 16 3 7} + *

    If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice. * The result would be [41/3, 26/3] for fractional avg pooling. */ public final boolean overlapping; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java index 952b982148b..eee42886ab1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalAvgPoolGrad.java @@ -41,8 +41,6 @@ * out_backprop to those indices that form the same pooling cell. Therefore, we * just need to know the shape of original input tensor, instead of the whole * tensor. - * - * @param data type for {@code output} output */ @OpMetadata( opType = FractionalAvgPoolGrad.OP_NAME, @@ -186,12 +184,9 @@ public static class Inputs extends RawOpInputs{@code index 0 1 2 3 4} + *

    {@code value 20 5 16 3 7} + *

    If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice. * The result would be [41/3, 26/3] for fractional avg pooling. */ public final boolean overlapping; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java index fdbe02fc4ed..08bcbd1a63d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPool.java @@ -63,8 +63,6 @@ * *

    For more details on fractional max pooling, see this paper: * Benjamin Graham, Fractional Max-Pooling - * - * @param data type for {@code output} output */ @OpMetadata( opType = FractionalMaxPool.OP_NAME, @@ -326,8 +324,8 @@ public static class Inputs extends RawOpInputs value; /** - * Pooling ratio for each dimension of `value`, currently only - * supports row and col dimension and should be >= 1.0. For example, a valid + * Pooling ratio for each dimension of {@code value}, currently only + * supports row and col dimension and should be >= 1.0. For example, a valid * pooling ratio looks like [1.0, 1.44, 1.73, 1.0]. The first and last elements * must be 1.0 because we don't allow pooling on batch and channels * dimensions. 1.44 and 1.73 are pooling ratio on height and width dimensions @@ -337,8 +335,8 @@ public static class Inputs extends RawOpInputsBenjamin + * Graham, Fractional Max-Pooling for * difference between pseudorandom and random. */ public final boolean pseudoRandom; @@ -346,12 +344,9 @@ public static class Inputs extends RawOpInputs{@code index 0 1 2 3 4} + *

    {@code value 20 5 16 3 7} + *

    If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice. * The result would be [20, 16] for fractional max pooling. */ public final boolean overlapping; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java index c77591034a8..d44e062ccf7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FractionalMaxPoolGrad.java @@ -36,8 +36,6 @@ /** * Computes gradient of the FractionalMaxPool function. - * - * @param data type for {@code output} output */ @OpMetadata( opType = FractionalMaxPoolGrad.OP_NAME, @@ -188,12 +186,9 @@ public static class Inputs extends RawOpInputs{@code index 0 1 2 3 4} + *

    {@code value 20 5 16 3 7} + *

    If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice. * The result would be [20, 16] for fractional max pooling. */ public final boolean overlapping; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java index 50a39f70b02..f5cede8855e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNorm.java @@ -37,10 +37,6 @@ * Batch normalization. * Note that the size of 4D Tensors are defined by either "NHWC" or "NCHW". * The size of 1D Tensors matches the dimension C of the 4D Tensors. - * - * @param data type for {@code y} output - * - * @param data type for {@code batch_mean} output */ @OpMetadata( opType = FusedBatchNorm.OP_NAME, @@ -338,7 +334,7 @@ public static class Inputs extends RawOpIn public final float exponentialAvgFactor; /** - * The data format for x and y. Either "NHWC" (default) or "NCHW". + * The data format for x and y. Either "NHWC" (default) or "NCHW". */ public final String dataFormat; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java index d6094f54d10..985249a19fe 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedBatchNormGrad.java @@ -38,10 +38,6 @@ * Gradient for batch normalization. * Note that the size of 4D Tensors are defined by either "NHWC" or "NCHW". * The size of 1D Tensors matches the dimension C of the 4D Tensors. - * - * @param data type for {@code x_backprop} output - * - * @param data type for {@code scale_backprop} output */ @OpMetadata( opType = FusedBatchNormGrad.OP_NAME, @@ -316,7 +312,7 @@ public static class Inputs extends RawOpIn /** * The data format for y_backprop, x, x_backprop. - * Either "NHWC" (default) or "NCHW". + * Either "NHWC" (default) or "NCHW". */ public final String dataFormat; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java index aad10b64fea..336419f92ad 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/FusedPadConv2d.java @@ -48,8 +48,6 @@ * Internally this op uses a single per-graph scratch buffer, which means that it * will block if multiple versions are being run in parallel. This is because this * operator is primarily an optimization to minimize memory usage. - * - * @param data type for {@code output} output */ @OpMetadata( opType = FusedPadConv2d.OP_NAME, @@ -155,7 +153,7 @@ public static class Inputs extends RawOpInputs data type for {@code output} output */ @OpMetadata( opType = FusedResizeAndPadConv2d.OP_NAME, @@ -210,7 +208,7 @@ public static class Inputs extends RawOpInputs - * - * @param data type for {@code r} output */ @OpMetadata( opType = GRUBlockCell.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java index 108aa910427..7379a2790ba 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/GRUBlockCellGrad.java @@ -108,8 +108,6 @@ * * d_b_c = sum of d_c_bar along axis = 0 * - * - * @param data type for {@code d_x} output */ @OpMetadata( opType = GRUBlockCellGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InvGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InvGrad.java index 37f66b92878..5f178f53e50 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InvGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/InvGrad.java @@ -37,8 +37,6 @@ * Computes the gradient for the inverse of {@code x} wrt its input. * Specifically, {@code grad = -dy * y*y}, where {@code y = 1/x}, and {@code dy} * is the corresponding input gradient. - * - * @param data type for {@code z} output */ @OpMetadata( opType = InvGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/IsotonicRegression.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/IsotonicRegression.java index 8936770d8b7..ecd511253e8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/IsotonicRegression.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/IsotonicRegression.java @@ -38,8 +38,6 @@ /** * Solves a batch of isotonic regression problems. - * - * @param data type for {@code output} output */ @OpMetadata( opType = IsotonicRegression.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java index e3b179e440c..9cc952c05cb 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/L2Loss.java @@ -39,8 +39,6 @@ * 

      * output = sum(t ** 2) / 2
  *
    - * - * @param data type for {@code output} output */ @OpMetadata( opType = L2Loss.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java index 12d4402e70f..5b1e38d3fbe 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCell.java @@ -57,8 +57,6 @@ * co = tanh(cs) * h = co .* o * - * - * @param data type for {@code i} output */ @OpMetadata( opType = LSTMBlockCell.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java index e22e2241718..931e4bf2381 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LSTMBlockCellGrad.java @@ -36,8 +36,6 @@ /** * Computes the LSTM cell backward propagation for 1 timestep. * This implementation is to be used in conjunction of LSTMBlockCell. - * - * @param data type for {@code cs_prev_grad} output */ @OpMetadata( opType = LSTMBlockCellGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java index 022b81f82da..a0f088f9a03 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LeakyRelu.java @@ -35,8 +35,6 @@ /** * Computes rectified linear: {@code max(features, features * alpha)}. - * - * @param data type for {@code activations} output */ @OpMetadata( opType = LeakyRelu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java index f0bb2b5017b..17c1e5c0d04 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalization.java @@ -46,8 +46,6 @@ * *

    For details, see Krizhevsky et al., ImageNet classification with deep * convolutional neural networks (NIPS 2012) . - * - * @param data type for {@code output} output */ @OpMetadata( opType = LocalResponseNormalization.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java index ebf451c2f9c..c0b795094aa 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LocalResponseNormalizationGrad.java @@ -35,8 +35,6 @@ /** * Gradients for Local Response Normalization. - * - * @param data type for {@code output} output */ @OpMetadata( opType = LocalResponseNormalizationGrad.OP_NAME, @@ -237,7 +235,7 @@ public static class Inputs extends RawOpInputs 0 to avoid dividing by 0). + * An offset (usually > 0 to avoid dividing by 0). */ public final float bias; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java index 1f9ee440140..1e19b56c19f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/LogSoftmax.java @@ -39,8 +39,6 @@ * 

      * logsoftmax[i, j] = logits[i, j] - log(sum(exp(logits[i])))
  *
    - * - * @param data type for {@code logsoftmax} output */ @OpMetadata( opType = LogSoftmax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool.java index b3dd99bd3bf..75b432b8ba3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool.java @@ -36,8 +36,6 @@ /** * Performs max pooling on the input. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MaxPool.OP_NAME, @@ -178,10 +176,10 @@ public static class Inputs extends RawOpInputs> { /** * Specify the data format of the input and output data. With the - * default format "NHWC", the data is stored in the order of: - * [batch, in_height, in_width, in_channels]. - * Alternatively, the format could be "NCHW", the data storage order of: - * [batch, in_channels, in_height, in_width]. + * default format "NHWC", the data is stored in the order of: + * [batch, in_height, in_width, in_channels]. + * Alternatively, the format could be "NCHW", the data storage order of: + * [batch, in_channels, in_height, in_width]. */ public final String dataFormat; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java index 5aacb5f1c17..d701189d5e1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3d.java @@ -36,8 +36,6 @@ /** * Performs 3D max pooling on the input. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MaxPool3d.OP_NAME, @@ -166,13 +164,13 @@ public static class Inputs extends RawOpInputs> /** * 1-D tensor of length 5. The size of the window for each dimension of - * the input tensor. Must have `ksize[0] = ksize[4] = 1`. + * the input tensor. Must have {@code ksize[0] = ksize[4] = 1}. */ public final long[] ksize; /** * 1-D tensor of length 5. The stride of the sliding window for each - * dimension of `input`. Must have `strides[0] = strides[4] = 1`. + * dimension of {@code input}. Must have {@code strides[0] = strides[4] = 1}. */ public final long[] strides; @@ -183,10 +181,10 @@ public static class Inputs extends RawOpInputs> /** * The data format of the input and output data. With the - * default format "NDHWC", the data is stored in the order of: - * [batch, in_depth, in_height, in_width, in_channels]. - * Alternatively, the format could be "NCDHW", the data storage order is: - * [batch, in_channels, in_depth, in_height, in_width]. + * default format "NDHWC", the data is stored in the order of: + * [batch, in_depth, in_height, in_width, in_channels]. + * Alternatively, the format could be "NCDHW", the data storage order is: + * [batch, in_channels, in_depth, in_height, in_width]. */ public final String dataFormat; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java index ac313f4d45a..932399be80b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGrad.java @@ -36,8 +36,6 @@ /** * Computes gradients of 3D max pooling function. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MaxPool3dGrad.OP_NAME, @@ -182,13 +180,13 @@ public static class Inputs extends RawOpIn /** * 1-D tensor of length 5. The size of the window for each dimension of - * the input tensor. Must have `ksize[0] = ksize[4] = 1`. + * the input tensor. Must have {@code ksize[0] = ksize[4] = 1}. */ public final long[] ksize; /** * 1-D tensor of length 5. The stride of the sliding window for each - * dimension of `input`. Must have `strides[0] = strides[4] = 1`. + * dimension of {@code input}. Must have {@code strides[0] = strides[4] = 1}. */ public final long[] strides; @@ -199,10 +197,10 @@ public static class Inputs extends RawOpIn /** * The data format of the input and output data. With the - * default format "NDHWC", the data is stored in the order of: - * [batch, in_depth, in_height, in_width, in_channels]. - * Alternatively, the format could be "NCDHW", the data storage order is: - * [batch, in_channels, in_depth, in_height, in_width]. + * default format "NDHWC", the data is stored in the order of: + * [batch, in_depth, in_height, in_width, in_channels]. + * Alternatively, the format could be "NCDHW", the data storage order is: + * [batch, in_channels, in_depth, in_height, in_width]. */ public final String dataFormat; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java index 585f30e5aa9..74dbc598b35 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPool3dGradGrad.java @@ -36,8 +36,6 @@ /** * Computes second-order gradients of the maxpooling function. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MaxPool3dGradGrad.OP_NAME, @@ -181,13 +179,13 @@ public static class Inputs extends RawOpInputs extends RawOpInputs data type for {@code output} output */ @OpMetadata( opType = MaxPoolGrad.OP_NAME, @@ -188,10 +186,10 @@ public static class Inputs extends RawOpInputs /** * Specify the data format of the input and output data. With the - * default format "NHWC", the data is stored in the order of: - * [batch, in_height, in_width, in_channels]. - * Alternatively, the format could be "NCHW", the data storage order of: - * [batch, in_channels, in_height, in_width]. + * default format "NHWC", the data is stored in the order of: + * [batch, in_height, in_width, in_channels]. + * Alternatively, the format could be "NCHW", the data storage order of: + * [batch, in_channels, in_height, in_width]. */ public final String dataFormat; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java index 7189844a8d6..0b0f0f616b7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/MaxPoolGradGrad.java @@ -36,8 +36,6 @@ /** * Computes second-order gradients of the maxpooling function. - * - * @param data type for {@code output} output */ @OpMetadata( opType = MaxPoolGradGrad.OP_NAME, @@ -188,10 +186,10 @@ public static class Inputs extends RawOpInputs data type for {@code output} output */ @OpMetadata( opType = MaxPoolGradGradWithArgmax.OP_NAME, @@ -189,7 +187,7 @@ public static class Inputs extends RawOpInputs data type for {@code output} output */ @OpMetadata( opType = MaxPoolGradWithArgmax.OP_NAME, @@ -189,7 +187,7 @@ public static class Inputs extends RawOpInputs data type for {@code output} output - * - * @param data type for {@code argmax} output */ @OpMetadata( opType = MaxPoolWithArgmax.OP_NAME, @@ -221,7 +217,7 @@ public static class Inputs extends RawOpInputs * values.shape = input.shape[:-1] * - * - * @param data type for {@code values} output */ @OpMetadata( opType = NthElement.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedAvgPool.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedAvgPool.java index 2e27d649947..8987fcd7d55 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedAvgPool.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedAvgPool.java @@ -37,8 +37,6 @@ /** * Produces the average pool of the input tensor for quantized types. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedAvgPool.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java index 0b9e3b27b55..7f22995509c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBatchNormWithGlobalNormalization.java @@ -39,8 +39,6 @@ * Quantized Batch normalization. * This op is deprecated and will be removed in the future. Prefer * {@code tf.nn.batch_normalization}. - * - * @param data type for {@code result} output */ @OpMetadata( opType = QuantizedBatchNormWithGlobalNormalization.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java index c95300fa493..744eb1397eb 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedBiasAdd.java @@ -38,8 +38,6 @@ /** * Adds Tensor 'bias' to Tensor 'input' for Quantized types. * Broadcasts the values of bias on dimensions 0..N-2 of 'input'. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedBiasAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java index 4594e0401cc..9226b7b697e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRelu.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DAndRelu operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DAndRelu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java index 0104cbf9908..f02eba09012 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndReluAndRequantize.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DAndReluAndRequantize operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DAndReluAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java index 5fe5999adab..66344508160 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DAndRequantize.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DAndRequantize operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java index 134449aba91..bfd108c34d3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DPerChannel.java @@ -38,8 +38,6 @@ /** * Computes QuantizedConv2D per channel. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DPerChannel.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java index 27f5343c6ff..fe5566ac7e9 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBias.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DWithBias operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DWithBias.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java index 61c9bb31b45..ff7d157a846 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRelu.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DWithBiasAndRelu operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DWithBiasAndRelu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java index 081b8ac3863..b68080cc72c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndReluAndRequantize.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DWithBiasAndReluAndRequantize operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DWithBiasAndReluAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java index 21f4eef7826..5301017e666 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasAndRequantize.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DWithBiasAndRequantize operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DWithBiasAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java index afdd8b87219..687e41485d4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DWithBiasSignedSumAndReluAndRequantize operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DWithBiasSignedSumAndReluAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java index d92782f88bb..34ceb6e7898 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndRelu.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DWithBiasSumAndRelu operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DWithBiasSumAndRelu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java index 0d9c4fab0f6..021873d6885 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2DWithBiasSumAndReluAndRequantize.java @@ -38,8 +38,6 @@ /** * The QuantizedConv2DWithBiasSumAndReluAndRequantize operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2DWithBiasSumAndReluAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java index ff2b1bb989a..77d21ba9794 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedConv2d.java @@ -42,8 +42,6 @@ * number of the associated minimum, and the highest represents the maximum. * This means that you can only interpret the quantized output in the same way, by * taking the returned minimum and maximum values into account. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConv2d.OP_NAME, @@ -283,9 +281,9 @@ public static class Inputs extends RawOpInputs> { /** * 1-D tensor of length 4. The dilation factor for each dimension of - * `input`. If set to k > 1, there will be k-1 skipped cells between each + * {@code input}. If set to k > 1, there will be k-1 skipped cells between each * filter element on that dimension. The dimension order is determined by the - * value of `data_format`, see above for details. Dilations in the batch and + * value of {@code data_format}, see above for details. Dilations in the batch and * depth dimensions must be 1. */ public final long[] dilations; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java index 19c05799f1f..3281b31698b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2D.java @@ -38,8 +38,6 @@ /** * Computes quantized depthwise Conv2D. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedDepthwiseConv2D.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java index 9414fd9e015..70314ace0b0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBias.java @@ -38,8 +38,6 @@ /** * Computes quantized depthwise Conv2D with Bias. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedDepthwiseConv2DWithBias.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java index c8d6a30445b..76b0917f709 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndRelu.java @@ -38,8 +38,6 @@ /** * Computes quantized depthwise Conv2D with Bias and Relu. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedDepthwiseConv2DWithBiasAndRelu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java index b23311716d2..55dfdecdb39 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.java @@ -38,8 +38,6 @@ /** * Computes quantized depthwise Conv2D with Bias, Relu and Requantize. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedInstanceNorm.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedInstanceNorm.java index af8f32f2353..48aedde6806 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedInstanceNorm.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedInstanceNorm.java @@ -36,8 +36,6 @@ /** * Quantized Instance normalization. - * - * @param data type for {@code y} output */ @OpMetadata( opType = QuantizedInstanceNorm.OP_NAME, @@ -287,19 +285,19 @@ public static class Inputs extends RawOpInputs extends RawOpInputs data type for {@code output} output */ @OpMetadata( opType = QuantizedMaxPool.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java index b80e07346d9..ad55085ab6f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu.java @@ -37,8 +37,6 @@ /** * Computes Quantized Rectified Linear: {@code max(features, 0)} - * - * @param data type for {@code activations} output */ @OpMetadata( opType = QuantizedRelu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java index d820e51188a..2b2f21a6b45 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedRelu6.java @@ -37,8 +37,6 @@ /** * Computes Quantized Rectified Linear 6: {@code min(max(features, 0), 6)} - * - * @param data type for {@code activations} output */ @OpMetadata( opType = QuantizedRelu6.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java index 577df61b8dd..41daae389b6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/QuantizedReluX.java @@ -37,8 +37,6 @@ /** * Computes Quantized Rectified Linear X: {@code min(max(features, 0), max_value)} - * - * @param data type for {@code activations} output */ @OpMetadata( opType = QuantizedReluX.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu.java index 218fee4f3d2..126eb0c4c56 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu.java @@ -45,8 +45,6 @@ * * * - * - * @param data type for {@code activations} output */ @OpMetadata( opType = Relu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java index 19de03d7f8e..5500229b21c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6.java @@ -35,8 +35,6 @@ /** * Computes rectified linear 6: {@code min(max(features, 0), 6)}. - * - * @param data type for {@code activations} output */ @OpMetadata( opType = Relu6.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java index 48ec9cb7037..9af8b816d87 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Relu6Grad.java @@ -35,8 +35,6 @@ /** * Computes rectified linear 6 gradients for a Relu6 operation. - * - * @param data type for {@code backprops} output */ @OpMetadata( opType = Relu6Grad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java index 5e7103853f3..b15132dd583 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/ReluGrad.java @@ -35,8 +35,6 @@ /** * Computes rectified linear gradients for a Relu operation. - * - * @param data type for {@code backprops} output */ @OpMetadata( opType = ReluGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java index d382a2f5a75..33d504105ec 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Selu.java @@ -40,8 +40,6 @@ * {@code initializer = tf.variance_scaling_initializer(factor=1.0, mode='FAN_IN')}. * For correct dropout, use {@code tf.contrib.nn.alpha_dropout}. *

    See Self-Normalizing Neural Networks - * - * @param data type for {@code activations} output */ @OpMetadata( opType = Selu.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java index 7a2e0656275..bd2d2203f69 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SeluGrad.java @@ -35,8 +35,6 @@ /** * Computes gradients for the scaled exponential linear (Selu) operation. - * - * @param data type for {@code backprops} output */ @OpMetadata( opType = SeluGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java index 36ef20f21fd..dd6b9ecb2b5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softmax.java @@ -39,8 +39,6 @@ * 

      * $$softmax[i, j] = exp(logits[i, j]) / sum_j(exp(logits[i, j]))$$
  *
    - * - * @param data type for {@code softmax} output */ @OpMetadata( opType = Softmax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java index 9a17188c048..a7836f24051 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftmaxCrossEntropyWithLogits.java @@ -36,8 +36,6 @@ /** * Computes softmax cross entropy cost and gradients to backpropagate. * Inputs are the logits, not probabilities. - * - * @param data type for {@code loss} output */ @OpMetadata( opType = SoftmaxCrossEntropyWithLogits.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java index 1345a1ffd11..1144c4c21be 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/Softsign.java @@ -35,8 +35,6 @@ /** * Computes softsign: {@code features / (abs(features) + 1)}. - * - * @param data type for {@code activations} output */ @OpMetadata( opType = Softsign.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java index b16c933ffe0..3ebe407b08e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SoftsignGrad.java @@ -35,8 +35,6 @@ /** * Computes softsign gradients for a softsign operation. - * - * @param data type for {@code backprops} output */ @OpMetadata( opType = SoftsignGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToBatch.java index 050a12e7f98..e35f65ee574 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToBatch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToBatch.java @@ -100,8 +100,6 @@ * *

    Among others, this operation is useful for reducing atrous convolution into * regular convolution. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SpaceToBatch.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToDepth.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToDepth.java index 18449c4627c..aaaddf55663 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToDepth.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SpaceToDepth.java @@ -103,8 +103,6 @@ * [[9, 10, 11, 12], * [13, 14, 15, 16]]]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SpaceToDepth.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java index 043587de9b5..1b7c99a694e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/SparseSoftmaxCrossEntropyWithLogits.java @@ -40,8 +40,6 @@ * of features. This label is considered to have probability 1.0 for the * given row. *

    Inputs are the logits, not probabilities. - * - * @param data type for {@code loss} output */ @OpMetadata( opType = SparseSoftmaxCrossEntropyWithLogits.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java index 49552b20020..189f0434054 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/TopK.java @@ -46,10 +46,6 @@ * values.shape = indices.shape = input.shape[:-1] + [k] * *

