From fc531df8ce3df4fd434230dd3bd0e7fdfe5a6cf1 Mon Sep 17 00:00:00 2001 From: Tomer Kaftan Date: Mon, 15 Jun 2020 14:20:38 -0700 Subject: [PATCH] Stop skipping KerasTensors for Keras tests that now work with KerasTensors. PiperOrigin-RevId: 316543523 Change-Id: Iea54fa7ed735e239cda293304c6a17207b136ab7 --- .../python/keras/engine/training_test.py | 5 +--- .../preprocessing/category_encoding_test.py | 26 ++++++++----------- .../python/keras/premade/linear_test.py | 3 +-- .../python/keras/premade/wide_deep_test.py | 3 +-- tensorflow/python/keras/regularizers_test.py | 8 +++--- 5 files changed, 18 insertions(+), 27 deletions(-) diff --git a/tensorflow/python/keras/engine/training_test.py b/tensorflow/python/keras/engine/training_test.py index bb6bfc32921..aa01463582c 100644 --- a/tensorflow/python/keras/engine/training_test.py +++ b/tensorflow/python/keras/engine/training_test.py @@ -1563,10 +1563,7 @@ class TrainingTest(keras_parameterized.TestCase): self.assertEqual(self.evaluate(layer.v), 1.) @keras_parameterized.run_all_keras_modes( - always_skip_v1=True, - # TODO(kaftan): this is failing with KerasTensors - # in a way that seems orthogonal to what the code is testing - skip_keras_tensors=True) + always_skip_v1=True) @parameterized.named_parameters( ('numpy_array', 'numpy_array'), ('dataset_array', 'dataset_array'), diff --git a/tensorflow/python/keras/layers/preprocessing/category_encoding_test.py b/tensorflow/python/keras/layers/preprocessing/category_encoding_test.py index ff1a06a3ae7..7e7f7f32be0 100644 --- a/tensorflow/python/keras/layers/preprocessing/category_encoding_test.py +++ b/tensorflow/python/keras/layers/preprocessing/category_encoding_test.py @@ -31,7 +31,6 @@ from tensorflow.python.framework import dtypes from tensorflow.python.framework import sparse_tensor from tensorflow.python.keras import backend from tensorflow.python.keras import keras_parameterized -from tensorflow.python.keras import testing_utils from tensorflow.python.keras.layers import core from tensorflow.python.keras.layers.preprocessing import category_encoding from tensorflow.python.keras.layers.preprocessing import category_encoding_v1 @@ -252,24 +251,21 @@ class CategoryEncodingInputTest(keras_parameterized.TestCase, sparse_ops.sparse_tensor_to_dense(sp_output_dataset, default_value=0), output_dataset) - # TODO(b/158570051): Support KerasTensor - # Keras functional model doesn't support dense layer stacked with sparse out. def test_sparse_output_and_dense_layer(self): - with testing_utils.use_keras_tensors_scope(False): - input_array = constant_op.constant([[1, 2, 3], [3, 3, 0]]) + input_array = constant_op.constant([[1, 2, 3], [3, 3, 0]]) - max_tokens = 4 + max_tokens = 4 - input_data = keras.Input(shape=(None,), dtype=dtypes.int32) - encoding_layer = get_layer_class()( - max_tokens=max_tokens, output_mode=category_encoding.COUNT, - sparse=True) - int_data = encoding_layer(input_data) - dense_layer = keras.layers.Dense(units=1) - output_data = dense_layer(int_data) + input_data = keras.Input(shape=(None,), dtype=dtypes.int32) + encoding_layer = get_layer_class()( + max_tokens=max_tokens, output_mode=category_encoding.COUNT, + sparse=True) + int_data = encoding_layer(input_data) + dense_layer = keras.layers.Dense(units=1) + output_data = dense_layer(int_data) - model = keras.Model(inputs=input_data, outputs=output_data) - _ = model.predict(input_array, steps=1) + model = keras.Model(inputs=input_data, outputs=output_data) + _ = model.predict(input_array, steps=1) @keras_parameterized.run_all_keras_modes diff --git a/tensorflow/python/keras/premade/linear_test.py b/tensorflow/python/keras/premade/linear_test.py index 6fa1767a60a..676f29bb840 100644 --- a/tensorflow/python/keras/premade/linear_test.py +++ b/tensorflow/python/keras/premade/linear_test.py @@ -40,8 +40,7 @@ from tensorflow.python.ops import variables from tensorflow.python.platform import test -@keras_parameterized.run_all_keras_modes(always_skip_v1=True, - skip_keras_tensors=True) +@keras_parameterized.run_all_keras_modes(always_skip_v1=True) class LinearModelTest(keras_parameterized.TestCase): def test_linear_model_with_single_input(self): diff --git a/tensorflow/python/keras/premade/wide_deep_test.py b/tensorflow/python/keras/premade/wide_deep_test.py index eae28c31df8..591b53e9a84 100644 --- a/tensorflow/python/keras/premade/wide_deep_test.py +++ b/tensorflow/python/keras/premade/wide_deep_test.py @@ -37,8 +37,7 @@ from tensorflow.python.ops import variables from tensorflow.python.platform import test -@keras_parameterized.run_all_keras_modes(always_skip_v1=True, - skip_keras_tensors=True) +@keras_parameterized.run_all_keras_modes(always_skip_v1=True) class WideDeepModelTest(keras_parameterized.TestCase): def test_wide_deep_model(self): diff --git a/tensorflow/python/keras/regularizers_test.py b/tensorflow/python/keras/regularizers_test.py index c2c2e6c4a01..b10218ba114 100644 --- a/tensorflow/python/keras/regularizers_test.py +++ b/tensorflow/python/keras/regularizers_test.py @@ -83,7 +83,7 @@ class KerasRegularizersTest(keras_parameterized.TestCase, self.assertEqual(len(model.losses), 1) model.fit(x_train, y_train, batch_size=10, epochs=1, verbose=0) - @keras_parameterized.run_all_keras_modes(skip_keras_tensors=True) + @keras_parameterized.run_all_keras_modes @parameterized.named_parameters([ ('l1', regularizers.l1()), ('l2', regularizers.l2()), @@ -126,7 +126,7 @@ class KerasRegularizersTest(keras_parameterized.TestCase, model.get_config(), custom_objects={'my_regularizer': my_regularizer}) self.assertEqual(model2.layers[1].kernel_regularizer, my_regularizer) - @keras_parameterized.run_all_keras_modes(skip_keras_tensors=True) + @keras_parameterized.run_all_keras_modes @parameterized.named_parameters([ ('l1', regularizers.l1()), ('l2', regularizers.l2()), @@ -144,7 +144,7 @@ class KerasRegularizersTest(keras_parameterized.TestCase, run_eagerly=testing_utils.should_run_eagerly()) self.assertLen(model.losses, 5) - @keras_parameterized.run_all_keras_modes(skip_keras_tensors=True) + @keras_parameterized.run_all_keras_modes @parameterized.named_parameters([ ('l1', regularizers.l1()), ('l2', regularizers.l2()), @@ -166,7 +166,7 @@ class KerasRegularizersTest(keras_parameterized.TestCase, run_eagerly=testing_utils.should_run_eagerly()) self.assertLen(model.losses, 6) - @keras_parameterized.run_all_keras_modes(skip_keras_tensors=True) + @keras_parameterized.run_all_keras_modes @parameterized.named_parameters([ ('l1', regularizers.l1()), ('l2', regularizers.l2()),