Use '_' instead of '/' in feature names to avoid potential clash with

namescope separator. PiperOrigin-RevId: 299018918
m2kar · Mar 5, 2020 · 8e60b15 · 8e60b15
1 parent 4c8c0fe
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Showing 5 changed files with 8 additions and 5 deletions.
diff --git a/RELEASE.md b/RELEASE.md
@@ -152,6 +152,9 @@
 *   The ImporterNode now allows specification of general artifact properties.
 *   Added 'tfx_executor', 'tfx_version' and 'tfx_py_version' labels for CAIP,
     BQML and Dataflow jobs submitted from TFX components.
+*   Use '_' instead of '/' in feature names of several examples to avoid
+    potential clash with namescope separator.
+
 
 ### Deprecations
 

diff --git a/tfx/examples/mnist/README.md b/tfx/examples/mnist/README.md
@@ -11,8 +11,8 @@ Here is short summary of the example codes, status and known restrictions:
 
 *   The dataset included in this example consists of a selection of 1000 records
     from the MNIST dataset, converted to tfrecord format. Each record is
-    a tf.Example with 2 columns of data: 'image/floats' representing
-    the 28x28 image as 784 float values, and 'image/class' representing
+    a tf.Example with 2 columns of data: 'image_floats' representing
+    the 28x28 image as 784 float values, and 'image_class' representing
     the label with values [0-9] corresponding to decimal digit in the image.
 
     For a detailed description of tf.Example and TFRecord see

diff --git a/tfx/examples/mnist/data/mnist.tfrecord b/tfx/examples/mnist/data/mnist.tfrecord
diff --git a/tfx/examples/mnist/mnist_pipeline_native_keras.py b/tfx/examples/mnist/mnist_pipeline_native_keras.py
@@ -118,7 +118,7 @@ def _create_pipeline(pipeline_name: Text, pipeline_root: Text, data_root: Text,
   # Uses TFMA to compute an evaluation statistics over features of a model and
   # perform quality validation of a candidate model (compared to a baseline).
   eval_config = tfma.EvalConfig(
-      model_specs=[tfma.ModelSpec(label_key='image/class')],
+      model_specs=[tfma.ModelSpec(label_key='image_class')],
       slicing_specs=[tfma.SlicingSpec()],
       metrics_specs=[
           tfma.MetricsSpec(

diff --git a/tfx/examples/mnist/mnist_utils_native_keras.py b/tfx/examples/mnist/mnist_utils_native_keras.py
@@ -33,8 +33,8 @@
 
 # MNIST dataset consists of an image of the handwritten digits,
 # and it's label which is the class indicating digits 0 through 9.
-_IMAGE_KEY = 'image/floats'
-_LABEL_KEY = 'image/class'
+_IMAGE_KEY = 'image_floats'
+_LABEL_KEY = 'image_class'
 
 
 def _transformed_name(key):