    If two elements are equal, the lower-index element appears first. - * - * @param data type for {@code values} output - * - * @param data type for {@code indices} output */ @OpMetadata( opType = TopK.OP_NAME, @@ -193,7 +189,7 @@ public static class Inputs extends RawOpInputs> { public final Operand k; /** - * If true the resulting `k` elements will be sorted by the values in + * If true the resulting {@code k} elements will be sorted by the values in * descending order. */ public final boolean sorted; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolution.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolution.java index bcc2dec4789..124c2b062f0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolution.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolution.java @@ -55,8 +55,6 @@ * *

    {@code output} is also quantized, using the same formula. * If {@code rhs} is per-tensor quantized, {@code output} must be also per-tensor quantized. - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformQuantizedConvolution.OP_NAME, @@ -677,132 +675,131 @@ public static class Inputs extends RawOpInputs outputZeroPoints; /** - * The type of `lhs` and `rhs` input `Tensor`. + * The type of {@code lhs} and {@code rhs} input {@code Tensor}. */ public final DataType Tin; /** - * The type of `output` `Tensor`. + * The type of {@code output} {@code Tensor}. */ public final DataType Tout; /** - * The stride of the sliding window for each spatial dimension of `lhs`. + * The stride of the sliding window for each spatial dimension of {@code lhs}. * Must be an empty list (default) or a list of size (number of spatial dimensions). * If an empty list is provided, the stride for each spatial dimension is set to 1. */ public final long[] windowStrides; /** - * string from: `"SAME"`, `"VALID"`, or `"EXPLICIT"`, indicating the type of padding algorithm to use. + * string from: {@code "SAME"}, {@code "VALID"}, or {@code "EXPLICIT"}, indicating the type of padding algorithm to use. */ public final String padding; /** - * If `padding` is `"EXPLICIT"`, must be set as a list indicating - * the explicit paddings at the start and end of each `lhs` spatial dimension. + * If {@code padding} is {@code "EXPLICIT"}, must be set as a list indicating + * the explicit paddings at the start and end of each {@code lhs} spatial dimension. * Otherwise, this must be empty. - * - * (If used,) Must be a list of size `2 * (number of lhs spatial dimensions)`, - * where `(explicit_padding[2 * i], explicit_padding[2 * i + 1])` indicates - * `(start_padding, end_padding)` of `spatial_dimensions[i]`. + *

    (If used,) Must be a list of size {@code 2 * (number of lhs spatial dimensions)}, + * where {@code (explicit_padding[2 * i], explicit_padding[2 * i + 1])} indicates + * {@code (start_padding, end_padding)} of {@code spatial_dimensions[i]}. */ public final long[] explicitPadding; /** - * The dilation factor to apply in each spatial dimension of `lhs`. - * Must be an empty list (default) or a list of size (number of `lhs` spatial dimensions). - * If empty list, the dilation for each `lhs` spatial dimension is set to 1. + * The dilation factor to apply in each spatial dimension of {@code lhs}. + * Must be an empty list (default) or a list of size (number of {@code lhs} spatial dimensions). + * If empty list, the dilation for each {@code lhs} spatial dimension is set to 1. */ public final long[] lhsDilation; /** - * The dilation factor to apply in each spatial dimension of `rhs`. - * Must be an empty list (default) or a list of size (number of `rhs` spatial dimensions). - * If empty list, the dilation for each `rhs` spatial dimension is set to 1. + * The dilation factor to apply in each spatial dimension of {@code rhs}. + * Must be an empty list (default) or a list of size (number of {@code rhs} spatial dimensions). + * If empty list, the dilation for each {@code rhs} spatial dimension is set to 1. */ public final long[] rhsDilation; /** * The number of batch groups. Used for grouped filters. - * Must be a divisor of `output_feature`. + * Must be a divisor of {@code output_feature}. */ public final long batchGroupCount; /** * The number of feature groups. Used for grouped convolutions. - * Must be a divisor of both `lhs_feature` and `output_feature`. + * Must be a divisor of both {@code lhs_feature} and {@code output_feature}. */ public final long featureGroupCount; /** * Structure of dimension information for the convolution op. - * Must be an empty string (default) or a serialized string of `tensorflow.UniformQuantizedConvolutionDimensionNumbersAttr` proto. - * If empty string, the default is `("NCHW", "OIHW", "NCHW")` (for a 2D convolution). + * Must be an empty string (default) or a serialized string of {@code tensorflow.UniformQuantizedConvolutionDimensionNumbersAttr} proto. + * If empty string, the default is {@code ("NCHW", "OIHW", "NCHW")} (for a 2D convolution). */ public final String dimensionNumbers; /** * Indicates the dimension index of the tensor where per-axis quantization is applied for the slices along that dimension. * If set to -1 (default), this indicates per-tensor quantization. - * For the `lhs`, only per-tensor quantization is supported. + * For the {@code lhs}, only per-tensor quantization is supported. * Thus, this must be set to -1. * Other values will raise error at OpKernel construction. */ public final long lhsQuantizationAxis; /** - * The min value of the quantized data stored in `lhs`. - * For example, if `Tin` is `qint8`, this must be set to -127 if narrow range quantized or -128 if not. + * The min value of the quantized data stored in {@code lhs}. + * For example, if {@code Tin} is {@code qint8}, this must be set to -127 if narrow range quantized or -128 if not. */ public final long lhsQuantizationMinVal; /** - * The max value of the quantized data stored in `lhs`. - * For example, if `Tin` is `qint8`, this must be set to 127. + * The max value of the quantized data stored in {@code lhs}. + * For example, if {@code Tin} is {@code qint8}, this must be set to 127. */ public final long lhsQuantizationMaxVal; /** * Indicates the dimension index of the tensor where per-axis quantization is applied for the slices along that dimension. * If set to -1 (default), this indicates per-tensor quantization. - * For the `rhs`, only per-tensor quantization - * or per-channel quantization along `kernel_output_feature_dimension` is supported. - * Thus, this must be set to -1 or `dimension_numbers.kernel_output_feature_dimension`. + * For the {@code rhs}, only per-tensor quantization + * or per-channel quantization along {@code kernel_output_feature_dimension} is supported. + * Thus, this must be set to -1 or {@code dimension_numbers.kernel_output_feature_dimension}. * Other values will raise error at OpKernel construction. */ public final long rhsQuantizationAxis; /** - * The min value of the quantized data stored in `rhs`. - * For example, if `Tin` is `qint8`, this must be set to -127 if narrow range quantized or -128 if not. + * The min value of the quantized data stored in {@code rhs}. + * For example, if {@code Tin} is {@code qint8}, this must be set to -127 if narrow range quantized or -128 if not. */ public final long rhsQuantizationMinVal; /** - * The max value of the quantized data stored in `rhs`. - * For example, if `Tin` is `qint8`, this must be set to 127. + * The max value of the quantized data stored in {@code rhs}. + * For example, if {@code Tin} is {@code qint8}, this must be set to 127. */ public final long rhsQuantizationMaxVal; /** * Indicates the dimension index of the tensor where per-axis quantization is applied for the slices along that dimension. * If set to -1 (default), this indicates per-tensor quantization. - * For the `output`, only per-tensor quantization or per-channel quantization along `output_feature_dimension` is supported. - * Thus, this must be set to -1 or `dimension_numbers.output_feature_dimension`. + * For the {@code output}, only per-tensor quantization or per-channel quantization along {@code output_feature_dimension} is supported. + * Thus, this must be set to -1 or {@code dimension_numbers.output_feature_dimension}. * Other values will raise error at OpKernel construction. */ public final long outputQuantizationAxis; /** - * The min value of the quantized data stored in `output`. - * For example, if `Tout` is `qint8`, this must be set to -127 if narrow range quantized or -128 if not. + * The min value of the quantized data stored in {@code output}. + * For example, if {@code Tout} is {@code qint8}, this must be set to -127 if narrow range quantized or -128 if not. */ public final long outputQuantizationMinVal; /** - * The max value of the quantized data stored in `output`. - * For example, if `Tout` is `qint8`, this must be set to 127. + * The max value of the quantized data stored in {@code output}. + * For example, if {@code Tout} is {@code qint8}, this must be set to 127. */ public final long outputQuantizationMaxVal; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolutionHybrid.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolutionHybrid.java index 80d0d92a223..8510272759e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolutionHybrid.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/nn/UniformQuantizedConvolutionHybrid.java @@ -55,8 +55,6 @@ * *

    {@code rhs} must be quantized Tensor, where its data value is quantized using the formula: * quantized_data = clip(original_data / scale + zero_point, quantization_min_val, quantization_max_val). - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformQuantizedConvolutionHybrid.OP_NAME, @@ -544,12 +542,12 @@ public static class Inputs extends RawOpInputs rhsZeroPoints; /** - * The type of `lhs` input Tensor. + * The type of {@code lhs} input Tensor. */ public final DataType Tlhs; /** - * The type of `rhs` (quantized) input Tensor. + * The type of {@code rhs} (quantized) input Tensor. */ public final DataType Trhs; @@ -559,37 +557,36 @@ public static class Inputs extends RawOpInputs(If used,) Must be a list of size 2 * (number of lhs spatial dimensions), * where (explicit_padding[2 * i], explicit_padding[2 * i + 1]) indicates * spatial_dimensions[i] (start_padding, end_padding). */ public final long[] explicitPadding; /** - * The dilation factor to apply in each spatial dimension of `lhs`. + * The dilation factor to apply in each spatial dimension of {@code lhs}. * Must be an empty list (default) or a list of size (number of lhs spatial dimensions). * If empty list, the dilation for each lhs spatial dimension is set to 1. */ public final long[] lhsDilation; /** - * The dilation factor to apply in each spatial dimension of `rhs`. + * The dilation factor to apply in each spatial dimension of {@code rhs}. * Must be an empty list (default) or a list of size (number of rhs spatial dimensions). * If empty list, the dilation for each rhs spatial dimension is set to 1. */ @@ -610,29 +607,29 @@ public static class Inputs extends RawOpInputs - * - * @param data type for {@code output} output */ @OpMetadata( opType = Dequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java index a6a5df07a8a..ed34d301ec7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Quantize.java @@ -128,8 +128,6 @@ *

    Ensures the minimum quantization range is at least this value. * The legacy default value for this is 0.01, but it is strongly suggested to * set it to 0 for new uses. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Quantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java index b6552257828..eeb9f05536c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantize.java @@ -38,8 +38,6 @@ * Quantizes then dequantizes a tensor. * This is almost identical to QuantizeAndDequantizeV2, except that num_bits is a * tensor, so its value can change during training. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizeAndDequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV3.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV3.java index a715ecdb8e5..e1de6cd2ab7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV3.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV3.java @@ -38,8 +38,6 @@ * Quantizes then dequantizes a tensor. * This is almost identical to QuantizeAndDequantizeV2, except that num_bits is a * tensor, so its value can change during training. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizeAndDequantizeV3.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4.java index 161eae5c2f2..7de2e59c64b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4.java @@ -37,8 +37,6 @@ * Quantizes then dequantizes a tensor. * This is almost identical to QuantizeAndDequantizeV2, except that it returns a * gradient of 1 for inputs that are within the quantization range, or 0 otherwise. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizeAndDequantizeV4.OP_NAME, @@ -114,7 +112,7 @@ public static QuantizeAndDequantizeV4 create(Scope scope, * Sets the signedInput option. * * @param signedInput Whether the quantization is signed or unsigned. (actually this parameter should - * have been called {@code signed_output}</b>) + * have been called {@code signed_output}) * @return this Options instance. */ public static Options signedInput(Boolean signedInput) { @@ -218,7 +216,7 @@ private Options() { * Sets the signedInput option. * * @param signedInput Whether the quantization is signed or unsigned. (actually this parameter should - * have been called {@code signed_output}</b>) + * have been called {@code signed_output}) * @return this Options instance. */ public Options signedInput(Boolean signedInput) { @@ -317,7 +315,7 @@ public static class Inputs extends RawOpInputs`signed_output`) + * have been called {@code signed_output}) */ public final boolean signedInput; @@ -327,7 +325,7 @@ public static class Inputs extends RawOpInputs extends RawOpInputs + *

  • HALF_TO_EVEN: this is the default round_mode.
    • + *
  • HALF_UP: round towards positive. In this mode 7.5 rounds up to 8 and -7.5 + * rounds up to -7.
    • + * */ public final String roundMode; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4Grad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4Grad.java index d2d9d9e6035..65cf77c43ca 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4Grad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeAndDequantizeV4Grad.java @@ -37,8 +37,6 @@ * Returns the gradient of {@code QuantizeAndDequantizeV4}. * Returns a gradient of 1 for inputs that are within the quantization range, * or 0 otherwise. - * - * @param data type for {@code input_backprop} output */ @OpMetadata( opType = QuantizeAndDequantizeV4Grad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java index d8aee82efb2..77aaa257758 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizeDownAndShrinkRange.java @@ -56,8 +56,6 @@ * input values that only uses a small fraction of the possible range. By feeding * that output into this operator, we can reduce it from 32 bits down to 8 with * minimal loss of accuracy. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizeDownAndShrinkRange.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedConcat.java index cae65990d35..a52e49b8080 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedConcat.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedConcat.java @@ -38,8 +38,6 @@ /** * Concatenates quantized tensors along one dimension. - * - * @param data type for {@code output} output */ @OpMetadata( opType = QuantizedConcat.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java index 69827ccd019..c03a82caf5c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndDequantize.java @@ -37,8 +37,6 @@ /** * The QuantizedMatMulWithBiasAndDequantize operation - * - * @param data type for {@code out} output */ @OpMetadata( opType = QuantizedMatMulWithBiasAndDequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java index cd48b07ac48..b848d068a15 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/QuantizedMatMulWithBiasAndRequantize.java @@ -37,8 +37,6 @@ /** * The QuantizedMatMulWithBiasAndRequantize operation - * - * @param data type for {@code out} output */ @OpMetadata( opType = QuantizedMatMulWithBiasAndRequantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java index 48bfa78ab74..0ebd2ce0e3a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/Requantize.java @@ -43,8 +43,6 @@ * interpretation of the {@code input} data. For example, if {@code input_min} is -1.0f and * {@code input_max} is 1.0f, and we are dealing with {@code quint16} quantized data, then a 0 * value in the 16-bit data should be interpreted as -1.0f, and a 65535 means 1.0f. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Requantize.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformDequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformDequantize.java index d9d5594ae49..8f5d44bf663 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformDequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformDequantize.java @@ -40,8 +40,6 @@ * Perform dequantization on the quantized Tensor {@code input}. * Given quantized {@code input} which was quantized using {@code scales} and {@code zero_points}, performs dequantization using the formula: * dequantized_data = (quantized_data - zero_point) * scale. - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformDequantize.OP_NAME, @@ -196,7 +194,7 @@ public static class Inputs extends RawOpInputs> { /** * The quantization min value that was used when input was quantized. * The purpose of this attribute is typically (but not limited to) to indicate narrow range, where this is set to: - * `(Tin lowest) + 1` if narrow range, and `(Tin lowest)` otherwise. + * {@code (Tin lowest) + 1} if narrow range, and {@code (Tin lowest)} otherwise. * For example, if Tin is qint8, this is set to -127 if narrow range quantized or -128 if not. */ public final long quantizationMinVal; @@ -204,7 +202,7 @@ public static class Inputs extends RawOpInputs> { /** * The quantization max value that was used when input was quantized. * The purpose of this attribute is typically (but not limited to) indicate narrow range, where this is set to: - * `(Tout max)` for both narrow range and not narrow range. + * {@code (Tout max)} for both narrow range and not narrow range. * For example, if Tin is qint8, this is set to 127. */ public final long quantizationMaxVal; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantize.java index fd5f44970be..390ceb83d8a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantize.java @@ -40,8 +40,6 @@ * Perform quantization on Tensor {@code input}. * Given {@code input}, {@code scales} and {@code zero_points}, performs quantization using the formula: * quantized_data = floor(input_data * (1.0f / scale) + 0.5f) + zero_point - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformQuantize.OP_NAME, @@ -194,17 +192,17 @@ public static class Inputs extends RawOpInputs> { public final long quantizationAxis; /** - * The quantization min value to quantize `input`. + * The quantization min value to quantize {@code input}. * The purpose of this attribute is typically (but not limited to) to indicate narrow range, where this is set to: - * `(Tin lowest) + 1` if narrow range, and `(Tin lowest)` otherwise. + * {@code (Tin lowest) + 1} if narrow range, and {@code (Tin lowest)} otherwise. * For example, if Tin is qint8, this is set to -127 if narrow range quantized or -128 if not. */ public final long quantizationMinVal; /** - * The quantization max value to quantize `input`. + * The quantization max value to quantize {@code input}. * The purpose of this attribute is typically (but not limited to) indicate narrow range, where this is set to: - * `(Tout max)` for both narrow range and not narrow range. + * {@code (Tout max)} for both narrow range and not narrow range. * For example, if Tin is qint8, this is set to 127. */ public final long quantizationMaxVal; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDot.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDot.java index 16768a99b22..eff33c22ce7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDot.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDot.java @@ -44,8 +44,6 @@ * quantized_data = clip(original_data / scale + zero_point, quantization_min_val, quantization_max_val). * {@code output} is also quantized, using the same formula. * If {@code rhs} is per-tensor quantized, {@code output} must be also per-tensor quantized. - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformQuantizedDot.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDotHybrid.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDotHybrid.java index ed8c67f9a53..1f30f7a1a4c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDotHybrid.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformQuantizedDotHybrid.java @@ -43,8 +43,6 @@ * {@code lhs} and {@code rhs} must be 2D Tensors and the lhs.dim_size(1) must match rhs.dim_size(0). * {@code rhs} must be quantized Tensor, where its data value is quantized using the formula: * quantized_data = clip(original_data / scale + zero_point, quantization_min_val, quantization_max_val). - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformQuantizedDotHybrid.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformRequantize.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformRequantize.java index c1ef14c7ae7..eb4c511b567 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformRequantize.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/quantization/UniformRequantize.java @@ -52,8 +52,6 @@ *
  • per-axis -> per-axis where input_quantization_axis equals output_quantization_axis. * i.e. At least one among input_quantization_axis and output_quantization_axis must be -1, or two must be equal.
    • * - * - * @param data type for {@code output} output */ @OpMetadata( opType = UniformRequantize.OP_NAME, @@ -253,40 +251,40 @@ public static class Inputs extends RawOpInputs> { public final DataType Tout; /** - * The quantization axis that was used when quantizing original data that `input` represents. + * The quantization axis that was used when quantizing original data that {@code input} represents. * Indicates the dimension index of the tensor where per-axis quantization is applied for the slices along that dimension. * If set to -1 (default), this indicates per-tensor quantization. Otherwise, it must be set within range [0, input.dims()). */ public final long inputQuantizationAxis; /** - * The quantization min value that was used when quantizing original data that `input` represents. + * The quantization min value that was used when quantizing original data that {@code input} represents. * The purpose of this attribute is typically (but not limited to) to indicate narrow range, where this is set to: - * `(Tin lowest) + 1` if narrow range, and `(Tin lowest)` otherwise. + * {@code (Tin lowest) + 1} if narrow range, and {@code (Tin lowest)} otherwise. * For example, if Tin is qint8, this is set to -127 if narrow range quantized or -128 if not. */ public final long inputQuantizationMinVal; /** - * The quantization max value that was used when quantizing original data that `input` represents. + * The quantization max value that was used when quantizing original data that {@code input} represents. * The purpose of this attribute is typically (but not limited to) indicate narrow range, where this is set to: - * `(Tout max)` for both narrow range and not narrow range. + * {@code (Tout max)} for both narrow range and not narrow range. * For example, if Tin is qint8, this is set to 127. */ public final long inputQuantizationMaxVal; /** - * The new quantization axis to use to quantize original data that `input` represents. + * The new quantization axis to use to quantize original data that {@code input} represents. */ public final long outputQuantizationAxis; /** - * The new quantization min value to quantize original data that `input` represents. + * The new quantization min value to quantize original data that {@code input} represents. */ public final long outputQuantizationMinVal; /** - * The new quantization max value to quantize original data that `input` represents. + * The new quantization max value to quantize original data that {@code input} represents. */ public final long outputQuantizationMaxVal; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java index 2607b8e0fcf..0aadded3990 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedBincount.java @@ -42,8 +42,6 @@ * the value in {@code weights} at each index where the corresponding value in {@code arr} is * {@code i}. *

    Values in {@code arr} outside of the range [0, size) are ignored. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RaggedBincount.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java index 1e654d1665b..720919e6873 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCountSparseOutput.java @@ -37,8 +37,6 @@ /** * Performs sparse-output bin counting for a ragged tensor input. * Counts the number of times each value occurs in the input. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = RaggedCountSparseOutput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java index 816bdc2b4d2..3b356804b4f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedCross.java @@ -39,10 +39,6 @@ /** * Generates a feature cross from a list of tensors, and returns it as a * RaggedTensor. See {@code tf.ragged.cross} for more details. - * - * @param data type for {@code output_values} output - * - * @param data type for {@code output_row_splits} output */ @OpMetadata( opType = RaggedCross.OP_NAME, @@ -169,8 +165,8 @@ public static class Inputs extends RawOpInputs> { public final Iterable> denseInputs; /** - * String specifying the tensor type for each input. The `i`th character in - * this string specifies the type of the `i`th input, and is one of: 'R' (ragged), + * String specifying the tensor type for each input. The {@code i}th character in + * this string specifies the type of the {@code i}th input, and is one of: 'R' (ragged), * 'D' (dense), or 'S' (sparse). This attr is used to ensure that the crossed * values are combined in the order of the inputs from the call to tf.ragged.cross. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRows.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRows.java index 5f1b9cf66ec..d8414fd1ae3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRows.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRows.java @@ -37,8 +37,6 @@ /** * The RaggedFillEmptyRows operation - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = RaggedFillEmptyRows.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRowsGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRowsGrad.java index 9ea15d1320a..314e4a689af 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRowsGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedFillEmptyRowsGrad.java @@ -36,8 +36,6 @@ /** * The RaggedFillEmptyRowsGrad operation - * - * @param data type for {@code d_values} output */ @OpMetadata( opType = RaggedFillEmptyRowsGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedGather.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedGather.java index 059c102f6ed..3c71b9987c4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedGather.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedGather.java @@ -56,10 +56,6 @@ * *

    (Note: This c++ op is used to implement the higher-level python * {@code tf.ragged.gather} op, which also supports ragged indices.) - * - * @param data type for {@code output_nested_splits} output - * - * @param data type for {@code output_dense_values} output */ @OpMetadata( opType = RaggedGather.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java index 52d8d2d66b9..39a6487398e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedRange.java @@ -50,10 +50,6 @@ *

