From 7b4d025aa03d2cdd684970e0dc7404f12bb98cd4 Mon Sep 17 00:00:00 2001 From: Neal Wu Date: Sun, 26 Mar 2017 23:58:02 -0700 Subject: [PATCH] Update slim README as well --- slim/README.md | 22 ++++------------------ 1 file changed, 4 insertions(+), 18 deletions(-) diff --git a/slim/README.md b/slim/README.md index 52eef6f4a9f..bf20a084c66 100644 --- a/slim/README.md +++ b/slim/README.md @@ -41,23 +41,9 @@ prerequisite packages. ## Installing latest version of TF-slim -As of 8/28/16, the latest [stable release of TF](https://www.tensorflow.org/versions/r0.10/get_started/os_setup.html#pip-installation) -is r0.10, which contains most of TF-Slim but not some later additions. To obtain the -latest version, you must install the most recent nightly build of -TensorFlow. You can find the latest nightly binaries at -[TensorFlow Installation](https://github.com/tensorflow/tensorflow#installation) -in the section that reads "People who are a little more adventurous can -also try our nightly binaries". Copy the link address that corresponds to -the appropriate machine architecture and python version, and pip install -it. For example: - -```shell -export TF_BINARY_URL=https://ci.tensorflow.org/view/Nightly/job/nightly-matrix-cpu/TF_BUILD_CONTAINER_TYPE=CPU,TF_BUILD_IS_OPT=OPT,TF_BUILD_IS_PIP=PIP,TF_BUILD_PYTHON_VERSION=PYTHON2,label=cpu-slave/lastSuccessfulBuild/artifact/pip_test/whl/tensorflow-0.10.0rc0-cp27-none-linux_x86_64.whl -sudo pip install --upgrade $TF_BINARY_URL -``` - -To test this has worked, execute the following command; it should run -without raising any errors. +TF-Slim is available as `tf.contrib.slim` via TensorFlow 1.0. To test that your +installation is working, execute the following command; it should run without +raising any errors. ``` python -c "import tensorflow.contrib.slim as slim; eval = slim.evaluation.evaluate_once" @@ -140,7 +126,7 @@ You can use the same script to create the mnist and cifar10 datasets. However, for ImageNet, you have to follow the instructions [here](https://github.com/tensorflow/models/blob/master/inception/README.md#getting-started). Note that you first have to sign up for an account at image-net.org. -Also, the download can take several hours, and uses about 500MB. +Also, the download can take several hours, and could use up to 500GB. ## Creating a TF-Slim Dataset Descriptor.