    The input tensors {@code starts}, {@code limits}, and {@code deltas} may be scalars or vectors. * The vector inputs must all have the same size. Scalar inputs are broadcast * to match the size of the vector inputs. - * - * @param data type for {@code rt_nested_splits} output - * - * @param data type for {@code rt_dense_values} output */ @OpMetadata( opType = RaggedRange.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java index 677c642582f..5e9e6cae9a7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorFromVariant.java @@ -50,10 +50,6 @@ * values of the decoded {@code RaggedTensor}. If {@code input_ragged_rank} is -1, then it is * inferred as {@code output_ragged_rank} - {@code rank(encoded_ragged)}. See * {@code RaggedTensorToVariant} for the corresponding encoding logic. - * - * @param data type for {@code output_nested_splits} output - * - * @param data type for {@code output_dense_values} output */ @OpMetadata( opType = RaggedTensorFromVariant.OP_NAME, @@ -163,8 +159,8 @@ public static class Inputs extends RawOpInputs> { public final Operand encodedRagged; /** - * The ragged rank of each encoded `RaggedTensor` component in the input. If set to - * -1, this is inferred as `output_ragged_rank` - `rank(encoded_ragged)` + * The ragged rank of each encoded {@code RaggedTensor} component in the input. If set to + * -1, this is inferred as {@code output_ragged_rank} - {@code rank(encoded_ragged)} */ public final long inputRaggedRank; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToSparse.java index 510cab39924..e765d995332 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToSparse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToSparse.java @@ -41,8 +41,6 @@ * input=ragged.from_nested_row_splits(rt_dense_values, rt_nested_splits) * output=SparseTensor(indices=sparse_indices, values=sparse_values, * dense_shape=sparse_dense_shape) - * - * @param data type for {@code sparse_values} output */ @OpMetadata( opType = RaggedTensorToSparse.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToTensor.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToTensor.java index 7a3f212b56b..1bbb93a9327 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToTensor.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToTensor.java @@ -54,8 +54,6 @@ *

  • "FIRST_DIM_SIZE": if value_rowids is used for the first dimension, then it * is preceded by "FIRST_DIM_SIZE".
    • * - * - * @param data type for {@code result} output */ @OpMetadata( opType = RaggedTensorToTensor.OP_NAME, @@ -209,11 +207,13 @@ public static class Inputs extends RawOpInputs + *
  • "ROW_SPLITS": the row_splits tensor from the ragged tensor.
    • + *
  • "VALUE_ROWIDS": the value_rowids tensor from the ragged tensor.
    • + *
  • "FIRST_DIM_SIZE": if value_rowids is used for the first dimension, then it + * is preceeded by "FIRST_DIM_SIZE". + * The tensors are in the order of the dimensions.
    • + * */ public final String[] rowPartitionTypes; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariant.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariant.java index ab616b0379d..48918309097 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariant.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariant.java @@ -134,7 +134,7 @@ public static class Inputs extends RawOpInputs { public final DataType Tsplits; /** - * A `bool` denoting whether the input is a batched `RaggedTensor`. + * A {@code bool} denoting whether the input is a batched {@code RaggedTensor}. */ public final boolean batchedInput; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariantGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariantGradient.java index d8e57336a0e..ca254cd1cf5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariantGradient.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/ragged/RaggedTensorToVariantGradient.java @@ -42,8 +42,6 @@ * op, given the variant-encoded ragged gradients of the outputs, along with * the outer row-splits and the shape of the dense-values that were provided as * inputs to the RaggedTensorToVariant op. - * - * @param data type for {@code dense_values_grad} output */ @OpMetadata( opType = RaggedTensorToVariantGradient.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java index 6412651e6ac..a213609fca6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/Multinomial.java @@ -38,8 +38,6 @@ /** * Draws samples from a multinomial distribution. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Multinomial.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java index 6008cd03718..83f81ee6c51 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/NonDeterministicInts.java @@ -38,8 +38,6 @@ /** * Non-deterministically generates some integers. * This op may use some OS-provided source of non-determinism (e.g. an RNG), so each execution will give different results. - * - * @param data type for {@code output} output */ @OpMetadata( opType = NonDeterministicInts.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java index 262cb79226d..4bc87b4da51 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/ParameterizedTruncatedNormal.java @@ -37,8 +37,6 @@ * Outputs random values from a normal distribution. The parameters may each be a * scalar which applies to the entire output, or a vector of length shape[0] which * stores the parameters for each batch. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ParameterizedTruncatedNormal.OP_NAME, @@ -204,7 +202,7 @@ public static class Inputs extends RawOpInputs maxvals; /** - * If either `seed` or `seed2` are set to be non-zero, the random number + * If either {@code seed} or {@code seed2} are set to be non-zero, the random number * generator is seeded by the given seed. Otherwise, it is seeded by a * random seed. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java index 6b47bf1cb15..cc1a0ab9ba6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGamma.java @@ -38,8 +38,6 @@ * This op uses the algorithm by Marsaglia et al. to acquire samples via * transformation-rejection from pairs of uniform and normal random variables. * See http://dl.acm.org/citation.cfm?id=358414 - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomGamma.OP_NAME, @@ -186,7 +184,7 @@ public static class Inputs extends RawOpInputs public final Operand alpha; /** - * If either `seed` or `seed2` are set to be non-zero, the random number + * If either {@code seed} or {@code seed2} are set to be non-zero, the random number * generator is seeded by the given seed. Otherwise, it is seeded by a * random seed. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java index 7baaab08ee4..4ab62242717 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomGammaGrad.java @@ -35,8 +35,6 @@ /** * Computes the derivative of a Gamma random sample w.r.t. {@code alpha}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomGammaGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java index 963377774cd..3e5fc40fc2f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomPoisson.java @@ -45,8 +45,6 @@ * random variables. * See Donald E. Knuth (1969). Seminumerical Algorithms. The Art of Computer * Programming, Volume 2. Addison Wesley - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomPoisson.OP_NAME, @@ -215,7 +213,7 @@ public static class Inputs extends RawOpInputs> { public final Operand rate; /** - * If either `seed` or `seed2` are set to be non-zero, the random number + * If either {@code seed} or {@code seed2} are set to be non-zero, the random number * generator is seeded by the given seed. Otherwise, it is seeded by a * random seed. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomShuffle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomShuffle.java index 6e5259d7cd3..517900e7df1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomShuffle.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomShuffle.java @@ -43,8 +43,6 @@ * [3, 4], ==> [1, 2], * [5, 6]] [3, 4]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomShuffle.OP_NAME, @@ -179,7 +177,7 @@ public static class Inputs extends RawOpInputs public final Operand value; /** - * If either `seed` or `seed2` are set to be non-zero, the random number + * If either {@code seed} or {@code seed2} are set to be non-zero, the random number * generator is seeded by the given seed. Otherwise, it is seeded by a * random seed. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java index 70a133cd5a4..322fe10883c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomStandardNormal.java @@ -37,8 +37,6 @@ /** * Outputs random values from a normal distribution. * The generated values will have mean 0 and standard deviation 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomStandardNormal.OP_NAME, @@ -174,7 +172,7 @@ public static class Inputs extends RawOpInputs> { public final Operand shape; /** - * If either `seed` or `seed2` are set to be non-zero, the random number + * If either {@code seed} or {@code seed2} are set to be non-zero, the random number * generator is seeded by the given seed. Otherwise, it is seeded by a * random seed. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java index 9306d1d7fcf..5940994392c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniform.java @@ -38,8 +38,6 @@ * Outputs random values from a uniform distribution. * The generated values follow a uniform distribution in the range {@code [0, 1)}. The * lower bound 0 is included in the range, while the upper bound 1 is excluded. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomUniform.OP_NAME, @@ -175,7 +173,7 @@ public static class Inputs extends RawOpInputs> { public final Operand shape; /** - * If either `seed` or `seed2` are set to be non-zero, the random number + * If either {@code seed} or {@code seed2} are set to be non-zero, the random number * generator is seeded by the given seed. Otherwise, it is seeded by a * random seed. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java index dc227152afe..6eba6a6c8b8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/RandomUniformInt.java @@ -41,8 +41,6 @@ *

    The random integers are slightly biased unless {@code maxval - minval} is an exact * power of two. The bias is small for values of {@code maxval - minval} significantly * smaller than the range of the output (either {@code 2^32} or {@code 2^64}). - * - * @param data type for {@code output} output */ @OpMetadata( opType = RandomUniformInt.OP_NAME, @@ -190,7 +188,7 @@ public static class Inputs extends RawOpInputs maxval; /** - * If either `seed` or `seed2` are set to be non-zero, the random number + * If either {@code seed} or {@code seed2} are set to be non-zero, the random number * generator is seeded by the given seed. Otherwise, it is seeded by a * random seed. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java index fc03e7feddb..67bc6bf1167 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulRandomBinomial.java @@ -38,8 +38,6 @@ /** * The StatefulRandomBinomial operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatefulRandomBinomial.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java index 8330a9f4b49..ff905308114 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulStandardNormal.java @@ -39,8 +39,6 @@ /** * Outputs random values from a normal distribution. * The generated values will have mean 0 and standard deviation 1. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatefulStandardNormal.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java index e623baabf5c..409dff36de6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulTruncatedNormal.java @@ -41,8 +41,6 @@ * The generated values follow a normal distribution with mean 0 and standard * deviation 1, except that values whose magnitude is more than 2 standard * deviations from the mean are dropped and re-picked. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatefulTruncatedNormal.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java index a0e85b0458f..65f86463b06 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniform.java @@ -40,8 +40,6 @@ * Outputs random values from a uniform distribution. * The generated values follow a uniform distribution in the range {@code [0, 1)}. The * lower bound 0 is included in the range, while the upper bound 1 is excluded. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatefulUniform.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java index a43b26418ea..80f425ff575 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformFullInt.java @@ -38,8 +38,6 @@ /** * Outputs random integers from a uniform distribution. * The generated values are uniform integers covering the whole range of {@code dtype}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatefulUniformFullInt.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformInt.java index 154f3bd2841..d2854aea992 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformInt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatefulUniformInt.java @@ -42,8 +42,6 @@ *

    The random integers are slightly biased unless {@code maxval - minval} is an exact * power of two. The bias is small for values of {@code maxval - minval} significantly * smaller than the range of the output (either {@code 2^32} or {@code 2^64}). - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatefulUniformInt.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java index 1c306047fd5..45a902b2da8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessMultinomial.java @@ -38,8 +38,6 @@ /** * Draws samples from a multinomial distribution. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessMultinomial.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java index b10e961aab2..64f85682701 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessParameterizedTruncatedNormal.java @@ -35,8 +35,6 @@ /** * The StatelessParameterizedTruncatedNormal operation - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessParameterizedTruncatedNormal.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java index 71a3cb24cf9..ebd295592eb 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomBinomial.java @@ -39,8 +39,6 @@ * Outputs deterministic pseudorandom random numbers from a binomial distribution. * Outputs random values from a binomial distribution. *

    The outputs are a deterministic function of {@code shape}, {@code seed}, {@code counts}, and {@code probs}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomBinomial.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java index e57dfcf90f6..69bd0d03ddd 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomGamma.java @@ -39,8 +39,6 @@ * Outputs deterministic pseudorandom random numbers from a gamma distribution. * Outputs random values from a gamma distribution. *

    The outputs are a deterministic function of the inputs. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomGamma.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java index 7081e980beb..bf0fa718d0e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormal.java @@ -39,8 +39,6 @@ * Outputs deterministic pseudorandom values from a normal distribution. * The generated values will have mean 0 and standard deviation 1. *

    The outputs are a deterministic function of {@code shape} and {@code seed}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomNormal.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormalV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormalV2.java index b1e9dcb4439..ef4f9aafee6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormalV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomNormalV2.java @@ -41,8 +41,6 @@ * Outputs deterministic pseudorandom values from a normal distribution. * The generated values will have mean 0 and standard deviation 1. *

    The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomNormalV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java index 3a55731c32d..c617e49f652 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomPoisson.java @@ -38,8 +38,6 @@ * Outputs deterministic pseudorandom random numbers from a Poisson distribution. * Outputs random values from a Poisson distribution. *

    The outputs are a deterministic function of {@code shape}, {@code seed}, and {@code lam}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomPoisson.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java index 6e18ceffb6f..86c24f1e171 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniform.java @@ -40,8 +40,6 @@ * The generated values follow a uniform distribution in the range {@code [0, 1)}. The * lower bound 0 is included in the range, while the upper bound 1 is excluded. *

    The outputs are a deterministic function of {@code shape} and {@code seed}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomUniform.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java index ef2bf5e7884..41e703d9ddf 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullInt.java @@ -38,8 +38,6 @@ * Outputs deterministic pseudorandom random integers from a uniform distribution. * The generated values are uniform integers covering the whole range of {@code dtype}. *

    The outputs are a deterministic function of {@code shape} and {@code seed}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomUniformFullInt.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullIntV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullIntV2.java index 50fb67d6fe1..7a910d86feb 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullIntV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformFullIntV2.java @@ -40,8 +40,6 @@ * Outputs deterministic pseudorandom random integers from a uniform distribution. * The generated values are uniform integers covering the whole range of {@code dtype}. *

    The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomUniformFullIntV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java index 8bce8bc129e..5c792f75e51 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformInt.java @@ -37,8 +37,6 @@ * Outputs deterministic pseudorandom random integers from a uniform distribution. * The generated values follow a uniform distribution in the range {@code [minval, maxval)}. *

    The outputs are a deterministic function of {@code shape}, {@code seed}, {@code minval}, and {@code maxval}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomUniformInt.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformIntV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformIntV2.java index aa3e3d0de83..ae538d14050 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformIntV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformIntV2.java @@ -39,8 +39,6 @@ * Outputs deterministic pseudorandom random integers from a uniform distribution. * The generated values follow a uniform distribution in the range {@code [minval, maxval)}. *

    The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter}, {@code alg}, {@code minval} and {@code maxval}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomUniformIntV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformV2.java index 8b0e106cb95..86bb5202639 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessRandomUniformV2.java @@ -42,8 +42,6 @@ * The generated values follow a uniform distribution in the range {@code [0, 1)}. The * lower bound 0 is included in the range, while the upper bound 1 is excluded. *

    The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessRandomUniformV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java index 2ddedee0436..83c4ebdab9c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormal.java @@ -41,8 +41,6 @@ * deviation 1, except that values whose magnitude is more than 2 standard * deviations from the mean are dropped and re-picked. *

    The outputs are a deterministic function of {@code shape} and {@code seed}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessTruncatedNormal.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormalV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormalV2.java index 6505cd06561..ae8b00ae1df 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormalV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/StatelessTruncatedNormalV2.java @@ -43,8 +43,6 @@ * deviation 1, except that values whose magnitude is more than 2 standard * deviations from the mean are dropped and re-picked. *

    The outputs are a deterministic function of {@code shape}, {@code key}, {@code counter} and {@code alg}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessTruncatedNormalV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java index 6b986b4e08e..36fbe8a2a05 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/TruncatedNormal.java @@ -39,8 +39,6 @@ * The generated values follow a normal distribution with mean 0 and standard * deviation 1, except that values whose magnitude is more than 2 standard * deviations from the mean are dropped and re-picked. - * - * @param data type for {@code output} output */ @OpMetadata( opType = TruncatedNormal.OP_NAME, @@ -177,7 +175,7 @@ public static class Inputs extends RawOpInputs> { public final Operand shape; /** - * If either `seed` or `seed2` are set to be non-zero, the random number + * If either {@code seed} or {@code seed2} are set to be non-zero, the random number * generator is seeded by the given seed. Otherwise, it is seeded by a * random seed. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/experimental/StatelessShuffle.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/experimental/StatelessShuffle.java index 5100d0ef8c6..dc17294084b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/experimental/StatelessShuffle.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/random/experimental/StatelessShuffle.java @@ -45,8 +45,6 @@ * [5, 6]] [3, 4]] * *

    The outputs are a deterministic function of {@code value}, {@code key}, {@code counter} and {@code alg}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = StatelessShuffle.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft.java index 42ef1e6bdf9..220c72d1723 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft.java @@ -37,8 +37,6 @@ * Fast Fourier transform. * Computes the 1-dimensional discrete Fourier transform over the inner-most * dimension of {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Fft.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft2d.java index 118d2db63e0..4f78086027b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft2d.java @@ -37,8 +37,6 @@ * 2D fast Fourier transform. * Computes the 2-dimensional discrete Fourier transform over the inner-most * 2 dimensions of {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Fft2d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft3d.java index 6195de0eae8..7f5478e228a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft3d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Fft3d.java @@ -37,8 +37,6 @@ * 3D fast Fourier transform. * Computes the 3-dimensional discrete Fourier transform over the inner-most 3 * dimensions of {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Fft3d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/FftNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/FftNd.java index b7f4268150c..8f530229379 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/FftNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/FftNd.java @@ -44,8 +44,6 @@ * is not given, the default shape(input) is used. *

    Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. - * - * @param data type for {@code output} output */ @OpMetadata( opType = FftNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft.java index 3a313a6f23e..6b1f6fa6d8c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft.java @@ -37,8 +37,6 @@ * Inverse fast Fourier transform. * Computes the inverse 1-dimensional discrete Fourier transform over the * inner-most dimension of {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Ifft.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft2d.java index ad0902bf3a1..2c4c19b2ead 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft2d.java @@ -37,8 +37,6 @@ * Inverse 2D fast Fourier transform. * Computes the inverse 2-dimensional discrete Fourier transform over the * inner-most 2 dimensions of {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Ifft2d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft3d.java index 82251ed232c..efcb06fafcd 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft3d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Ifft3d.java @@ -37,8 +37,6 @@ * Inverse 3D fast Fourier transform. * Computes the inverse 3-dimensional discrete Fourier transform over the * inner-most 3 dimensions of {@code input}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Ifft3d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IfftNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IfftNd.java index 82855d2bab4..181e3756015 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IfftNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IfftNd.java @@ -44,8 +44,6 @@ * is not given, the default shape(input) is used. *

    Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. - * - * @param data type for {@code output} output */ @OpMetadata( opType = IfftNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java index ecf2703b6e8..50f6daef0a0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft.java @@ -50,8 +50,6 @@ *

    Along the axis {@code signal.Irfft} is computed on, if {@code fft_length / 2 + 1} is smaller * than the corresponding dimension of {@code input}, the dimension is cropped. If it is * larger, the dimension is padded with zeros. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Irfft.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java index 8a448fd2a52..01214bfec41 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft2d.java @@ -51,8 +51,6 @@ * {@code fft_length / 2 + 1} for the inner-most dimension) is smaller than the * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Irfft2d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java index a336791cb83..c83389668b4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Irfft3d.java @@ -51,8 +51,6 @@ * {@code fft_length / 2 + 1} for the inner-most dimension) is smaller than the * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Irfft3d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IrfftNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IrfftNd.java index 93006aea156..5e83c9f4dc3 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IrfftNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/IrfftNd.java @@ -48,8 +48,6 @@ * is not given, the default shape(input) is used. *

    Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. - * - * @param data type for {@code output} output */ @OpMetadata( opType = IrfftNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java index f5c14f6eec7..c4d7b74e39a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft.java @@ -46,8 +46,6 @@ *

    Along the axis {@code signal.Rfft} is computed on, if {@code fft_length} is smaller than the * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Rfft.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java index 6587b7378c1..314d16f4eec 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft2d.java @@ -47,8 +47,6 @@ *

    Along each axis {@code signal.Rfft2d} is computed on, if {@code fft_length} is smaller than the * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Rfft2d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java index 35746c0f93b..282c4b7386e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/Rfft3d.java @@ -47,8 +47,6 @@ *

    Along each axis {@code signal.Rfft3d} is computed on, if {@code fft_length} is smaller than the * corresponding dimension of {@code input}, the dimension is cropped. If it is larger, * the dimension is padded with zeros. - * - * @param data type for {@code output} output */ @OpMetadata( opType = Rfft3d.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/RfftNd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/RfftNd.java index 85e48957ee4..17bf1368600 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/RfftNd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/signal/RfftNd.java @@ -47,8 +47,6 @@ * is not given, the default shape(input) is used. *

    Axes mean the dimensions to perform the transform on. Default is to perform on * all axes. - * - * @param data type for {@code output} output */ @OpMetadata( opType = RfftNd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddManySparseToTensorsMap.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddManySparseToTensorsMap.java index d0ad3bed95e..59d8449fa2e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddManySparseToTensorsMap.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddManySparseToTensorsMap.java @@ -208,12 +208,12 @@ public static class Inputs extends RawOpInputs { public final DataType T; /** - * The container name for the `SparseTensorsMap` created by this op. + * The container name for the {@code SparseTensorsMap} created by this op. */ public final String container; /** - * The shared name for the `SparseTensorsMap` created by this op. + * The shared name for the {@code SparseTensorsMap} created by this op. * If blank, the new Operation's unique name is used. */ public final String sharedName; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddSparseToTensorsMap.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddSparseToTensorsMap.java index c15afe711c9..ddfba840a21 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddSparseToTensorsMap.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/AddSparseToTensorsMap.java @@ -198,12 +198,12 @@ public static class Inputs extends RawOpInputs { public final DataType T; /** - * The container name for the `SparseTensorsMap` created by this op. + * The container name for the {@code SparseTensorsMap} created by this op. */ public final String container; /** - * The shared name for the `SparseTensorsMap` created by this op. + * The shared name for the {@code SparseTensorsMap} created by this op. * If blank, the new Operation's unique name is used. */ public final String sharedName; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java index 49d78c0517c..5cf78a2a0a6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseCountSparseOutput.java @@ -37,8 +37,6 @@ /** * Performs sparse-output bin counting for a tf.tensor input. * Counts the number of times each value occurs in the input. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = DenseCountSparseOutput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToDenseSetOperation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToDenseSetOperation.java index 2ea6aa671d1..546adba1a9d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToDenseSetOperation.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToDenseSetOperation.java @@ -42,8 +42,6 @@ * has rank {@code n} and the same 1st {@code n-1} dimensions as {@code set1} and {@code set2}. The {@code nth} * dimension contains the result of {@code set_operation} applied to the corresponding * {@code [0...n-1]} dimension of {@code set}. - * - * @param data type for {@code result_values} output */ @OpMetadata( opType = DenseToDenseSetOperation.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToSparseSetOperation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToSparseSetOperation.java index bb75893bfd4..1b8cbcaee50 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToSparseSetOperation.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DenseToSparseSetOperation.java @@ -48,8 +48,6 @@ * has rank {@code n} and the same 1st {@code n-1} dimensions as {@code set1} and {@code set2}. The {@code nth} * dimension contains the result of {@code set_operation} applied to the corresponding * {@code [0...n-1]} dimension of {@code set}. - * - * @param data type for {@code result_values} output */ @OpMetadata( opType = DenseToSparseSetOperation.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java index 851b3eb9856..ba0c51f9a1e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/DeserializeSparse.java @@ -76,8 +76,6 @@ * values = [1, 2, 3, 4, 5] * shape = [2 50] * - * - * @param data type for {@code sparse_values} output */ @OpMetadata( opType = DeserializeSparse.OP_NAME, @@ -165,7 +163,7 @@ public static class Inputs extends RawOpInputs> { public final Operand serializedSparse; /** - * The `dtype` of the serialized `SparseTensor` objects. + * The {@code dtype} of the serialized {@code SparseTensor} objects. */ public final DataType dtype; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java index aeb639d2d6e..fb8a868349d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAccumulatorTakeGradient.java @@ -45,8 +45,6 @@ * average of the accumulated gradients. Also automatically increments * the recorded global_step in the accumulator by 1, and resets the * aggregate to 0. - * - * @param data type for {@code values} output */ @OpMetadata( opType = SparseAccumulatorTakeGradient.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAdd.java index 1591773a20c..88ef61b78a1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAdd.java @@ -48,8 +48,6 @@ * {@code thresh == 0} (default) means everything is kept and actual thresholding happens * only for a positive value. *

    In the following shapes, {@code nnz} is the count after taking {@code thresh} into account. - * - * @param data type for {@code sum_values} output */ @OpMetadata( opType = SparseAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAddGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAddGrad.java index 7d6c0923f4f..8a844c96eff 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAddGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseAddGrad.java @@ -40,8 +40,6 @@ * as {@code SparseTensor} objects. This op takes in the upstream gradient w.r.t. * non-empty values of the sum, and outputs the gradients w.r.t. the non-empty * values of A and B. - * - * @param data type for {@code a_val_grad} output */ @OpMetadata( opType = SparseAddGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java index b7414e4ab54..9eca1295d45 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseBincount.java @@ -42,8 +42,6 @@ * the value in {@code weights} at each index where the corresponding value in {@code arr} is * {@code i}. *

    Values in {@code arr} outside of the range [0, size) are ignored. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseBincount.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConcat.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConcat.java index 2213a990292..016f010647b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConcat.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseConcat.java @@ -74,8 +74,6 @@ * [ a] concat [ d e ] = [ a d e ] * [b c ] [ ] [b c ] * - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseConcat.OP_NAME, @@ -178,7 +176,7 @@ public static class Inputs extends RawOpInputs> /** * Dimension to concatenate along. Must be in range [-rank, rank), - * where rank is the number of dimensions in each input `SparseTensor`. + * where rank is the number of dimensions in each input {@code SparseTensor}. */ public final long concatDim; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java index c3983444bd3..4c59b4e2774 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseCountSparseOutput.java @@ -37,8 +37,6 @@ /** * Performs sparse-output bin counting for a sparse tensor input. * Counts the number of times each value occurs in the input. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseCountSparseOutput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseAdd.java index 261d292d3b0..10ac8721d98 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseAdd.java @@ -43,8 +43,6 @@ *

    By these rules, the result is a logical SparseTensor with exactly the same * indices and shape, but possibly with different non-zero values. The output of * this Op is the resultant non-zero values. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseDenseCwiseAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseDiv.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseDiv.java index e0b56d6827c..724997892b1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseDiv.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseDiv.java @@ -38,8 +38,6 @@ * Component-wise divides a SparseTensor by a dense Tensor. * Limitation: this Op only broadcasts the dense side to the sparse side, but not * the other direction. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseDenseCwiseDiv.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseMul.java index 3fb7a03c683..fe8386f0838 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseDenseCwiseMul.java @@ -41,8 +41,6 @@ * contents of the dense tensor (even if it's +/-INF and that INF*0 == NaN). *

    Limitation: this Op only broadcasts the dense side to the sparse side, but not * the other direction. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseDenseCwiseMul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRows.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRows.java index 989fda03492..ef0d2f85afa 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRows.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRows.java @@ -71,8 +71,6 @@ * 

      * reverse_index_map[j] = out_j s.t. indices[j, :] == output_indices[out_j, :]
  *
    - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseFillEmptyRows.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRowsGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRowsGrad.java index 21d4e2f099f..3b1c80bb5b1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRowsGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseFillEmptyRowsGrad.java @@ -43,8 +43,6 @@ *

    d_values[j] = grad_values[reverse_index_map[j]] * d_default_value = sum_{k : 0 .. N_full - 1} ( * grad_values[k] * 1{k not in reverse_index_map}) - * - * @param data type for {@code d_values} output */ @OpMetadata( opType = SparseFillEmptyRowsGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java index 1e48a53ea82..256695f0acd 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMax.java @@ -47,8 +47,6 @@ *

    If {@code reduction_axes} has no entries, all dimensions are reduced, and a tensor * with a single element is returned. Additionally, the axes can be negative, * which are interpreted according to the indexing rules in Python. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseReduceMax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java index 8f337f0c19e..b0a65daea67 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceMaxSparse.java @@ -47,8 +47,6 @@ *

    If {@code reduction_axes} has no entries, all dimensions are reduced, and a tensor * with a single element is returned. Additionally, the axes can be negative, * which are interpreted according to the indexing rules in Python. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseReduceMaxSparse.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSum.java index 26e0ecbfc45..3589487bece 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSum.java @@ -47,8 +47,6 @@ *

    If {@code reduction_axes} has no entries, all dimensions are reduced, and a tensor * with a single element is returned. Additionally, the axes can be negative, * which are interpreted according to the indexing rules in Python. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseReduceSum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSumSparse.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSumSparse.java index bb434694ccf..ef58eac0af1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSumSparse.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReduceSumSparse.java @@ -47,8 +47,6 @@ *

    If {@code reduction_axes} has no entries, all dimensions are reduced, and a tensor * with a single element is returned. Additionally, the axes can be negative, * which are interpreted according to the indexing rules in Python. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseReduceSumSparse.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReorder.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReorder.java index 9e963285d77..4e2883435f9 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReorder.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseReorder.java @@ -42,8 +42,6 @@ *

    Reordering does not affect the shape of the SparseTensor. *

    If the tensor has rank {@code R} and {@code N} non-empty values, {@code input_indices} has * shape {@code [N, R]}, input_values has length {@code N}, and input_shape has length {@code R}. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseReorder.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java index c1899b2fbf6..4703ba10fca 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMean.java @@ -38,8 +38,6 @@ * See {@code tf.sparse.segment_sum} for usage examples. *

    Like {@code SegmentMean}, but {@code segment_ids} can have rank less than {@code data}'s first * dimension, selecting a subset of dimension 0, specified by {@code indices}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseSegmentMean.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java index 50f29512a23..9da8038eee9 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanGrad.java @@ -39,10 +39,6 @@ * Returns tensor "output" with same shape as grad, except for dimension 0 whose * value is the number of unique indexes in "indices". Also returns vector * "sorted_unique_indices" containing the corresponding indexes from "indices". - * - * @param data type for {@code output} output - * - * @param data type for {@code sorted_unique_indices} output */ @OpMetadata( opType = SparseSegmentMeanGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java index d1c0e07c099..99cf33231a5 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentMeanWithNumSegments.java @@ -40,8 +40,6 @@ *

    Read * the section on segmentation * for an explanation of segments. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseSegmentMeanWithNumSegments.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java index ee0dc4238fc..5e299d7d124 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtN.java @@ -37,8 +37,6 @@ * Computes the sum along sparse segments of a tensor divided by the sqrt of N. * N is the size of the segment being reduced. *

    See {@code tf.sparse.segment_sum} for usage examples. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseSegmentSqrtN.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java index 075cbacbcfb..b458c7daff9 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNGrad.java @@ -39,10 +39,6 @@ * Returns tensor "output" with same shape as grad, except for dimension 0 whose * value is the number of unique indexes in "indices". Also returns vector * "sorted_unique_indices" containing the corresponding indexes from "indices". - * - * @param data type for {@code output} output - * - * @param data type for {@code sorted_unique_indices} output */ @OpMetadata( opType = SparseSegmentSqrtNGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java index 84ccc501312..146dd696d6e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSqrtNWithNumSegments.java @@ -41,8 +41,6 @@ *

    Read * the section on segmentation * for an explanation of segments. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseSegmentSqrtNWithNumSegments.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java index cf2ce2c9851..2f28386d05c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSum.java @@ -61,8 +61,6 @@ * # Which is equivalent to: * tf.segment_sum(c, tf.constant([0, 0, 1])) * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseSegmentSum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumGrad.java index 71b8f92448e..1372d6f7089 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumGrad.java @@ -39,10 +39,6 @@ * Returns tensor "output" with same shape as grad, except for dimension 0 whose * value is the number of unique indexes in "indices". Also returns vector * "sorted_unique_indices" containing the corresponding indexes from "indices". - * - * @param data type for {@code output} output - * - * @param data type for {@code sorted_unique_indices} output */ @OpMetadata( opType = SparseSegmentSumGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java index 4c44377244d..88b577afec1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSegmentSumWithNumSegments.java @@ -59,8 +59,6 @@ * # [-1 -2 -3 -4] * # [ 0 0 0 0]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseSegmentSumWithNumSegments.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSlice.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSlice.java index 58c794dfb2f..a3718f1a7e0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSlice.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSlice.java @@ -52,8 +52,6 @@ * [ d e ] * [ ] * - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseSlice.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSliceGrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSliceGrad.java index 4cfa41a7e45..969ef935dc7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSliceGrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSliceGrad.java @@ -39,8 +39,6 @@ * This op takes in the upstream gradient w.r.t. non-empty values of * the sliced {@code SparseTensor}, and outputs the gradients w.r.t. * the non-empty values of input {@code SparseTensor}. - * - * @param data type for {@code val_grad} output */ @OpMetadata( opType = SparseSliceGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java index be61533da26..43cd85b5a9f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSoftmax.java @@ -48,8 +48,6 @@ * (3) Renormalizes the remaining elements. *

    Hence, the {@code SparseTensor} result has exactly the same non-zero indices and * shape. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseSoftmax.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java index 22a1d407274..80b44623ca8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMaximum.java @@ -37,8 +37,6 @@ /** * Returns the element-wise max of two SparseTensors. * Assumes the two SparseTensors have the same shape, i.e., no broadcasting. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseSparseMaximum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMinimum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMinimum.java index 8dd8978c627..ecbc022d09d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMinimum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSparseMinimum.java @@ -37,8 +37,6 @@ /** * Returns the element-wise min of two SparseTensors. * Assumes the two SparseTensors have the same shape, i.e., no broadcasting. - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseSparseMinimum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSplit.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSplit.java index a09e9ff9d38..da66d34d134 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSplit.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseSplit.java @@ -55,8 +55,6 @@ * [ d e ] * [ ] * - * - * @param data type for {@code output_values} output */ @OpMetadata( opType = SparseSplit.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseAdd.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseAdd.java index c153cf68776..7f73769030b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseAdd.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseAdd.java @@ -37,8 +37,6 @@ /** * Adds up a {@code SparseTensor} and a dense {@code Tensor}, producing a dense {@code Tensor}. * This Op does not require {@code a_indices} be sorted in standard lexicographic order. - * - * @param data type for {@code output} output */ @OpMetadata( opType = SparseTensorDenseAdd.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseMatMul.java index 346c9297596..0425354268c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseMatMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseTensorDenseMatMul.java @@ -45,8 +45,6 @@ * if adjoint_a == true: * A should be sorted in order of increasing dimension 1 (i.e., "column major" * order instead of "row major" order). - * - * @param data type for {@code product} output */ @OpMetadata( opType = SparseTensorDenseMatMul.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToDense.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToDense.java index 95c8f189d48..448a7c4ec83 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToDense.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToDense.java @@ -52,8 +52,6 @@ *

    Indices should be sorted in lexicographic order, and indices must not * contain any repeats. If {@code validate_indices} is true, these properties * are checked during execution. - * - * @param data type for {@code dense} output */ @OpMetadata( opType = SparseToDense.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToSparseSetOperation.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToSparseSetOperation.java index 8a71016a669..e658f88abb7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToSparseSetOperation.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/SparseToSparseSetOperation.java @@ -54,8 +54,6 @@ * has rank {@code n} and the same 1st {@code n-1} dimensions as {@code set1} and {@code set2}. The {@code nth} * dimension contains the result of {@code set_operation} applied to the corresponding * {@code [0...n-1]} dimension of {@code set}. - * - * @param data type for {@code result_values} output */ @OpMetadata( opType = SparseToSparseSetOperation.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java index 7db6538b380..2c6293f402d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/sparse/TakeManySparseFromTensorsMap.java @@ -77,8 +77,6 @@ * values = [1, 2, 3, 4, 5] * shape = [2 50] * - * - * @param data type for {@code sparse_values} output */ @OpMetadata( opType = TakeManySparseFromTensorsMap.OP_NAME, @@ -236,20 +234,20 @@ public static class Inputs extends RawOpInputs> public final Operand sparseHandles; /** - * The `dtype` of the `SparseTensor` objects stored in the - * `SparseTensorsMap`. + * The {@code dtype} of the {@code SparseTensor} objects stored in the + * {@code SparseTensorsMap}. */ public final DataType dtype; /** - * The container name for the `SparseTensorsMap` read by this op. + * The container name for the {@code SparseTensorsMap} read by this op. */ public final String container; /** - * The shared name for the `SparseTensorsMap` read by this op. - * It should not be blank; rather the `shared_name` or unique Operation name - * of the Op that created the original `SparseTensorsMap` should be used. + * The shared name for the {@code SparseTensorsMap} read by this op. + * It should not be blank; rather the {@code shared_name} or unique Operation name + * of the Op that created the original {@code SparseTensorsMap} should be used. */ public final String sharedName; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Lower.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Lower.java index f2571768b5c..62c18ce5098 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Lower.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Lower.java @@ -146,7 +146,7 @@ public static class Inputs extends RawOpInputs { public final Operand input; /** - * Character encoding of `input`. Allowed values are '' and 'utf-8'. + * Character encoding of {@code input}. Allowed values are '' and 'utf-8'. * Value '' is interpreted as ASCII. */ public final String encoding; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ReduceJoin.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ReduceJoin.java index c3315f28064..5bbc3e772ef 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ReduceJoin.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ReduceJoin.java @@ -196,7 +196,7 @@ public static class Inputs extends RawOpInputs { public final Operand reductionIndices; /** - * If `True`, retain reduced dimensions with length `1`. + * If {@code True}, retain reduced dimensions with length {@code 1}. */ public final boolean keepDims; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/RegexReplace.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/RegexReplace.java index af9bad8df72..bec4a4a7219 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/RegexReplace.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/RegexReplace.java @@ -158,9 +158,9 @@ public static class Inputs extends RawOpInputs { public final Operand rewrite; /** - * If True, the replacement is global (that is, all matches of the `pattern` regular - * expression in each input string are rewritten), otherwise the `rewrite` - * substitution is only made for the first `pattern` match. + * If True, the replacement is global (that is, all matches of the {@code pattern} regular + * expression in each input string are rewritten), otherwise the {@code rewrite} + * substitution is only made for the first {@code pattern} match. */ public final boolean replaceGlobal; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringLength.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringLength.java index 1e720453925..0a1ee1dff0d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringLength.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringLength.java @@ -157,10 +157,10 @@ public static class Inputs extends RawOpInputs { public final Operand input; /** - * The unit that is counted to compute string length. One of: `"BYTE"` (for - * the number of bytes in each string) or `"UTF8_CHAR"` (for the number of UTF-8 + * The unit that is counted to compute string length. One of: {@code "BYTE"} (for + * the number of bytes in each string) or {@code "UTF8_CHAR"} (for the number of UTF-8 * encoded Unicode code points in each string). Results are undefined - * if `unit=UTF8_CHAR` and the `input` strings do not contain structurally + * if {@code unit=UTF8_CHAR} and the {@code input} strings do not contain structurally * valid UTF-8. */ public final String unit; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java index ac5c914bdb1..c04fa6cd987 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/StringNGrams.java @@ -40,8 +40,6 @@ * This op accepts a ragged tensor with 1 ragged dimension containing only * strings and outputs a ragged tensor with 1 ragged dimension containing ngrams * of that string, joined along the innermost axis. - * - * @param data type for {@code ngrams_splits} output */ @OpMetadata( opType = StringNGrams.OP_NAME, @@ -144,7 +142,7 @@ public static class Inputs extends RawOpInputs dataSplits; /** - * The string to append between elements of the token. Use "" for no separator. + * The string to append between elements of the token. Use "" for no separator. */ public final String separator; @@ -168,7 +166,7 @@ public static class Inputs extends RawOpInputs { public final Operand sep; /** - * An `int`. If `maxsplit > 0`, limit of the split of the result. + * An {@code int}. If {@code maxsplit > 0}, limit of the split of the result. */ public final long maxsplit; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Substr.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Substr.java index 536a8b7f9c2..868f2bc239b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Substr.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Substr.java @@ -233,10 +233,10 @@ public static class Inputs extends RawOpInputs { public final DataType T; /** - * The unit that is used to create the substring. One of: `"BYTE"` (for - * defining position and length by bytes) or `"UTF8_CHAR"` (for the UTF-8 - * encoded Unicode code points). The default is `"BYTE"`. Results are undefined if - * `unit=UTF8_CHAR` and the `input` strings do not contain structurally valid + * The unit that is used to create the substring. One of: {@code "BYTE"} (for + * defining position and length by bytes) or {@code "UTF8_CHAR"} (for the UTF-8 + * encoded Unicode code points). The default is {@code "BYTE"}. Results are undefined if + * {@code unit=UTF8_CHAR} and the {@code input} strings do not contain structurally valid * UTF-8. */ public final String unit; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java index c1032a598a7..74e4816ed43 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/ToNumber.java @@ -50,8 +50,6 @@ * * * - * - * @param data type for {@code output} output */ @OpMetadata( opType = ToNumber.OP_NAME, @@ -132,7 +130,7 @@ public static class Inputs extends RawOpInputs> { public final Operand stringTensor; /** - * The numeric type to interpret each string in `string_tensor` as. + * The numeric type to interpret each string in {@code string_tensor} as. */ public final DataType outType; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java index f3808a6b3d2..40624c66adf 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecode.java @@ -52,8 +52,6 @@ *

  • {@code row_splits[i+1] - row_splits[i]} is the number of characters in the {@code i}th * string (in row-major order).
    • * - * - * @param data type for {@code row_splits} output */ @OpMetadata( opType = UnicodeDecode.OP_NAME, @@ -263,7 +261,7 @@ public static class Inputs extends RawOpInputs> { /** * Text encoding of the input strings. This is any of the encodings supported - * by ICU ucnv algorithmic converters. Examples: `"UTF-16", "US ASCII", "UTF-8"`. + * by ICU ucnv algorithmic converters. Examples: {@code "UTF-16", "US ASCII", "UTF-8"}. */ public final String inputEncoding; @@ -272,7 +270,7 @@ public static class Inputs extends RawOpInputs> { * The value of 'strict' will cause the operation to produce a InvalidArgument * error on any invalid input formatting. A value of 'replace' (the default) will * cause the operation to replace any invalid formatting in the input with the - * `replacement_char` codepoint. A value of 'ignore' will cause the operation to + * {@code replacement_char} codepoint. A value of 'ignore' will cause the operation to * skip any invalid formatting in the input and produce no corresponding output * character. */ @@ -280,7 +278,7 @@ public static class Inputs extends RawOpInputs> { /** * The replacement character codepoint to be used in place of any invalid - * formatting in the input when `errors='replace'`. Any valid unicode codepoint may + * formatting in the input when {@code errors='replace'}. Any valid unicode codepoint may * be used. The default value is the default unicode replacement character is * 0xFFFD or U+65533.) */ @@ -288,7 +286,7 @@ public static class Inputs extends RawOpInputs> { /** * Whether to replace the C0 control characters (00-1F) with the - * `replacement_char`. Default is false. + * {@code replacement_char}. Default is false. */ public final boolean replaceControlCharacters; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java index 9694f3cef53..5989e8e7106 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeDecodeWithOffsets.java @@ -56,8 +56,6 @@ *
  • {@code row_splits[i+1] - row_splits[i]} is the number of characters in the {@code i}th * string (in row-major order).
    • * - * - * @param data type for {@code row_splits} output */ @OpMetadata( opType = UnicodeDecodeWithOffsets.OP_NAME, @@ -280,7 +278,7 @@ public static class Inputs extends RawOpInputs> { /** * Text encoding of the input strings. This is any of the encodings supported - * by ICU ucnv algorithmic converters. Examples: `"UTF-16", "US ASCII", "UTF-8"`. + * by ICU ucnv algorithmic converters. Examples: {@code "UTF-16", "US ASCII", "UTF-8"}. */ public final String inputEncoding; @@ -289,7 +287,7 @@ public static class Inputs extends RawOpInputs> { * The value of 'strict' will cause the operation to produce a InvalidArgument * error on any invalid input formatting. A value of 'replace' (the default) will * cause the operation to replace any invalid formatting in the input with the - * `replacement_char` codepoint. A value of 'ignore' will cause the operation to + * {@code replacement_char} codepoint. A value of 'ignore' will cause the operation to * skip any invalid formatting in the input and produce no corresponding output * character. */ @@ -297,7 +295,7 @@ public static class Inputs extends RawOpInputs> { /** * The replacement character codepoint to be used in place of any invalid - * formatting in the input when `errors='replace'`. Any valid unicode codepoint may + * formatting in the input when {@code errors='replace'}. Any valid unicode codepoint may * be used. The default value is the default unicode replacement character is * 0xFFFD or U+65533.) */ @@ -305,7 +303,7 @@ public static class Inputs extends RawOpInputs> { /** * Whether to replace the C0 control characters (00-1F) with the - * `replacement_char`. Default is false. + * {@code replacement_char}. Default is false. */ public final boolean replaceControlCharacters; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeEncode.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeEncode.java index d3dbb9589df..074ff7af61b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeEncode.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeEncode.java @@ -212,21 +212,20 @@ public static class Inputs extends RawOpInputs { * The value of 'strict' will cause the operation to produce a InvalidArgument * error on any invalid input formatting. A value of 'replace' (the default) will * cause the operation to replace any invalid formatting in the input with the - * `replacement_char` codepoint. A value of 'ignore' will cause the operation to + * {@code replacement_char} codepoint. A value of 'ignore' will cause the operation to * skip any invalid formatting in the input and produce no corresponding output * character. */ public final String errors; /** - * Unicode encoding of the output strings. Valid encodings are: `"UTF-8", - * "UTF-16-BE", and "UTF-32-BE"`. + * Unicode encoding of the output strings. Valid encodings are: {@code "UTF-8", "UTF-16-BE", and "UTF-32-BE"}. */ public final String outputEncoding; /** * The replacement character codepoint to be used in place of any invalid - * formatting in the input when `errors='replace'`. Any valid unicode codepoint may + * formatting in the input when {@code errors='replace'}. Any valid unicode codepoint may * be used. The default value is the default unicode replacement character is * 0xFFFD (U+65533). */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeTranscode.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeTranscode.java index 7dee74bb545..56bfc2e406e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeTranscode.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/UnicodeTranscode.java @@ -258,13 +258,13 @@ public static class Inputs extends RawOpInputs { /** * Text encoding of the input strings. This is any of the encodings supported - * by ICU ucnv algorithmic converters. Examples: `"UTF-16", "US ASCII", "UTF-8"`. + * by ICU ucnv algorithmic converters. Examples: {@code "UTF-16", "US ASCII", "UTF-8"}. */ public final String inputEncoding; /** * The unicode encoding to use in the output. Must be one of - * `"UTF-8", "UTF-16-BE", "UTF-32-BE"`. Multi-byte encodings will be big-endian. + * {@code "UTF-8", "UTF-16-BE", "UTF-32-BE"}. Multi-byte encodings will be big-endian. */ public final String outputEncoding; @@ -273,7 +273,7 @@ public static class Inputs extends RawOpInputs { * The value of 'strict' will cause the operation to produce a InvalidArgument * error on any invalid input formatting. A value of 'replace' (the default) will * cause the operation to replace any invalid formatting in the input with the - * `replacement_char` codepoint. A value of 'ignore' will cause the operation to + * {@code replacement_char} codepoint. A value of 'ignore' will cause the operation to * skip any invalid formatting in the input and produce no corresponding output * character. */ @@ -281,11 +281,10 @@ public static class Inputs extends RawOpInputs { /** * The replacement character codepoint to be used in place of any invalid - * formatting in the input when `errors='replace'`. Any valid unicode codepoint may + * formatting in the input when {@code errors='replace'}. Any valid unicode codepoint may * be used. The default value is the default unicode replacement character is * 0xFFFD or U+65533.) - * - * Note that for UTF-8, passing a replacement character expressible in 1 byte, such + *

    Note that for UTF-8, passing a replacement character expressible in 1 byte, such * as ' ', will preserve string alignment to the source since invalid bytes will be * replaced with a 1-byte replacement. For UTF-16-BE and UTF-16-LE, any 1 or 2 byte * replacement character will preserve byte alignment to the source. @@ -294,7 +293,7 @@ public static class Inputs extends RawOpInputs { /** * Whether to replace the C0 control characters (00-1F) with the - * `replacement_char`. Default is false. + * {@code replacement_char}. Default is false. */ public final boolean replaceControlCharacters; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Upper.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Upper.java index f7854678822..230e5a618a4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Upper.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/strings/Upper.java @@ -146,7 +146,7 @@ public static class Inputs extends RawOpInputs { public final Operand input; /** - * Character encoding of `input`. Allowed values are '' and 'utf-8'. + * Character encoding of {@code input}. Allowed values are '' and 'utf-8'. * Value '' is interpreted as ASCII. */ public final String encoding; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/AllToAll.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/AllToAll.java index dfe6664886c..3bd1592cbc7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/AllToAll.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/AllToAll.java @@ -49,8 +49,6 @@ * split_count=2 *

    replica 0's output: {@code [[A], [C]]} * replica 1's output: {@code [[B], [D]]} - * - * @param data type for {@code output} output */ @OpMetadata( opType = AllToAll.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java index c56e985eafb..15e942cac31 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/CrossReplicaSum.java @@ -41,8 +41,6 @@ * Passing group_assignment={@code [[0,2,4,6],[1,3,5,7]]} sets {@code A, C, E, G} as group 0, * and {@code B, D, F, H} as group 1. Thus we get the outputs: * {@code [A+C+E+G, B+D+F+H, A+C+E+G, B+D+F+H, A+C+E+G, B+D+F+H, A+C+E+G, B+D+F+H]}. - * - * @param data type for {@code output} output */ @OpMetadata( opType = CrossReplicaSum.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingArbitraryTensorBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingArbitraryTensorBatch.java index eca45be182a..248871292ed 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingArbitraryTensorBatch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingArbitraryTensorBatch.java @@ -275,7 +275,7 @@ public static class Inputs extends RawOpInputs= 0 and less than the number + * The TPU device to use. Should be >= 0 and less than the number * of TPU cores in the task on which the node is placed. */ public final long deviceOrdinal; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingBatch.java index 0697ab23c98..811be9baee8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingBatch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingBatch.java @@ -215,7 +215,7 @@ public static class Inputs extends RawOpInputs { /** * The TPU device to use. This should be -1 when the Op - * is running on a TPU device, and >= 0 when the Op is running on the CPU + * is running on a TPU device, and >= 0 when the Op is running on the CPU * device. */ public final long deviceOrdinal; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingIntegerBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingIntegerBatch.java index b8a39d7a685..e68de9fd067 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingIntegerBatch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingIntegerBatch.java @@ -136,7 +136,7 @@ public static class Inputs extends RawOpInputs public final Operand modeOverride; /** - * The TPU device to use. Should be >= 0 and less than the number + * The TPU device to use. Should be >= 0 and less than the number * of TPU cores in the task on which the node is placed. */ public final long deviceOrdinal; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingRaggedTensorBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingRaggedTensorBatch.java index 17ed314dab1..14853b93ac7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingRaggedTensorBatch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingRaggedTensorBatch.java @@ -372,7 +372,7 @@ public static class Inputs extends RawOpInputs= 0 and less than the number + * The TPU device to use. Should be >= 0 and less than the number * of TPU cores in the task on which the node is placed. */ public final long deviceOrdinal; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseBatch.java index 14f9f072088..9c78459892d 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseBatch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseBatch.java @@ -257,7 +257,7 @@ public static class Inputs extends RawOpInputs { public final DataType T3; /** - * The TPU device to use. Should be >= 0 and less than the number + * The TPU device to use. Should be >= 0 and less than the number * of TPU cores in the task on which the node is placed. */ public final long deviceOrdinal; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseTensorBatch.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseTensorBatch.java index cec65b34619..40c6df43f92 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseTensorBatch.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/EnqueueTPUEmbeddingSparseTensorBatch.java @@ -368,7 +368,7 @@ public static class Inputs extends RawOpInputs= 0 and less than the number + * The TPU device to use. Should be >= 0 and less than the number * of TPU cores in the task on which the node is placed. */ public final long deviceOrdinal; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java index 20e200e26af..2f2d689a23a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeue.java @@ -37,8 +37,6 @@ /** * A placeholder op for a value that will be fed into the computation. - * - * @param data type for {@code output} output */ @OpMetadata( opType = InfeedDequeue.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeueTuple.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeueTuple.java index aa59b48755f..1aaa438e7c6 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeueTuple.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedDequeueTuple.java @@ -107,12 +107,12 @@ public Iterator> iterator() { ) public static class Inputs extends RawOpInputs { /** - * The element types of each element in `outputs`. + * The element types of each element in {@code outputs}. */ public final DataType[] dtypes; /** - * The shapes of each tensor in `outputs`. + * The shapes of each tensor in {@code outputs}. */ public final Shape[] shapes; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueue.java index e9c5ebd146c..bc6c1e51a79 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueue.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueue.java @@ -227,7 +227,7 @@ public static class Inputs extends RawOpInputs { /** * The TPU device to use. This should be -1 when the Op - * is running on a TPU device, and >= 0 when the Op is running on the CPU + * is running on a TPU device, and >= 0 when the Op is running on the CPU * device. */ public final long deviceOrdinal; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueueTuple.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueueTuple.java index 6d5b8ab5cb1..faae10fe8a4 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueueTuple.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/InfeedEnqueueTuple.java @@ -193,18 +193,18 @@ public static class Inputs extends RawOpInputs { public final Iterable> inputs; /** - * The element types of each element in `inputs`. + * The element types of each element in {@code inputs}. */ public final DataType[] dtypes; /** - * The shapes of each tensor in `inputs`. + * The shapes of each tensor in {@code inputs}. */ public final Shape[] shapes; /** * A vector holding the requested layout in minor-to-major sequence for - * all the tuple shapes, in the order the shapes appear in the "shapes" input. + * all the tuple shapes, in the order the shapes appear in the "shapes" input. * The layout elements for a sub-shape can be set to -1, in which case the * corresponding layout will be computed by the infeed operation. */ @@ -212,7 +212,7 @@ public static class Inputs extends RawOpInputs { /** * The TPU device to use. This should be -1 when the Op - * is running on a TPU device, and >= 0 when the Op is running on the CPU + * is running on a TPU device, and >= 0 when the Op is running on the CPU * device. */ public final long deviceOrdinal; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java index fa6e47d2c7d..f2043c5047c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeue.java @@ -38,8 +38,6 @@ /** * Retrieves a single tensor from the computation outfeed. * This operation will block indefinitely until data is available. - * - * @param data type for {@code output} output */ @OpMetadata( opType = OutfeedDequeue.OP_NAME, @@ -155,7 +153,7 @@ public static class Inputs extends RawOpInputs> { /** * The TPU device to use. This should be -1 when the Op - * is running on a TPU device, and >= 0 when the Op is running on the CPU + * is running on a TPU device, and >= 0 when the Op is running on the CPU * device. */ public final long deviceOrdinal; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTuple.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTuple.java index bef44e59c77..e3256963740 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTuple.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTuple.java @@ -152,18 +152,18 @@ public Options deviceOrdinal(Long deviceOrdinal) { ) public static class Inputs extends RawOpInputs { /** - * The element types of each element in `outputs`. + * The element types of each element in {@code outputs}. */ public final DataType[] dtypes; /** - * The shapes of each tensor in `outputs`. + * The shapes of each tensor in {@code outputs}. */ public final Shape[] shapes; /** * The TPU device to use. This should be -1 when the Op - * is running on a TPU device, and >= 0 when the Op is running on the CPU + * is running on a TPU device, and >= 0 when the Op is running on the CPU * device. */ public final long deviceOrdinal; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTupleV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTupleV2.java index 23b7f3ae189..dc78bf09faa 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTupleV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueTupleV2.java @@ -122,12 +122,12 @@ public static class Inputs extends RawOpInputs { public final Operand deviceOrdinal; /** - * The element types of each element in `outputs`. + * The element types of each element in {@code outputs}. */ public final DataType[] dtypes; /** - * The shapes of each tensor in `outputs`. + * The shapes of each tensor in {@code outputs}. */ public final Shape[] shapes; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueV2.java index 481f916e86a..dc0d6a3649a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/OutfeedDequeueV2.java @@ -40,8 +40,6 @@ * Retrieves a single tensor from the computation outfeed. Device ordinal is a * tensor allowing dynamic outfeed. * This operation will block indefinitely until data is available. - * - * @param data type for {@code output} output */ @OpMetadata( opType = OutfeedDequeueV2.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedInput.java index be69029e573..89d11541c1b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedInput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedInput.java @@ -37,8 +37,6 @@ /** * An op that groups a list of partitioned inputs together. Supports ND sharding. - * - * @param data type for {@code output} output */ @OpMetadata( opType = PartitionedInput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedOutput.java index a49b96f066d..b69bdea9a7b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedOutput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PartitionedOutput.java @@ -38,8 +38,6 @@ /** * An op that demultiplexes a tensor to be sharded by XLA to a list of partitioned * outputs outside the XLA computation. Supports ND sharding. - * - * @param data type for {@code output} output */ @OpMetadata( opType = PartitionedOutput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PrelinearizeTuple.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PrelinearizeTuple.java index cb67b7ad219..9c0217fded0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PrelinearizeTuple.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/PrelinearizeTuple.java @@ -185,18 +185,18 @@ public static class Inputs extends RawOpInputs { public final Iterable> inputs; /** - * The element types of each element in `inputs`. + * The element types of each element in {@code inputs}. */ public final DataType[] dtypes; /** - * The shapes of each tensor in `inputs`. + * The shapes of each tensor in {@code inputs}. */ public final Shape[] shapes; /** * A vector holding the requested layout in minor-to-major sequence for all the - * tuple shapes in the order the shapes appear in the "shapes" input. The layout + * tuple shapes in the order the shapes appear in the "shapes" input. The layout * elements for a sub-shape can be set to -1 in which case the corresponding layout * will be computed by the infeed operation. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedInput.java index 37c057fc375..5f5ae14be0e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedInput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedInput.java @@ -46,8 +46,6 @@ * %computation = "tf.Computation"(%replicated_input) * *

    The above computation has a replicated input of two replicas. - * - * @param data type for {@code output} output */ @OpMetadata( opType = ReplicatedInput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedOutput.java index fcc447fb932..6daab9ae1a2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedOutput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/ReplicatedOutput.java @@ -45,8 +45,6 @@ * %replicated_output:2 = "tf.TPUReplicatedOutput"(%computation) * *

    The above computation has a replicated output of two replicas. - * - * @param data type for {@code outputs} output */ @OpMetadata( opType = ReplicatedOutput.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/SplitDedupData.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/SplitDedupData.java index ad72b480077..8e8d4537dff 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/SplitDedupData.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/SplitDedupData.java @@ -41,10 +41,6 @@ * Deduplication data is an XLA tuple, which consists of integer and floating point * values. This op is to split these values into two groups for two types, and * construct each group as one tensor to return. - * - * @param data type for {@code integer_tensor} output - * - * @param data type for {@code float_tensor} output */ @OpMetadata( opType = SplitDedupData.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedInput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedInput.java index 1816bb842df..80ac7e3ea03 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedInput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedInput.java @@ -47,8 +47,6 @@ * *

    The above computation has a replicated input of two replicas. * - * @param data type for {@code output} output - * * @deprecated use {@link org.tensorflow.op.tpu.ReplicatedInput} instead */ @OpMetadata( diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedOutput.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedOutput.java index ea53c36f109..dcc1b12b2b8 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedOutput.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/tpu/TPUReplicatedOutput.java @@ -46,8 +46,6 @@ * *

    The above computation has a replicated output of two replicas. * - * @param data type for {@code outputs} output - * * @deprecated use {@link org.tensorflow.op.tpu.ReplicatedOutput} instead */ @OpMetadata( diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java index a2d152ab93e..e7c94866732 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/AccumulatorTakeGradient.java @@ -43,8 +43,6 @@ * aggregated more than num_required gradients, it returns the average of * the accumulated gradients. Also automatically increments the recorded * global_step in the accumulator by 1, and resets the aggregate to 0. - * - * @param data type for {@code average} output */ @OpMetadata( opType = AccumulatorTakeGradient.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdaMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdaMax.java index 3745c1a0dc0..0bdb47444ad 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdaMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdaMax.java @@ -38,8 +38,6 @@ * m_t <- beta1 * m_{t-1} + (1 - beta1) * g * v_t <- max(beta2 * v_{t-1}, abs(g)) * variable <- variable - learning_rate / (1 - beta1^t) * m_t / (v_t + epsilon) - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyAdaMax.OP_NAME, @@ -209,7 +207,7 @@ public static class Inputs extends RawOpInputs> public final DataType T; /** - * If `True`, updating of the var, m, and v tensors will be protected + * If {@code True}, updating of the var, m, and v tensors will be protected * by a lock; otherwise the behavior is undefined, but may exhibit less * contention. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdadelta.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdadelta.java index be5bdc297ea..7d53245fe2a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdadelta.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdadelta.java @@ -39,8 +39,6 @@ * update = (update_accum + epsilon).sqrt() * (accum + epsilon()).rsqrt() * grad; * update_accum = rho() * update_accum + (1 - rho()) * update.square(); * var -= update; - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyAdadelta.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagrad.java index 94ede4d4a85..0d243bfce4b 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagrad.java @@ -37,8 +37,6 @@ * Update '*var' according to the adagrad scheme. * accum += grad * grad * var -= lr * grad * (1 / sqrt(accum)) - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyAdagrad.OP_NAME, @@ -198,7 +196,7 @@ public static class Inputs extends RawOpInputs> public final DataType T; /** - * If `True`, updating of the var and accum tensors will be protected + * If {@code True}, updating of the var and accum tensors will be protected * by a lock; otherwise the behavior is undefined, but may exhibit less * contention. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradDa.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradDa.java index b1577260bf8..a2769eae2e7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradDa.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradDa.java @@ -36,8 +36,6 @@ /** * Update '*var' according to the proximal adagrad scheme. - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyAdagradDa.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradV2.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradV2.java index abb8cf13c08..22d0edd340e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradV2.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAdagradV2.java @@ -37,8 +37,6 @@ * Update '*var' according to the adagrad scheme. * accum += grad * grad * var -= lr * grad * (1 / sqrt(accum)) - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyAdagradV2.OP_NAME, @@ -205,7 +203,7 @@ public static class Inputs extends RawOpInputs{t-1} + (1 - \beta_1) \cdot g$$ * $$v_t := \beta_2 \cdot v_{t-1} + (1 - \beta_2) \cdot g^2$$ * $$\text{var} := \begin{cases} \text{var} - (m_t \beta_1 + g \cdot (1 - \beta_1))\cdot\text{lr}_t/(\sqrt{v_t} + \epsilon), &\text{if use_nesterov}\\ \text{var} - m_t \cdot \text{lr}_t /(\sqrt{v_t} + \epsilon), &\text{otherwise} \end{cases}$$ - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyAdam.OP_NAME, @@ -243,14 +241,14 @@ public static class Inputs extends RawOpInputs> { public final DataType T; /** - * If `True`, updating of the var, m, and v tensors will be protected + * If {@code True}, updating of the var, m, and v tensors will be protected * by a lock; otherwise the behavior is undefined, but may exhibit less * contention. */ public final boolean useLocking; /** - * If `True`, uses the nesterov update. + * If {@code True}, uses the nesterov update. */ public final boolean useNesterov; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAddSign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAddSign.java index 6adc7810232..69127231eb1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAddSign.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyAddSign.java @@ -38,8 +38,6 @@ * m_t <- beta1 * m_{t-1} + (1 - beta1) * g * update <- (alpha + sign_decay * sign(g) *sign(m)) * g * variable <- variable - lr_t * update - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyAddSign.OP_NAME, @@ -195,7 +193,7 @@ public static class Inputs extends RawOpInputs> public final DataType T; /** - * If `True`, updating of the var and m tensors is + * If {@code True}, updating of the var and m tensors is * protected by a lock; otherwise the behavior is undefined, but may exhibit less * contention. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyCenteredRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyCenteredRmsProp.java index ff482191f8c..f7801bf277e 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyCenteredRmsProp.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyCenteredRmsProp.java @@ -49,8 +49,6 @@ * ms <- rho * ms_{t-1} + (1-rho) * grad * grad * mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms - mg * mg + epsilon) * var <- var - mom - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyCenteredRmsProp.OP_NAME, @@ -220,7 +218,7 @@ public static class Inputs extends RawOpInputs data type for {@code out} output */ @OpMetadata( opType = ApplyFtrl.OP_NAME, @@ -239,7 +237,7 @@ public static class Inputs extends RawOpInputs> { public final DataType T; /** - * If `True`, updating of the var and accum tensors will be protected + * If {@code True}, updating of the var and accum tensors will be protected * by a lock; otherwise the behavior is undefined, but may exhibit less * contention. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyGradientDescent.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyGradientDescent.java index 3ecfae71626..5ebb7b31330 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyGradientDescent.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyGradientDescent.java @@ -35,8 +35,6 @@ /** * Update '*var' by subtracting 'alpha' * 'delta' from it. - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyGradientDescent.OP_NAME, @@ -161,7 +159,7 @@ public static class Inputs extends RawOpInputsaccum = accum * momentum + grad * var -= lr * accum - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyMomentum.OP_NAME, @@ -210,14 +208,14 @@ public static class Inputs extends RawOpInputs public final DataType T; /** - * If `True`, updating of the var and accum tensors will be protected + * If {@code True}, updating of the var and accum tensors will be protected * by a lock; otherwise the behavior is undefined, but may exhibit less * contention. */ public final boolean useLocking; /** - * If `True`, the tensor passed to compute grad will be + * If {@code True}, the tensor passed to compute grad will be * var - lr * momentum * accum, so in the end, the var you get is actually * var - lr * momentum * accum. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyPowerSign.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyPowerSign.java index 800923076c3..f298f853be2 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyPowerSign.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyPowerSign.java @@ -38,8 +38,6 @@ * m_t <- beta1 * m_{t-1} + (1 - beta1) * g * update <- exp(logbase * sign_decay * sign(g) * sign(m_t)) * g * variable <- variable - lr_t * update - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyPowerSign.OP_NAME, @@ -195,7 +193,7 @@ public static class Inputs extends RawOpInputsl2) * max{|prox_v|-lrl1,0} - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyProximalAdagrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalGradientDescent.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalGradientDescent.java index 488faf4d559..ffd6ee70e68 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalGradientDescent.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyProximalGradientDescent.java @@ -37,8 +37,6 @@ * Update '*var' as FOBOS algorithm with fixed learning rate. * prox_v = var - alpha * delta * var = sign(prox_v)/(1+alphal2) * max{|prox_v|-alphal1,0} - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyProximalGradientDescent.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyRmsProp.java index f4ea6418cbb..fcfeb5b895a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyRmsProp.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ApplyRmsProp.java @@ -43,8 +43,6 @@ *

    ms <- rho * ms_{t-1} + (1-rho) * grad * grad * mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon) * var <- var - mom - * - * @param data type for {@code out} output */ @OpMetadata( opType = ApplyRmsProp.OP_NAME, @@ -207,7 +205,7 @@ public static class Inputs extends RawOpInputs> public final DataType T; /** - * If `True`, updating of the var, ms, and mom tensors is protected + * If {@code True}, updating of the var, ms, and mom tensors is protected * by a lock; otherwise the behavior is undefined, but may exhibit less * contention. */ diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/BatchMatMul.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/BatchMatMul.java index 479f29deaf2..17560573705 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/BatchMatMul.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/BatchMatMul.java @@ -56,8 +56,6 @@ *

    NOTE: {@code train.BatchMatMul} supports broadcasting in the batch dimensions. More * about broadcasting * here . - * - * @param data type for {@code output} output */ @OpMetadata( opType = BatchMatMul.OP_NAME, @@ -263,12 +261,12 @@ public static class Inputs extends RawOpInputs> { public final DataType Tout; /** - * If `True`, adjoint the slices of `x`. Defaults to `False`. + * If {@code True}, adjoint the slices of {@code x}. Defaults to {@code False}. */ public final boolean adjX; /** - * If `True`, adjoint the slices of `y`. Defaults to `False`. + * If {@code True}, adjoint the slices of {@code y}. Defaults to {@code False}. */ public final boolean adjY; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/PreventGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/PreventGradient.java index a7181e6cb0b..c98b11d0050 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/PreventGradient.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/PreventGradient.java @@ -41,8 +41,6 @@ * because no gradient must ever be registered for this function. This * op exists to prevent subtle bugs from silently returning unimplemented * gradients in some corner cases. - * - * @param data type for {@code output} output */ @OpMetadata( opType = PreventGradient.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java index 4b7a918f597..843ecae89f1 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceAccumulatorTakeGradient.java @@ -42,8 +42,6 @@ * aggregated more than num_required gradients, it returns the average of * the accumulated gradients. Also automatically increments the recorded * global_step in the accumulator by 1, and resets the aggregate to 0. - * - * @param data type for {@code average} output */ @OpMetadata( opType = ResourceAccumulatorTakeGradient.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdaMax.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdaMax.java index b6cc57f3185..470a8f8414c 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdaMax.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/ResourceApplyAdaMax.java @@ -189,7 +189,7 @@ public static class Inputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputs extends RawOpInputsThe {@code shape_and_slice} input has the same format as the * elements of the {@code shapes_and_slices} input of the {@code SaveSlices} op. - * - * @param data type for {@code tensor} output */ @OpMetadata( opType = RestoreSlice.OP_NAME, @@ -178,7 +176,7 @@ public static class Inputs extends RawOpInputs> { /** * Index of file to open first if multiple files match - * `file_pattern`. See the documentation for `Restore`. + * {@code file_pattern}. See the documentation for {@code Restore}. */ public final long preferredShard; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdadelta.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdadelta.java index c68618fecc1..8b12e83f51f 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdadelta.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdadelta.java @@ -36,8 +36,6 @@ /** * var: Should be from a Variable(). - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyAdadelta.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagrad.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagrad.java index b53c5b6f540..fbda4c582a0 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagrad.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyAdagrad.java @@ -39,8 +39,6 @@ * That is for rows we have grad for, we update var and accum as follows: * $$accum += grad * grad$$ * $$var -= lr * grad * (1 / sqrt(accum))$$ - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyAdagrad.OP_NAME, @@ -220,7 +218,7 @@ public static class Inputs extends RawOpInputs data type for {@code out} output */ @OpMetadata( opType = SparseApplyAdagradDa.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyCenteredRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyCenteredRmsProp.java index aa940b94ea0..cfbf01b8044 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyCenteredRmsProp.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyCenteredRmsProp.java @@ -49,8 +49,6 @@ *

    $$ms <- rho * ms_{t-1} + (1-rho) * grad * grad$$ * $$mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)$$ * $$var <- var - mom$$ - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyCenteredRmsProp.OP_NAME, @@ -233,7 +231,7 @@ public static class Inputs extends RawOpInputs data type for {@code out} output */ @OpMetadata( opType = SparseApplyFtrl.OP_NAME, @@ -254,7 +252,7 @@ public static class Inputs extends RawOpInputsThat is for rows we have grad for, we update var and accum as follows: *

    $$accum = accum * momentum + grad$$ * $$var -= lr * accum$$ - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyMomentum.OP_NAME, @@ -225,14 +223,14 @@ public static class Inputs extends RawOpInputsl2) * max{|prox_v|-lrl1,0}$$ - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyProximalAdagrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalGradientDescent.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalGradientDescent.java index 08b098f80ca..3da972089e7 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalGradientDescent.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyProximalGradientDescent.java @@ -39,8 +39,6 @@ * That is for rows we have grad for, we update var as follows: * $$prox_v = var - alpha * grad$$ * $$var = sign(prox_v)/(1+alphal2) * max{|prox_v|-alphal1,0}$$ - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyProximalGradientDescent.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyRmsProp.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyRmsProp.java index 3a71d3826c4..3c642ebcf81 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyRmsProp.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/train/SparseApplyRmsProp.java @@ -44,8 +44,6 @@ *

    $$ms <- rho * ms_{t-1} + (1-rho) * grad * grad$$ * $$mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)$$ * $$var <- var - mom$$ - * - * @param data type for {@code out} output */ @OpMetadata( opType = SparseApplyRmsProp.OP_NAME, @@ -220,7 +218,7 @@ public static class Inputs extends RawOpInputs data type for {@code output} output */ @OpMetadata( opType = TileGrad.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ConcatND.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ConcatND.java index 7e55c95e679..1967df6a719 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ConcatND.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ConcatND.java @@ -66,8 +66,6 @@ * [4, 5, 6], * [8, 9, 10]] * - * - * @param data type for {@code output} output */ @OpMetadata( opType = ConcatND.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReadVariableSplitND.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReadVariableSplitND.java index 666103dd273..91571db9698 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReadVariableSplitND.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/ReadVariableSplitND.java @@ -67,8 +67,6 @@ * [[8, 0], * [0, 0]] * - * - * @param data type for {@code outputs} output */ @OpMetadata( opType = ReadVariableSplitND.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SplitND.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SplitND.java index 6bf5656f68c..dd6b61d2e81 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SplitND.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/SplitND.java @@ -66,8 +66,6 @@ * [[8, 0], * [0, 0]] * - * - * @param data type for {@code outputs} output */ @OpMetadata( opType = SplitND.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaHostCompute.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaHostCompute.java index 3c1fbfdd0ea..0b25f9f064a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaHostCompute.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaHostCompute.java @@ -245,12 +245,12 @@ public static class Inputs extends RawOpInputs { public final Iterable> inputs; /** - * The element types of each element in `inputs`. + * The element types of each element in {@code inputs}. */ public final DataType[] Tinputs; /** - * The element types of each element in `outputs`. + * The element types of each element in {@code outputs}. */ public final DataType[] Toutputs; @@ -261,7 +261,7 @@ public static class Inputs extends RawOpInputs { public final String[] ancestors; /** - * If shape_inference_graph is empty, a list of the shapes of `outputs`. + * If shape_inference_graph is empty, a list of the shapes of {@code outputs}. */ public final Shape[] shapes; diff --git a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvFromHost.java b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvFromHost.java index c8d5507a673..b05f7199f7a 100644 --- a/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvFromHost.java +++ b/tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow/op/xla/XlaRecvFromHost.java @@ -41,8 +41,6 @@ * Toutput: element type for output. * shape: shape for output. * key: A unique identifier for this region used to match up host transfers. - * - * @param data type for {@code output} output */ @OpMetadata( opType = XlaRecvFromHost.OP_NAME, diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerSession.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerSession.java index 62b93bcf219..84fc4d7fe9c 100644 --- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerSession.java +++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/EagerSession.java @@ -1,4 +1,4 @@ -/* Copyright 2019-2021 The TensorFlow Authors. All Rights Reserved. +/* Copyright 2019-2024 The TensorFlow Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. @@ -115,7 +115,7 @@ public Options devicePlacementPolicy(DevicePlacementPolicy value) { * * @param config a config protocol buffer * @see config.proto + * href="https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/protobuf/config.proto">config.proto */ public Options config(ConfigProto config) { this.config = config; diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/SavedModelBundle.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/SavedModelBundle.java index 9f63f3e7fea..0228519e42c 100644 --- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/SavedModelBundle.java +++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/SavedModelBundle.java @@ -1,4 +1,4 @@ -/* Copyright 2019-2021 The TensorFlow Authors. All Rights Reserved. +/* Copyright 2019-2024 The TensorFlow Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. @@ -250,9 +250,8 @@ public Exporter withSignature(Signature signature) { /** * Add multiple signatures to the model. Wraps {@link #withSignature(Signature)} * - *

    Either {@link #withSession(Session)} or {@link * #withFunction(SessionFunction)} must - * be called before this method, and the session set there will be used for these - * signatures. + *

    Either {@link #withSession(Session)} or {@link #withFunction(SessionFunction)} must be + * called before this method, and the session set there will be used for these signatures. * * @throws IllegalStateException if no session has been set * @return this diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Session.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Session.java index 5b9f2f1985e..80d99f227ec 100644 --- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Session.java +++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Session.java @@ -221,8 +221,8 @@ public final class Runner { * Avoid evaluating {@code operation} and substitute {@code t} for the value it produces. * * @param operation Is either the string name of the operation, in which case this method is a - * shorthand for {@code feed(operation, 0)}, or it is a string of the form - * operation_name:output_index , in which case this method acts like {@code + * shorthand for {@code feed(operation, 0)}, or it is a string of the form {@code + * operation_name:output_index}, in which case this method acts like {@code * feed(operation_name, output_index)}. These colon-separated names are commonly used in the * {@code SignatureDef} protocol buffer messages that are included in {@link * SavedModelBundle#metaGraphDef()}. @@ -283,8 +283,8 @@ public Runner feed(Operand operand, Tensor t) { *

    If the output is a resource variable, will fetch the value. * * @param operation Is either the string name of the operation, in which case this method is a - * shorthand for {@code fetch(operation, 0)}, or it is a string of the form - * operation_name:output_index , in which case this method acts like {@code + * shorthand for {@code fetch(operation, 0)}, or it is a string of the form {@code + * operation_name:output_index}, in which case this method acts like {@code * fetch(operation_name, output_index)}. These colon-separated names are commonly used in * the {@code SignatureDef} protocol buffer messages that are included in {@link * SavedModelBundle#metaGraphDef()}. @@ -403,7 +403,7 @@ public Runner fetch(Operand operand) { * Tensors}. * * @param operation Is either the string name of the operation or it is a string of the form - * operation_name:output_index, where output_index will simply be ignored. + * {@code operation_name:output_index}, where {@code output_index} will simply be ignored. * @return this session runner * @throws IllegalArgumentException if no operation exists with the provided name */ @@ -467,16 +467,7 @@ public boolean isEmpty() { * Execute the graph fragments necessary to compute all requested fetches. * *

    WARNING: The caller assumes ownership of all returned {@link Tensor Tensors}, i.e., - * the caller must call {@link Tensor#close} on all elements of the returned list to free up - * resources. - * - *

    TODO(ashankar): Reconsider the return type here. Two things in particular: (a) Make it - * easier for the caller to cleanup (perhaps returning something like AutoCloseableList in - * SessionTest.java), and (b) Evaluate whether the return value should be a list, or maybe a - * {@code Map}? - * - *

    TODO(andrewmyers): It would also be good if whatever is returned here made it easier to - * extract output tensors in a type-safe way. + * the caller must call {@link Result#close} to free up resources. * * @return list of resulting tensors fetched by this session runner */ @@ -703,7 +694,7 @@ public synchronized void restore(String prefix) { markAllInitializersAsRan(); } - Graph graph() { + public Graph graph() { return graph; } diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Signature.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Signature.java index 9f524ef2544..0d6866c4e70 100644 --- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Signature.java +++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Signature.java @@ -158,11 +158,15 @@ public Signature build() { return new Signature(key, signatureBuilder.build()); } - private static TensorInfo toTensorInfo(Output operand) { + static TensorInfo toTensorInfo(Output operand) { Shape shape = operand.shape(); TensorShapeProto.Builder tensorShapeBuilder = TensorShapeProto.newBuilder(); - for (int i = 0; i < shape.numDimensions(); ++i) { - tensorShapeBuilder.addDim(Dim.newBuilder().setSize(shape.size(i))); + if (shape.isUnknown()) { + tensorShapeBuilder.setUnknownRank(true); + } else { + for (int i = 0; i < shape.numDimensions(); ++i) { + tensorShapeBuilder.addDim(Dim.newBuilder().setSize(shape.get(i))); + } } return TensorInfo.newBuilder() .setDtype(operand.dataType()) diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Tensor.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Tensor.java index 4d9f2a453b7..0c243f4a2ab 100644 --- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Tensor.java +++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/Tensor.java @@ -1,4 +1,4 @@ -/* Copyright 2016 The TensorFlow Authors. All Rights Reserved. +/* Copyright 2016-2024 The TensorFlow Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. @@ -100,7 +100,7 @@ static T of(Class type, Shape shape, long size) { * *

    The amount of memory to allocate is derived from the datatype and the shape of the tensor. * Tensor data is initialized by calling the {@code dataInitializer}, which receives in argument - * the value returned by {@link #data()} on the allocated tensor. For example: + * the value returned by {@code data()} on the allocated tensor. For example: * * 

    {@code
    * FloatNdArray data = ...
@@ -207,10 +207,10 @@ static  T of(Class type, Shape shape, ByteDataBuffer rawData
   /**
    * Check if this tensor is sparse or not.
    *
-   * 
    When this methods retuns {@code true}, the tensor could be cast to a {@link SparseTensor
-   * SparseTensor} to access its indices, values and denseShape tensors.
+   * 
    When this method returns {@code true}, the tensor could be cast to a {@link SparseTensor} to
+   * access its indices, values and denseShape tensors.
    *
-   * @return true if this tensor is a sparse
+   * @return true if this tensor is a sparse tensor.
    */
   default boolean isSparse() {
     return false;
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/TensorMapper.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/TensorMapper.java
index 8660395b702..1abf8c115cf 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/TensorMapper.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/TensorMapper.java
@@ -49,8 +49,7 @@ public abstract class TensorMapper {
    *     space.
    * @param tensorScope scope to extend to keep a reference on the sub-tensors composing this sparse
    *     tensor
-   * @return an instance of {@code T}, that could also be casted to a {@link SparseTensor
-   *     SparseTensor}
+   * @return an instance of {@code T}.
    */
   protected abstract SparseTensor mapSparse(
       TInt64 indices, T values, TInt64 denseShape, PointerScope tensorScope);
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/BooleanMask.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/BooleanMask.java
index 5c20bc7c9e4..f83cf577889 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/BooleanMask.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/BooleanMask.java
@@ -78,7 +78,7 @@ public static  Operand create(
     if (maskShape.numDimensions() == 0) {
       throw new IllegalArgumentException("Mask cannot be a scalar.");
     }
-    if (maskShape.hasUnknownDimension()) {
+    if (maskShape.isUnknown()) {
       throw new IllegalArgumentException("Mask cannot have unknown number of dimensions");
     }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/BooleanMaskUpdate.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/BooleanMaskUpdate.java
index 81eb5c507ea..d402bda432a 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/BooleanMaskUpdate.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/BooleanMaskUpdate.java
@@ -86,7 +86,7 @@ public static  Operand create(
     if (maskShape.numDimensions() == 0) {
       throw new IllegalArgumentException("Mask cannot be a scalar.");
     }
-    if (maskShape.hasUnknownDimension()) {
+    if (maskShape.isUnknown()) {
       throw new IllegalArgumentException("Mask cannot have unknown number of dimensions");
     }
 
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Constant.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Constant.java
index 246d222f303..b68bdbcd289 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Constant.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Constant.java
@@ -1329,11 +1329,7 @@ public static  Constant tensorOfSameType(
 
   /**
    * Create a constant by making an immutable copy of {@code tensor}. {@code tensor} may be closed
-   * afterwards without issue.
-   *
-   * 
    Note: this endpoint cannot be simply called {@code constant} since it will conflict with
-   * other endpoints accepting an NdArray in parameter {e.g. {@link #tensorOf(Scope,
-   * FloatNdArray)}}.
+   * afterward without issue.
    *
    * @param scope is a scope used to add the underlying operation.
    * @param tensor a Tensor holding the constant value
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Function.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Function.java
index 04d107baa75..94d279b52fa 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Function.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Function.java
@@ -1,4 +1,4 @@
-/* Copyright 2020-2021 The TensorFlow Authors. All Rights Reserved.
+/* Copyright 2020-2024 The TensorFlow Authors. All Rights Reserved.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -27,6 +27,9 @@
 @Operator(name = "call")
 public abstract class Function {
 
+  /** Constructor. */
+  public Function() {}
+
   /**
    * Calls the function in an execution environment, adding its graph as a function if it isn't
    * already present. The inputs and outputs are keyed by the names set in the {@code Signature}.
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Shapes.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Shapes.java
index a8cc8409785..309fd81f1e5 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Shapes.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/Shapes.java
@@ -1,4 +1,4 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+/* Copyright 2020-2024 The TensorFlow Authors. All Rights Reserved.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -389,7 +389,8 @@ public static  Operand head(Scope scope, Shape shape, C
    *
    * @param scope current scope
    * @param shape the TensorFlow shape
-   * @param n the number of leading dimensions to get, must be <= than the shape's numDimensions()
+   * @param n the number of leading dimensions to get, must be less than or equal to the shape's
+   *     numDimensions()
    * @return a 1-dimensional operand with the dimensions matching the first n dimensions of the
    *     shape
    */
@@ -404,7 +405,8 @@ public static Operand take(Scope scope, Shape shape, Operand the shape datatype.
    * @return a 1-dimensional operand with the dimensions matching * the first n dimensions of the
@@ -456,7 +458,8 @@ public static  Operand tail(Scope scope, Shape shape, C
    *
    * @param scope current scope
    * @param shape the TensorFlow shape
-   * @param n the number of leading dimensions to get, must be <= than the shape's numDimensions()
+   * @param n the number of leading dimensions to get, must be less than or equal to the shape's
+   *     numDimensions()
    * @return a 1-dimensional operand containing the dimensions matching the last n dimensions of the
    *     shape
    */
@@ -472,7 +475,8 @@ public static  Operand takeLast(
    *
    * @param scope current scope
    * @param shape the TensorFlow shape
-   * @param n the number of leading dimensions to get, must be <= than the shape's numDimensions()
+   * @param n the number of leading dimensions to get, must be less than or equal to the shape's
+   *     numDimensions()
    * @param type the shape datatype.
    * @param  the shape datatype.
    * @return a 1-dimensional operand containing the dimensions matching the last n dimensions of the
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/StridedSliceHelper.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/StridedSliceHelper.java
index c3eccac6931..109c97c0247 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/StridedSliceHelper.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/op/core/StridedSliceHelper.java
@@ -1,4 +1,4 @@
-/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
+/* Copyright 2020-2024 The TensorFlow Authors. All Rights Reserved.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -137,16 +137,17 @@ static StridedSliceArgs mergeIndexes(Index[] indices) {
    * equal to `n`, but this need not be the case. Each range specification entry can be one of the
    * following:
    *
-   * 
    - An ellipsis (...) using {@link Indices#ellipsis()}. Ellipses are used to imply zero or
-   * more dimensions of full-dimension selection. For example, {@code stridedSlice(foo,
-   * Indices.ellipsis()} is the identity slice.
+   * 
    - An ellipsis (...) using {@link org.tensorflow.ndarray.index.Indices#ellipsis()}. Ellipses
+   * are used to imply zero or more dimensions of full-dimension selection. For example, {@code
+   * stridedSlice(foo, Indices.ellipsis()} is the identity slice.
    *
-   * 
    - A new axis using {@link Indices#newAxis()}. This is used to insert a new shape=1
-   * dimension. For example, `{@code stridedSlice(foo, Indices.newAxis())} where {@code foo} is
-   * shape {@code (3, 4)} produces a {@code (1, 3, 4)} tensor.
+   * 
    - A new axis using {@link org.tensorflow.ndarray.index.Indices#newAxis()}. This is used to
+   * insert a new shape=1 dimension. For example, `{@code stridedSlice(foo, Indices.newAxis())}
+   * where {@code foo} is shape {@code (3, 4)} produces a {@code (1, 3, 4)} tensor.
    *
-   * 
    - A range {@code begin:end:stride} using {@link Indices#slice(Long, Long, long)}
-   * Index.slice()} or {@link Indices#all()}. This is used to specify how much to choose from a
+   * 
    - A range {@code begin:end:stride} using {@link
+   * org.tensorflow.ndarray.index.Indices#slice(Long, Long, long)} Index.slice()} or {@link
+   * org.tensorflow.ndarray.index.Indices#all()}. This is used to specify how much to choose from a
    * given dimension. {@code stride} can be any integer but 0. {@code begin} is an integer which
    * represents the index of the first value to select while {@code end} represents the index of the
    * last value to select (exclusive). Begin and end can be null, in which case the index begins or
@@ -163,10 +164,11 @@ static StridedSliceArgs mergeIndexes(Index[] indices) {
    * elements). For example {@code foo = [1,2,3,4]; stridedSlice(foo, Indices.slice(-2, null, -1)}
    * is {@code [4,3]}.
    *
-   * 
    - A single index using {@link Indices#at(long)}. This is used to keep only elements that
-   * have a given index. For example ({@code stridedSlice(foo, Indices.at(2))} on a shape {@code
-   * (5,6)} tensor produces a shape {@code (6,)} tensor. The dimension can be kept with size one
-   * using {@link Indices#at(long, boolean)}.
+   * 
    - A single index using {@link org.tensorflow.ndarray.index.Indices#at(long)}. This is used
+   * to keep only elements that have a given index. For example ({@code stridedSlice(foo,
+   * Indices.at(2))} on a shape {@code (5,6)} tensor produces a shape {@code (6,)} tensor. The
+   * dimension can be kept with size one using {@link org.tensorflow.ndarray.index.Indices#at(long,
+   * boolean)}.
    *
    * 
    These semantics generally follow NumPy's indexing semantics, which can be found here: https://numpy.org/doc/stable/reference/arrays.indexing.html
@@ -175,9 +177,9 @@ static StridedSliceArgs mergeIndexes(Index[] indices) {
    *
    * @param scope current scope
    * @param  data type for {@code output()} output
-   * @param indices The indices to slice. See {@link Indices}.
+   * @param indices The indices to slice. See {@link org.tensorflow.ndarray.index.Indices}.
    * @return a new instance of StridedSlice
-   * @see Indices
+   * @see org.tensorflow.ndarray.index.Indices
    */
   @Endpoint(name = "stridedSlice")
   public static  StridedSlice stridedSlice(
@@ -210,9 +212,10 @@ public static  StridedSlice stridedSlice(
    * @param scope current scope
    * @param ref the tensor to assign to.
    * @param value the value to assign.
-   * @param indices The indices to slice. See {@link Indices}.
+   * @param indices The indices to slice. See {@link org.tensorflow.ndarray.index.Indices}.
    * @return a new instance of StridedSliceAssign
-   * @see org.tensorflow.op.Ops#stridedSlice(Operand, Index...)
+   * @see org.tensorflow.op.Ops#stridedSlice(org.tensorflow.Operand,
+   *     org.tensorflow.ndarray.index.Index...)
    */
   @Endpoint(name = "stridedSliceAssign")
   public static  StridedSliceAssign stridedSliceAssign(
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBfloat16.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBfloat16.java
index f7f29de8424..c511262e339 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBfloat16.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBfloat16.java
@@ -120,11 +120,11 @@ static TBfloat16 tensorOf(Shape shape, Consumer dataInit) {
   }
 
   /**
-   * Create a sparse tensors from {@code indices}, {@code values} and {@code denseShape} dense
+   * Create a sparse tensor from {@code indices}, {@code values} and {@code denseShape} dense
    * tensors, with a default value of zero.
    *
-   * 
    The returned instance also implements the {@link SparseTensor SparseTensor}
-   * interface, allowing a user to access directly the dense tensors when needed.
+   * 
    The returned instance also implements the {@link SparseTensor} interface, allowing a user to
+   * access directly the dense tensors when needed.
    *
    * @param indices A 2-D tensor of shape {@code [N, ndims]}, that specifies the indices of the
    *     elements in the sparse tensor that contain non-default values (elements are zero-indexed).
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java
index ef218e6d24c..eee01cd0892 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TBool.java
@@ -1,5 +1,5 @@
 /*
- *  Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+ *  Copyright 2019-2024 The TensorFlow Authors. All Rights Reserved.
  *
  *  Licensed under the Apache License, Version 2.0 (the "License");
  *  you may not use this file except in compliance with the License.
@@ -111,11 +111,11 @@ static TBool tensorOf(Shape shape, Consumer dataInit) {
   }
 
   /**
-   * Create a sparse tensors from {@code indices}, {@code values} and {@code denseShape} dense
+   * Create a sparse tensor from {@code indices}, {@code values} and {@code denseShape} dense
    * tensors, with a default value of {@code false}.
    *
-   * 
    The returned instance also implements the {@link SparseTensor SparseTensor}
-   * interface, allowing a user to access directly the dense tensors when needed.
+   * 
    The returned instance also implements the {@link SparseTensor} interface, allowing a user to
+   * access directly the dense tensors when needed.
    *
    * @param indices A 2-D tensor of shape {@code [N, ndims]}, that specifies the indices of the
    *     elements in the sparse tensor that contain non-default values (elements are zero-indexed).
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat16.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat16.java
index 10f995f88a5..8b590b58339 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat16.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat16.java
@@ -117,11 +117,11 @@ static TFloat16 tensorOf(Shape shape, Consumer dataInit) {
   }
 
   /**
-   * Create a sparse tensors from {@code indices}, {@code values} and {@code denseShape} dense
+   * Create a sparse tensor from {@code indices}, {@code values} and {@code denseShape} dense
    * tensors, with a default value of zero.
    *
-   * 
    The returned instance also implements the {@link SparseTensor SparseTensor}
-   * interface, allowing a user to access directly the dense tensors when needed.
+   * 
    The returned instance also implements the {@link SparseTensor} interface, allowing a user to
+   * access directly the dense tensors when needed.
    *
    * @param indices A 2-D tensor of shape {@code [N, ndims]}, that specifies the indices of the
    *     elements in the sparse tensor that contain non-default values (elements are zero-indexed).
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat32.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat32.java
index 7bbeab3701b..8b1bdf13639 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat32.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat32.java
@@ -105,11 +105,11 @@ static TFloat32 tensorOf(Shape shape, Consumer dataInit) {
   }
 
   /**
-   * Create a sparse tensors from {@code indices}, {@code values} and {@code denseShape} dense
+   * Create a sparse tensor from {@code indices}, {@code values} and {@code denseShape} dense
    * tensors, with a default value of zero.
    *
-   * 
    The returned instance also implements the {@link SparseTensor SparseTensor}
-   * interface, allowing a user to access directly the dense tensors when needed.
+   * 
    The returned instance also implements the {@link SparseTensor} interface, allowing a user to
+   * access directly the dense tensors when needed.
    *
    * @param indices A 2-D tensor of shape {@code [N, ndims]}, that specifies the indices of the
    *     elements in the sparse tensor that contain non-default values (elements are zero-indexed).
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat64.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat64.java
index 5c616232454..f76323d06d4 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat64.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TFloat64.java
@@ -105,11 +105,11 @@ static TFloat64 tensorOf(Shape shape, Consumer dataInit) {
   }
 
   /**
-   * Create a sparse tensors from {@code indices}, {@code values} and {@code denseShape} dense
+   * Create a sparse tensor from {@code indices}, {@code values} and {@code denseShape} dense
    * tensors, with a default value of zero.
    *
-   * 
    The returned instance also implements the {@link SparseTensor SparseTensor}
-   * interface, allowing a user to access directly the dense tensors when needed.
+   * 
    The returned instance also implements the {@link SparseTensor} interface, allowing a user to
+   * access directly the dense tensors when needed.
    *
    * @param indices A 2-D tensor of shape {@code [N, ndims]}, that specifies the indices of the
    *     elements in the sparse tensor that contain non-default values (elements are zero-indexed).
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt32.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt32.java
index c3a54d59d36..d2fb4814a24 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt32.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt32.java
@@ -103,11 +103,11 @@ static TInt32 tensorOf(Shape shape, Consumer dataInit) {
   }
 
   /**
-   * Create a sparse tensors from {@code indices}, {@code values} and {@code denseShape} dense
+   * Create a sparse tensor from {@code indices}, {@code values} and {@code denseShape} dense
    * tensors, with a default value of zero.
    *
-   * 
    The returned instance also implements the {@link SparseTensor SparseTensor}
-   * interface, allowing a user to access directly the dense tensors when needed.
+   * 
    The returned instance also implements the {@link SparseTensor} interface, allowing a user to
+   * access directly the dense tensors when needed.
    *
    * @param indices A 2-D tensor of shape {@code [N, ndims]}, that specifies the indices of the
    *     elements in the sparse tensor that contain non-default values (elements are zero-indexed).
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt64.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt64.java
index 175188278a5..57741e22641 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt64.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TInt64.java
@@ -1,5 +1,5 @@
 /*
- *  Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+ *  Copyright 2019-2024 The TensorFlow Authors. All Rights Reserved.
  *
  *  Licensed under the Apache License, Version 2.0 (the "License");
  *  you may not use this file except in compliance with the License.
@@ -104,11 +104,11 @@ static TInt64 tensorOf(Shape shape, Consumer dataInit) {
   }
 
   /**
-   * Create a sparse tensors from {@code indices}, {@code values} and {@code denseShape} dense
+   * Create a sparse tensor from {@code indices}, {@code values} and {@code denseShape} dense
    * tensors, with a default value of zero.
    *
-   * 
    The returned instance also implements the {@link SparseTensor SparseTensor}
-   * interface, allowing a user to access directly the dense tensors when needed.
+   * 
    The returned instance also implements the {@link SparseTensor} interface, allowing a user to
+   * access directly the dense tensors when needed.
    *
    * @param indices A 2-D tensor of shape {@code [N, ndims]}, that specifies the indices of the
    *     elements in the sparse tensor that contain non-default values (elements are zero-indexed).
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java
index eee64d53a50..14b438fbe76 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TString.java
@@ -1,5 +1,5 @@
 /*
- *  Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+ *  Copyright 2019-2024 The TensorFlow Authors. All Rights Reserved.
  *
  *  Licensed under the Apache License, Version 2.0 (the "License");
  *  you may not use this file except in compliance with the License.
@@ -131,8 +131,8 @@ static TString tensorOf(Shape shape, DataBuffer data) {
    * 
    The data will be copied from the provided buffer to the tensor after it is allocated. The
    * strings are encoded into bytes using the charset passed in parameter.
    *
-   * 
    If charset is different than default UTF-8, then it must also be provided explicitly when
-   * reading data from the tensor, using {@link #using(Charset)}:
+   * 
    If charset is different from the default UTF-8, then it must also be provided explicitly
+   * when reading data from the tensor, using {@link #using(Charset)}:
    *
    * 
    {@code
    * // Given `originalStrings` an initialized buffer of strings
@@ -193,11 +193,11 @@ static TString tensorOfBytes(Shape shape, DataBuffer data) {
   }
 
   /**
-   * Create a sparse tensors from {@code indices}, {@code values} and {@code denseShape} dense
+   * Create a sparse tensor from {@code indices}, {@code values} and {@code denseShape} dense
    * tensors, with an empty string as the default value.
    *
-   * 
    The returned instance also implements the {@link SparseTensor SparseTensor}
-   * interface, allowing a user to access directly the dense tensors when needed.
+   * 
    The returned instance also implements the {@link SparseTensor} interface, allowing a user to
+   * access directly the dense tensors when needed.
    *
    * @param indices A 2-D tensor of shape {@code [N, ndims]}, that specifies the indices of the
    *     elements in the sparse tensor that contain non-default values (elements are zero-indexed).
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint16.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint16.java
index 24263a48767..313df5f6ea1 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint16.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint16.java
@@ -1,5 +1,5 @@
 /*
- *  Copyright 2022 The TensorFlow Authors. All Rights Reserved.
+ *  Copyright 2022-2024 The TensorFlow Authors. All Rights Reserved.
  *
  *  Licensed under the Apache License, Version 2.0 (the "License");
  *  you may not use this file except in compliance with the License.
@@ -105,11 +105,11 @@ static TUint16 tensorOf(Shape shape, Consumer dataInit) {
   }
 
   /**
-   * Create a sparse tensors from {@code indices}, {@code values} and {@code denseShape} dense
+   * Create a sparse tensor from {@code indices}, {@code values} and {@code denseShape} dense
    * tensors, with a default value of zero.
    *
-   * 
    The returned instance also implements the {@link SparseTensor SparseTensor}
-   * interface, allowing a user to access directly the dense tensors when needed.
+   * 
    The returned instance also implements the {@link SparseTensor} interface, allowing a user to
+   * access directly the dense tensors when needed.
    *
    * @param indices A 2-D tensor of shape {@code [N, ndims]}, that specifies the indices of the
    *     elements in the sparse tensor that contain non-default values (elements are zero-indexed).
diff --git a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint8.java b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint8.java
index 4507ae034eb..ff9d31a6fd2 100644
--- a/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint8.java
+++ b/tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/types/TUint8.java
@@ -1,5 +1,5 @@
 /*
- *  Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+ *  Copyright 2019-2024 The TensorFlow Authors. All Rights Reserved.
  *
  *  Licensed under the Apache License, Version 2.0 (the "License");
  *  you may not use this file except in compliance with the License.
@@ -104,11 +104,11 @@ static TUint8 tensorOf(Shape shape, Consumer dataInit) {
   }
 
   /**
-   * Create a sparse tensors from {@code indices}, {@code values} and {@code denseShape} dense
+   * Create a sparse tensor from {@code indices}, {@code values} and {@code denseShape} dense
    * tensors, with a default value of zero.
    *
-   * 
    The returned instance also implements the {@link SparseTensor SparseTensor}
-   * interface, allowing a user to access directly the dense tensors when needed.
+   * 
    The returned instance also implements the {@link SparseTensor} interface, allowing a user to
+   * access directly the dense tensors when needed.
    *
    * @param indices A 2-D tensor of shape {@code [N, ndims]}, that specifies the indices of the
    *     elements in the sparse tensor that contain non-default values (elements are zero-indexed).
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SignatureTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SignatureTest.java
index 8f636fb7459..28e97939aa2 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SignatureTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/SignatureTest.java
@@ -19,8 +19,11 @@
 import java.util.Map;
 import org.junit.jupiter.api.Test;
 import org.tensorflow.Signature.TensorDescription;
+import org.tensorflow.ndarray.Shape;
 import org.tensorflow.op.Ops;
+import org.tensorflow.op.core.Placeholder;
 import org.tensorflow.proto.DataType;
+import org.tensorflow.types.TInt32;
 
 public class SignatureTest {
 
@@ -80,4 +83,29 @@ public void emptyMethodNameConvertedToNull() {
     signature = Signature.builder().key("f").methodName(null).build();
     assertNull(signature.methodName());
   }
+
+  @Test
+  public void createTensorInfoFromOperandWithUnknownShape() {
+    try (Graph g = new Graph()) {
+      var tf = Ops.create(g);
+      var placeholder = tf.placeholder(TInt32.class);
+      var tensorInfo = Signature.Builder.toTensorInfo(placeholder.asOutput());
+      assertTrue(tensorInfo.getTensorShape().getUnknownRank());
+      assertEquals(0, tensorInfo.getTensorShape().getDimCount());
+    }
+  }
+
+  @Test
+  public void createTensorInfoFromOperandWithPartiallyUnknownShape() {
+    try (Graph g = new Graph()) {
+      var tf = Ops.create(g);
+      var shape = Shape.of(Shape.UNKNOWN_SIZE, 10);
+      var placeholder = tf.placeholder(TInt32.class, Placeholder.shape(shape));
+      var tensorInfo = Signature.Builder.toTensorInfo(placeholder.asOutput());
+      assertFalse(tensorInfo.getTensorShape().getUnknownRank());
+      assertEquals(2, tensorInfo.getTensorShape().getDimCount());
+      assertEquals(-1, tensorInfo.getTensorShape().getDim(0).getSize());
+      assertEquals(10, tensorInfo.getTensorShape().getDim(1).getSize());
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/BooleanMaskTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/BooleanMaskTest.java
index 246b44b8077..53af60d44bf 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/BooleanMaskTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/BooleanMaskTest.java
@@ -17,6 +17,7 @@
 package org.tensorflow.op.core;
 
 import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.junit.jupiter.api.Assertions.assertThrows;
 
 import org.junit.jupiter.api.Test;
 import org.tensorflow.Graph;
@@ -66,4 +67,39 @@ public void testBooleanMask() {
       }
     }
   }
+
+  @Test
+  public void testBooleanMaskWithPartiallyUnknownShape() {
+    try (Graph g = new Graph();
+        Session sess = new Session(g)) {
+      Scope scope = new OpScope(g);
+
+      Operand input = Constant.arrayOf(scope, 1, 2, 3, 4);
+      Placeholder inputMask =
+          Placeholder.create(scope, TBool.class, Placeholder.shape(Shape.of(Shape.UNKNOWN_SIZE)));
+
+      Operand output = BooleanMask.create(scope, input, inputMask);
+
+      try (TBool mask = TBool.vectorOf(true, false, false, true);
+          TInt32 result = (TInt32) sess.runner().feed(inputMask, mask).fetch(output).run().get(0)) {
+        // expected shape from Python tensorflow
+        assertEquals(Shape.of(2), result.shape());
+        assertEquals(1, result.getInt(0));
+        assertEquals(4, result.getInt(1));
+      }
+    }
+  }
+
+  @Test
+  public void testBooleanMaskWithUnknownShape() {
+    try (Graph g = new Graph()) {
+      Scope scope = new OpScope(g);
+
+      Operand input = Constant.arrayOf(scope, 1, 2, 3, 4);
+      Placeholder inputMask = Placeholder.create(scope, TBool.class);
+
+      assertThrows(
+          IllegalArgumentException.class, () -> BooleanMask.create(scope, input, inputMask));
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/BooleanMaskUpdateTest.java b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/BooleanMaskUpdateTest.java
index 4edbea33b0d..84f4229144b 100644
--- a/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/BooleanMaskUpdateTest.java
+++ b/tensorflow-core/tensorflow-core-api/src/test/java/org/tensorflow/op/core/BooleanMaskUpdateTest.java
@@ -17,6 +17,7 @@
 package org.tensorflow.op.core;
 
 import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.junit.jupiter.api.Assertions.assertThrows;
 
 import org.junit.jupiter.api.Test;
 import org.tensorflow.Graph;
@@ -151,4 +152,44 @@ public void testBooleanMaskUpdateAxis() {
       }
     }
   }
+
+  @Test
+  public void testBooleanMaskUpdateWithPartiallyUnknownShape() {
+    try (Graph g = new Graph();
+        Session sess = new Session(g)) {
+      Scope scope = new OpScope(g);
+
+      Operand input = Constant.arrayOf(scope, 1, 2, 3, 4);
+      Operand updates = Constant.arrayOf(scope, -1, 2);
+      Placeholder inputMask =
+          Placeholder.create(scope, TBool.class, Placeholder.shape(Shape.of(Shape.UNKNOWN_SIZE)));
+
+      Operand output = BooleanMaskUpdate.create(scope, input, inputMask, updates);
+
+      try (TBool mask = TBool.vectorOf(false, true, false, true);
+          TInt32 result = (TInt32) sess.runner().feed(inputMask, mask).fetch(output).run().get(0)) {
+        // expected shape from Python tensorflow
+        assertEquals(Shape.of(4), result.shape());
+        assertEquals(1, result.getInt(0));
+        assertEquals(-1, result.getInt(1));
+        assertEquals(3, result.getInt(2));
+        assertEquals(2, result.getInt(3));
+      }
+    }
+  }
+
+  @Test
+  public void testBooleanMaskUpdateWithUnknownShape() {
+    try (Graph g = new Graph()) {
+      Scope scope = new OpScope(g);
+
+      Operand input = Constant.arrayOf(scope, 1, 2, 3, 4);
+      Operand updates = Constant.arrayOf(scope, -1, 2);
+      Placeholder inputMask = Placeholder.create(scope, TBool.class);
+
+      assertThrows(
+          IllegalArgumentException.class,
+          () -> BooleanMaskUpdate.create(scope, input, inputMask, updates));
+    }
+  }
 }
diff --git a/tensorflow-core/tensorflow-core-generator/pom.xml b/tensorflow-core/tensorflow-core-generator/pom.xml
index 1e19903ff9c..312d06a8791 100644
--- a/tensorflow-core/tensorflow-core-generator/pom.xml
+++ b/tensorflow-core/tensorflow-core-generator/pom.xml
@@ -5,7 +5,7 @@
   
     org.tensorflow
     tensorflow-core
-    1.0.0-SNAPSHOT
+    1.0.0
   
   tensorflow-core-generator
   jar
@@ -44,7 +44,7 @@
     
       com.squareup
       javapoet
-      1.12.1
+      1.13.0
     
     
       com.google.protobuf
@@ -62,6 +62,16 @@
       commonmark
       0.17.1
     
+    
+      org.junit.jupiter
+      junit-jupiter-api
+      test
+    
+    
+      org.junit.jupiter
+      junit-jupiter-engine
+      test
+    
   
 
   
diff --git a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/ClassGenerator.java b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/ClassGenerator.java
index 51151992194..78b8ea04964 100644
--- a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/ClassGenerator.java
+++ b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/ClassGenerator.java
@@ -297,8 +297,6 @@ void buildClass() {
         if (seenGenerics.add(typeVar.name)) {
           typeParams.add(typeVar);
           builder.addTypeVariable(typeVar);
-          builder.addJavadoc(
-              "\n@param <$L> data type for {@code $L} output\n", typeVar.name, output.getName());
         }
       }
     }
@@ -1008,7 +1006,7 @@ private Set buildInputsClass() {
         attrNames.add(CodeBlock.of("$S", attr.getName()).toString());
         inputsBuilder.addField(
             FieldSpec.builder(javaType, name, Modifier.PUBLIC, Modifier.FINAL)
-                .addJavadoc("$L", description)
+                .addJavadoc("$L", parseDocumentation(description))
                 .build());
         fieldInits.addStatement(
             "$L = op.attributes().getAttr$L($S)",
diff --git a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/javadoc/CoreJavaDocNodeRenderer.java b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/javadoc/CoreJavaDocNodeRenderer.java
index cc80f5f0bb6..37c26c2a292 100644
--- a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/javadoc/CoreJavaDocNodeRenderer.java
+++ b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/javadoc/CoreJavaDocNodeRenderer.java
@@ -427,7 +427,7 @@ public void visit(Code code) {
   public void visit(HtmlInline htmlInline) {
     String text = htmlInline.getLiteral();
     // handle non- JavaDoc html, e.g. 
-    String tag = text.replace("\\", "");
+    String tag = text.replace("/", "");
     if (!allowedHtml5Tags.contains(tag.toLowerCase())) {
       text = text.replace("<", "<").replace(">", ">");
       writer.raw(text);
diff --git a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/javadoc/JavaDocRenderer.java b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/javadoc/JavaDocRenderer.java
index 66ea531b674..33b0aaf87b3 100644
--- a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/javadoc/JavaDocRenderer.java
+++ b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/javadoc/JavaDocRenderer.java
@@ -65,13 +65,7 @@ private JavaDocRenderer(Builder builder) {
     this.nodeRendererFactories = new ArrayList<>(builder.nodeRendererFactories.size() + 1);
     this.nodeRendererFactories.addAll(builder.nodeRendererFactories);
     // Add as last. This means clients can override the rendering of core nodes if they want.
-    this.nodeRendererFactories.add(
-        new JavaDocNodeRendererFactory() {
-          @Override
-          public NodeRenderer create(JavaDocNodeRendererContext context) {
-            return new CoreJavaDocNodeRenderer(context);
-          }
-        });
+    this.nodeRendererFactories.add(CoreJavaDocNodeRenderer::new);
   }
 
   /**
diff --git a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/processor/OperatorProcessor.java b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/processor/OperatorProcessor.java
index 57d18cb4c7b..5376d45027b 100644
--- a/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/processor/OperatorProcessor.java
+++ b/tensorflow-core/tensorflow-core-generator/src/main/java/org/tensorflow/generator/op/processor/OperatorProcessor.java
@@ -459,8 +459,7 @@ private static TypeSpec buildGroupClass(OpsSpec spec) {
         TypeSpec.classBuilder(spec.className)
             .addModifiers(Modifier.PUBLIC, Modifier.FINAL)
             .addJavadoc(
-                "An API for building {@code $L} operations as {@link $T Op}s\n\n"
-                    + "@see {@link $T}\n",
+                "An API for building {@code $L} operations as {@link $T Op}s\n\n" + "@see $T\n",
                 spec.groupName,
                 Names.Op,
                 Names.Ops)
@@ -546,7 +545,7 @@ private static TypeSpec buildTopClass(OpsSpec spec) {
             .addStatement("return new $T(scope.withSubScope(childScopeName))", Names.Ops)
             .addJavadoc(
                 "Returns an API that builds operations with the provided name prefix.\n"
-                    + "\n@see {@link $T#withSubScope(String)}\n",
+                    + "\n@see $T#withSubScope(String)\n",
                 Names.Scope)
             .build());
 
@@ -572,7 +571,7 @@ private static TypeSpec buildTopClass(OpsSpec spec) {
             .addStatement("return new Ops(scope.withName(opName))")
             .addJavadoc(
                 "Returns an API that uses the provided name for an op.\n\n"
-                    + "@see {@link $T#withName(String)}\n",
+                    + "@see $T#withName(String)\n",
                 Names.Scope)
             .build());
 
@@ -584,7 +583,7 @@ private static TypeSpec buildTopClass(OpsSpec spec) {
             .addStatement("return new Ops(scope.withDevice(deviceSpec))")
             .addJavadoc(
                 "Returns an API that places the created operations on the device(s) matching the provided spec.\n\n"
-                    + "@see {@link $T#withDevice(DeviceSpec)}\n",
+                    + "@see $T#withDevice(DeviceSpec)\n",
                 Names.Scope)
             .build());
 
@@ -596,7 +595,7 @@ private static TypeSpec buildTopClass(OpsSpec spec) {
             .addStatement("return new Ops(scope.withControlDependencies(controls))")
             .addJavadoc(
                 "Returns an API that adds operations to the graph with the provided control dependencies.\n\n"
-                    + "@see {@link $T#withControlDependencies(Iterable>)}\n",
+                    + "@see $T#withControlDependencies(Iterable)\n",
                 Names.Scope)
             .build());
 
@@ -609,7 +608,7 @@ private static TypeSpec buildTopClass(OpsSpec spec) {
             .addStatement("return withControlDependencies($T.asList(controls))", Names.Arrays)
             .addJavadoc(
                 "Returns an API that adds operations to the graph with the provided control dependencies.\n\n"
-                    + "@see {@link $T#withControlDependencies(Iterable>)}\n",
+                    + "@see $T#withControlDependencies(Iterable)\n",
                 Names.Scope)
             .build());
 
@@ -621,7 +620,7 @@ private static TypeSpec buildTopClass(OpsSpec spec) {
             .addStatement("return new Ops(scope.withControlDependencyOps(controls))")
             .addJavadoc(
                 "Returns an API that adds operations to the graph with the provided control dependencies.\n\n"
-                    + "@see {@link $T#withControlDependencyOps(Iterable)}\n",
+                    + "@see $T#withControlDependencyOps(Iterable)\n",
                 Names.Scope)
             .build());
 
@@ -634,7 +633,7 @@ private static TypeSpec buildTopClass(OpsSpec spec) {
             .addStatement("return withControlDependencyOps($T.asList(controls))", Names.Arrays)
             .addJavadoc(
                 "Returns an API that adds operations to the graph with the provided control dependencies.\n\n"
-                    + "@see {@link $T#withControlDependencyOps(Iterable)}\n",
+                    + "@see $T#withControlDependencyOps(Iterable)\n",
                 Names.Scope)
             .build());
 
diff --git a/tensorflow-core/tensorflow-core-native/WORKSPACE b/tensorflow-core/tensorflow-core-native/WORKSPACE
index 93acef27be1..1a745b13613 100644
--- a/tensorflow-core/tensorflow-core-native/WORKSPACE
+++ b/tensorflow-core/tensorflow-core-native/WORKSPACE
@@ -18,10 +18,10 @@ http_archive(
         "find tensorflow third_party/xla/third_party/tsl -name \\*.proto | xargs sed -i.bak 's/^package tensorflow\\([^;]*\\).*$/package tensorflow\\1;\\noption java_package = \"org.tensorflow.proto\\1\";/'",
     ],
     urls = [
-       "https://github.com/tensorflow/tensorflow/archive/refs/tags/v2.16.1.tar.gz",
+       "https://github.com/tensorflow/tensorflow/archive/refs/tags/v2.16.2.tar.gz",
     ],
-    sha256 = "c729e56efc945c6df08efe5c9f5b8b89329c7c91b8f40ad2bb3e13900bd4876d",
-    strip_prefix = "tensorflow-2.16.1"
+    sha256 = "023849bf253080cb1e4f09386f5eb900492da2288274086ed6cfecd6d99da9eb",
+    strip_prefix = "tensorflow-2.16.2"
 )
 
 ##### Copy content of tensorflow/WORKSPACE here (make sure to change references of default package "//" to "@org_tensorflow//")
diff --git a/tensorflow-core/tensorflow-core-native/pom.xml b/tensorflow-core/tensorflow-core-native/pom.xml
index fff8f9c5756..691d1db003f 100644
--- a/tensorflow-core/tensorflow-core-native/pom.xml
+++ b/tensorflow-core/tensorflow-core-native/pom.xml
@@ -6,7 +6,7 @@
   
     org.tensorflow
     tensorflow-core
-    1.0.0-SNAPSHOT
+    1.0.0
   
   tensorflow-core-native
   jar
@@ -72,7 +72,7 @@
         false
         false
         false
-        true
+        false 
       
     
 
@@ -131,6 +131,12 @@
                       ${project.version}
                       ${javacpp.platform.windows-x86_64}
                     
+                    
+                      ${project.groupId}
+                      ${project.artifactId}
+                      ${project.version}
+                      ${javacpp.platform.linux-arm64}
+                    
                   
                 
               
@@ -169,6 +175,10 @@
                       ${project.build.directory}/${project.artifactId}-${project.version}-${javacpp.platform.windows-x86_64}.jar
                       ${javacpp.platform.windows-x86_64}
                     
+                    
+                      ${project.build.directory}/${project.artifactId}-${project.version}-${javacpp.platform.linux-arm64}.jar
+                      ${javacpp.platform.linux-arm64}
+                    
                   
                 
               
@@ -641,7 +651,7 @@
 
       
         maven-javadoc-plugin
-        3.6.0
+        3.7.0
         
           
             attach-javadocs
@@ -649,10 +659,17 @@
               jar
             
             
+              
+                -Xmaxerrs
+                65536
+                -Xmaxwarns
+                65536
+              
               false
               256m
               2048m
               
+                https://protobuf.dev/reference/java/api-docs
                 http://bytedeco.org/javacpp/apidocs
               
             
diff --git a/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh b/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh
index c5b10d50d48..7727faefaed 100755
--- a/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh
+++ b/tensorflow-core/tensorflow-core-native/scripts/dist_download.sh
@@ -5,20 +5,23 @@ DOWNLOAD_FOLDER="$1"
 
 case ${PLATFORM:-} in
   'linux-x86_64')
-    WHEEL_URL='https://files.pythonhosted.org/packages/9b/0b/c18d6464a19d4c9b63df8880dd3ce0c67b5145ada9092f3ac67d82726566/tensorflow_cpu-2.16.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl'
+    WHEEL_URL='https://files.pythonhosted.org/packages/c6/d9/f2ff325194b8e8acb6b69f303c838b0486f41b8028ec42261f2eb037a031/tensorflow_cpu-2.16.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl'
     ;;
   'linux-x86_64-gpu')
-    WHEEL_URL='https://files.pythonhosted.org/packages/58/70/e8ac764ec80810eefcbab0cb1d21dbba6cf26719c44cd6d9a5e9f0407935/tensorflow-2.16.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl'
+    WHEEL_URL='https://files.pythonhosted.org/packages/43/dd/8f03331107b76e63313d2089ddfbd13f15e51fb8ed73517cdd0ab3341928/tensorflow-2.16.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl'
     ;;
   'macosx-x86_64')
-    WHEEL_URL='https://files.pythonhosted.org/packages/b8/75/ce4d8eeb1fb100726634358411bc4a8b12f889f6ce560b0973c0a5dbac39/tensorflow-2.16.1-cp311-cp311-macosx_10_15_x86_64.whl'
+    WHEEL_URL='https://files.pythonhosted.org/packages/6d/69/9999c2d9e8a3b08dfcfc7e9259a05fb1da5f700936091d2eb4a7985c2776/tensorflow-2.16.2-cp311-cp311-macosx_10_15_x86_64.whl'
     ;;
   'macosx-arm64')
-    WHEEL_URL='https://files.pythonhosted.org/packages/f9/14/67e9b2b2379cb530c0412123a674d045eca387dfcfa7db1c0028857b0a66/tensorflow-2.16.1-cp311-cp311-macosx_12_0_arm64.whl'
+    WHEEL_URL='https://files.pythonhosted.org/packages/9d/72/6f09443493b9df2fd8a9585c9af4d9453762906a8e5735a8a5efa6e3d1e3/tensorflow-2.16.2-cp311-cp311-macosx_12_0_arm64.whl'
     ;;
   'windows-x86_64')
-    WHEEL_URL='https://files.pythonhosted.org/packages/e0/36/6278e4e7e69a90c00e0f82944d8f2713dd85a69d1add455d9e50446837ab/tensorflow_intel-2.16.1-cp311-cp311-win_amd64.whl'
-    CLIB_URL='https://storage.googleapis.com/tensorflow/versions/2.16.1/libtensorflow-cpu-windows-x86_64.zip'
+    WHEEL_URL='https://files.pythonhosted.org/packages/46/87/c3e4e9fe7c630f38a6984afdd1d4ed531ef9c74dc66b86f46f6bdd89d608/tensorflow_intel-2.16.2-cp311-cp311-win_amd64.whl'
+    CLIB_URL='https://storage.googleapis.com/tensorflow/versions/2.16.2/libtensorflow-cpu-windows-x86_64.zip'
+    ;;
+  'linux-arm64')
+    WHEEL_URL='https://files.pythonhosted.org/packages/b5/01/c03e98c8e97d151d9ce075fae210f838832eb53d8aa55669d384cb72925b/tensorflow-2.16.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl'
     ;;
   *)
     echo "TensorFlow distribution for ${PLATFORM} is not supported for download"
@@ -34,6 +37,9 @@ if [[ -n "$WHEEL_URL" ]]; then
     curl -L $WHEEL_URL --output 'tensorflow.whl'
   fi
   yes | unzip -q -u 'tensorflow.whl' # use 'yes' because for some reasons -u does not work on Windows
+  if [[ "$PLATFORM" == "linux-arm64" ]]; then
+    cp $DOWNLOAD_FOLDER/tensorflow.libs/*  $DOWNLOAD_FOLDER/tensorflow/
+  fi
 fi
 
 if [[ -n "$CLIB_URL" ]]; then
@@ -48,6 +54,9 @@ cd tensorflow
 if [[ "$PLATFORM" =~ "linux" ]]; then
   ln -fs libtensorflow_cc.so.2 libtensorflow_cc.so
   ln -fs libtensorflow_framework.so.2 libtensorflow_framework.so
+  if [[ "$PLATFORM" == "linux-arm64" ]]; then
+    ln -fs libomp-e9212f90.so.5 libomp-e9212f90.so
+  fi
 elif [[ "$PLATFORM" =~ "macosx" ]]; then
   ln -fs libtensorflow_cc.2.dylib libtensorflow_cc.dylib
   ln -fs libtensorflow_framework.2.dylib libtensorflow_framework.dylib
@@ -56,4 +65,4 @@ elif [[ "$PLATFORM" =~ "windows" ]]; then
   # (while it is also available at the root of the include folder for other platforms)
   cd include && ln -fs tensorflow/tsl tsl && cd -
 fi
-ls -l .
\ No newline at end of file
+ls -l .
diff --git a/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/AbstractTF_Buffer.java b/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/AbstractTF_Buffer.java
index 108549a875b..2e3dfc9f673 100644
--- a/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/AbstractTF_Buffer.java
+++ b/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/AbstractTF_Buffer.java
@@ -56,7 +56,10 @@ public static TF_Buffer newBuffer() {
     return b;
   }
 
-  /** Returns {@code newBufferFromString(new BytePointer(proto.toByteArray())), or null if proto is null or empty. */
+  /**
+   * Returns {@code newBufferFromString(new BytePointer(proto.toByteArray()))}, or null if proto is
+   * null or empty.
+   */
   public static TF_Buffer newBufferFromString(Message proto) {
     if (proto == null) {
       return null;
diff --git a/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/AbstractTF_Graph.java b/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/AbstractTF_Graph.java
index 3cc7624ab71..3795f19f30f 100644
--- a/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/AbstractTF_Graph.java
+++ b/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/AbstractTF_Graph.java
@@ -44,7 +44,7 @@ public AbstractTF_Graph(Pointer p) {
   /**
    * Calls TF_NewGraph(), and registers a deallocator.
    *
-   * 
    Note {@link org.tensorflow.Graph} will call TF_DeleteGraph on close, so do not use this
+   * 
    Note {@code org.tensorflow.Graph} will call TF_DeleteGraph on close, so do not use this
    * method when constructing a reference for use inside a {@code Graph} object.
    *
    * @return TF_Graph created. Do not call TF_DeleteGraph() on it.
diff --git a/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java b/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java
index ff9f02709e3..de4c25b8a97 100644
--- a/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java
+++ b/tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/internal/c_api/presets/tensorflow.java
@@ -62,6 +62,9 @@
           },
           link = {"tensorflow_cc@.2", "tensorflow_framework@.2"},
           resource = {"LICENSE", "THIRD_PARTY_TF_JNI_LICENSES"}),
+      @Platform(
+          value = {"linux-arm64"},
+          link = {"tensorflow_cc@.2", "tensorflow_framework@.2", "omp-e9212f90@.5"}),
       @Platform(
           value = "windows",
           preload = {
diff --git a/tensorflow-core/tensorflow-core-platform/pom.xml b/tensorflow-core/tensorflow-core-platform/pom.xml
index 5ed680a8bf2..86eac891e45 100644
--- a/tensorflow-core/tensorflow-core-platform/pom.xml
+++ b/tensorflow-core/tensorflow-core-platform/pom.xml
@@ -22,7 +22,7 @@
   
     org.tensorflow
     tensorflow-core
-    1.0.0-SNAPSHOT
+    1.0.0
   
   tensorflow-core-platform
   TensorFlow API Platform
@@ -43,6 +43,12 @@
       ${project.version}
       linux-x86_64
     
+    
+      org.tensorflow
+      tensorflow-core-native
+      ${project.version}
+      linux-arm64
+    
     
       org.tensorflow
       tensorflow-core-native
@@ -73,7 +79,7 @@
             
               
                 
-                  tensorflow-core-api.jar tensorflow-core-native.jar tensorflow-core-native-linux-x86_64.jar tensorflow-core-native-macosx-arm64.jar tensorflow-core-native-macosx-x86_64.jar tensorflow-core-native-windows-x86_64.jar
+                  tensorflow-core-api.jar tensorflow-core-native.jar tensorflow-core-native-linux-x86_64.jar tensorflow-core-native-macosx-arm64.jar tensorflow-core-native-macosx-x86_64.jar tensorflow-core-native-windows-x86_64.jar tensorflow-core-native-linux-arm64.jar
                   ${java.module.name}
                 
               
diff --git a/tensorflow-framework/pom.xml b/tensorflow-framework/pom.xml
index 982bf78e118..6342849b265 100644
--- a/tensorflow-framework/pom.xml
+++ b/tensorflow-framework/pom.xml
@@ -22,7 +22,7 @@
   
     org.tensorflow
     tensorflow-java
-    1.0.0-SNAPSHOT
+    1.0.0
   
   tensorflow-framework
   jar
diff --git a/tools/Dockerfile.release b/tools/Dockerfile.release
new file mode 100644
index 00000000000..70642a20e3d
--- /dev/null
+++ b/tools/Dockerfile.release
@@ -0,0 +1,7 @@
+FROM maven:3.8.6-jdk-11
+
+WORKDIR /root
+RUN curl -L https://github.com/adoptium/temurin17-binaries/releases/download/jdk-17.0.13%2B11/OpenJDK17U-jdk_x64_linux_hotspot_17.0.13_11.tar.gz -o openjdk-17.tar.gz
+RUN tar zxvf openjdk-17.tar.gz
+ENV JAVA_HOME /root/jdk-17.0.13+11/
+
diff --git a/tools/build_java_api_docs.py b/tools/build_java_api_docs.py
index 42a83703ecf..5eadafc276d 100644
--- a/tools/build_java_api_docs.py
+++ b/tools/build_java_api_docs.py
@@ -13,7 +13,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
-"""Generate TensorFlow Lite Java reference docs for TensorFlow.org."""
+"""Generate TensorFlow Java reference docs for TensorFlow.org."""
 from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
@@ -21,6 +21,7 @@
 import pathlib
 import shutil
 import tempfile
+from git import Repo
 
 from absl import app
 from absl import flags
@@ -28,6 +29,7 @@
 from tensorflow_docs.api_generator import gen_java
 
 FLAGS = flags.FLAGS
+NDARRAY_VERSION = 'v1.0.0'
 
 # These flags are required by infrastructure, not all of them are used.
 flags.DEFINE_string('output_dir', '/tmp/java_api/',
@@ -48,6 +50,18 @@
 TOOLS_DIR = pathlib.Path(__file__).resolve().parent
 REPO_ROOT = TOOLS_DIR.parent
 
+
+def checkout_ndarray():
+  repo_url = 'https://github.com/tensorflow/java-ndarray'
+  local_repo_path = REPO_ROOT/'ndarray'
+  if not pathlib.Path(local_repo_path).exists():
+    local_repo = Repo.clone_from(repo_url, local_repo_path)
+  else:
+    local_repo = Repo(local_repo_path)
+  local_repo.remotes['origin'].fetch()
+  local_repo.git.checkout(NDARRAY_VERSION)
+
+
 def overlay(from_root, to_root):
   for from_path in pathlib.Path(from_root).rglob('*'):
     relpath = from_path.relative_to(from_root)
@@ -58,24 +72,28 @@ def overlay(from_root, to_root):
     else:
       to_path.mkdir(exist_ok=True)
 
+
 def main(unused_argv):
+  checkout_ndarray()
   merged_source = pathlib.Path(tempfile.mkdtemp())
   (merged_source / 'java/org').mkdir(parents=True)
 
-  shutil.copytree(REPO_ROOT/'tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/',
-                  merged_source/'java/org/tensorflow')
-  overlay(REPO_ROOT/'tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow',
-            merged_source/'java/org/tensorflow')
-  shutil.copytree(REPO_ROOT/'tensorflow-framework/src/main/java/org/tensorflow/framework',
-                  merged_source/'java/org/tensorflow/framework')
-  shutil.copytree(REPO_ROOT/'ndarray/src/main/java/org/tensorflow/ndarray',
-                  merged_source/'java/org/tensorflow/ndarray')
+  shutil.copytree(REPO_ROOT/'tensorflow-core/tensorflow-core-api/src/main/java/org/tensorflow/', merged_source/'java/org/tensorflow')
+  overlay(REPO_ROOT/'tensorflow-core/tensorflow-core-api/src/gen/java/org/tensorflow', merged_source/'java/org/tensorflow')
+  shutil.copytree(REPO_ROOT/'tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/proto', merged_source/'java/org/tensorflow/proto')
+  shutil.copytree(REPO_ROOT/'tensorflow-core/tensorflow-core-native/src/main/java/org/tensorflow/exceptions', merged_source/'java/org/tensorflow/exceptions')
+  shutil.copytree(REPO_ROOT/'tensorflow-core/tensorflow-core-native/src/gen/java/org/tensorflow/internal/c_api', merged_source/'java/org/tensorflow/internal/c_api')
+  shutil.copytree(REPO_ROOT/'tensorflow-framework/src/main/java/org/tensorflow/framework', merged_source/'java/org/tensorflow/framework')
+  shutil.copytree(REPO_ROOT/'ndarray/ndarray/src/main/java/org/tensorflow/ndarray', merged_source/'java/org/tensorflow/ndarray')
 
   gen_java.gen_java_docs(
       package='org.tensorflow',
       source_path=merged_source / 'java',
       output_dir=pathlib.Path(FLAGS.output_dir),
-      site_path=pathlib.Path(FLAGS.site_path))
+      site_path=pathlib.Path(FLAGS.site_path),
+      # Uncomment for local testing:
+      # script_path=pathlib.Path(REPO_ROOT/'tools/run-javadoc-for-tf-local.sh'),
+  )
 
 
 if __name__ == '__main__':
diff --git a/tools/run-javadoc-for-tf-local.sh b/tools/run-javadoc-for-tf-local.sh
new file mode 100644
index 00000000000..59239b78141
--- /dev/null
+++ b/tools/run-javadoc-for-tf-local.sh
@@ -0,0 +1,98 @@
+#!/bin/bash
+set -ex
+
+export JAVA_HOME=/Library/Java/JavaVirtualMachines/zulu-11.jdk/Contents/Home # Or change to any JDK 11 home path
+
+# https://android.googlesource.com/platform/external/doclava/
+# There's a debian package:
+# https://packages.debian.org/unstable/doclava-aosp
+# Install with:
+#
+#   $ sudo apt install doclava-aosp #v 6.0.1+r55-1+build1
+#
+# https://unix.stackexchange.com/questions/594841/how-do-i-assign-a-value-to-a-bash-variable-iff-that-variable-is-null-unassigned
+DOCLAVA_JAR=${DOCLAVA_JAR:-'lib/doclava.jar'} # Build lib locally
+
+# Install java clear silver templates with:
+#
+#   $ sudo apt install libjsilver-aosp-java #v 6.0.1+r55-1+build1
+JSILVER_JAR=${JSILVER_JAR:-'lib/jsilver.jar'} # Build lib locally
+
+
+######### DELETE OUTPUT_DIR #################
+
+# Empty the output directory in case a class has been deleted
+rm -rf "${OUTPUT_DIR:?}"/*
+############ RUN DOCLAVA ###################
+
+# $FEDERATED_DOCS is a space-separated string of url,file pairs.
+read -a api_pairs <<< "${FEDERATED_DOCS}"
+FEDERATED_PARAMS=""
+for i in "${!api_pairs[@]}"; do
+  api_pair_str="${api_pairs[$i]}"  # "url,api.txt"
+  read -a api_pair <<< "${api_pair_str//,/ }"
+  # Using the index as the API "name", build the federation params. Note that
+  # using 0 as an API name will evaluate to false and cause rendering bugs,
+  # so we preface with "api_".
+  FEDERATED_PARAMS+=" -federate api_${i} ${api_pair[0]}"
+  FEDERATED_PARAMS+=" -federationapi api_${i} ${api_pair[1]}"
+done
+
+# To install javadoc, for example, use
+#
+#   sudo apt install openjdk-11-jdk
+#
+# doclava doesn't work with openjdk-13
+#   ```
+#   javadoc: error - Class com.google.doclava.Doclava is not a valid doclet.
+#   Note: As of JDK 13, the com.sun.javadoc API is no longer supported.
+#   ```
+#   It's used here: https://android.googlesource.com/platform/external/doclava/+/refs/heads/master/src/com/google/doclava/Doclava.java
+
+# Each package in $PACKAGE needs to prefaced with -subpackages, so do that.
+SUBPACKAGES=""
+read -r -a packages <<< "${PACKAGE}"
+for pkg in "${packages[@]}"; do
+  SUBPACKAGES+=" -subpackages ${pkg}"
+done
+( # Capture the return code. it may be non-zero for minor errors.
+  javadoc \
+  -sourcepath "${SOURCE_PATH}" \
+  -docletpath "${DOCLAVA_JAR}:${JSILVER_JAR}" \
+  -doclet com.google.doclava.Doclava \
+  -d "${OUTPUT_DIR}" \
+  -toroot "${SITE_PATH}"/ \
+  -yaml _toc.yaml \
+  -templatedir "${TEMPLATES}" \
+  -public \
+  -devsite \
+  ${FEDERATED_PARAMS} \
+  ${SUBPACKAGES}
+)
+
+
+mv "${OUTPUT_DIR}"/reference/* "${OUTPUT_DIR}"
+
+###################################################################
+################### START OF POST-PROCESSING ######################
+###################################################################
+rm "${OUTPUT_DIR}/navtree_data.js" || true
+rm "${OUTPUT_DIR}/hierarchy.html" || true
+
+find ${OUTPUT_DIR} -name "*.html" | xargs sed -i '' "s|${SITE_PATH}/reference|${SITE_PATH}|g"
+find ${OUTPUT_DIR} -name "*.yaml" | xargs sed -i '' "s|${SITE_PATH}/reference|${SITE_PATH}|g"
+find ${OUTPUT_DIR} -name "*.html" | xargs sed -i '' "s|a href=\"reference/org/tensorflow|a href=\"${SITE_PATH}/org/tensorflow|g"
+find ${OUTPUT_DIR} -name "*.html" | xargs sed -i '' "s|a href=\"reference/com/google|a href=\"${SITE_PATH}/com/google|g"
+
+JAVA_LANG=https://docs.oracle.com/javase/8/docs/api
+find ${OUTPUT_DIR} -name "*.html" | xargs sed -i '' "s|a href=\"reference/java/lang|a href=\"${JAVA_LANG}/java/lang|g"
+
+find ${OUTPUT_DIR} -name "*.html" | xargs sed -i '' 's|
    |
    |g'
+
+rm ${OUTPUT_DIR}/timestamp.js || true
+rm ${OUTPUT_DIR}/lists.js || true
+rm ${OUTPUT_DIR}/index.html || true
+
+cp ${TEMPLATES}/screen.css ${OUTPUT_DIR}/
+
+