117 lines
4.0 KiB
Python
117 lines
4.0 KiB
Python
# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Tests for stateful tf.keras LSTM models using DistributionStrategy."""
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import numpy as np
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import tensorflow.compat.v2 as tf
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import keras
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from keras.distribute import keras_correctness_test_base
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from keras.optimizers.legacy import gradient_descent as gradient_descent_keras
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def strategies_for_stateful_embedding_model():
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"""Returns TPUStrategy with single core device assignment."""
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return [
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tf.__internal__.distribute.combinations.tpu_strategy_one_core,
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]
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def test_combinations_for_stateful_embedding_model():
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return tf.__internal__.test.combinations.combine(
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distribution=strategies_for_stateful_embedding_model(),
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mode="graph",
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use_numpy=False,
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use_validation_data=False,
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)
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class DistributionStrategyStatefulLstmModelCorrectnessTest(
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keras_correctness_test_base.TestDistributionStrategyEmbeddingModelCorrectnessBase # noqa: E501
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):
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def get_model(
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self,
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max_words=10,
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initial_weights=None,
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distribution=None,
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input_shapes=None,
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):
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del input_shapes
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batch_size = keras_correctness_test_base._GLOBAL_BATCH_SIZE
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with keras_correctness_test_base.MaybeDistributionScope(distribution):
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word_ids = keras.layers.Input(
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shape=(max_words,),
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batch_size=batch_size,
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dtype=np.int32,
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name="words",
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)
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word_embed = keras.layers.Embedding(input_dim=20, output_dim=10)(
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word_ids
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)
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lstm_embed = keras.layers.LSTM(
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units=4, return_sequences=False, stateful=True
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)(word_embed)
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preds = keras.layers.Dense(2, activation="softmax")(lstm_embed)
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model = keras.Model(inputs=[word_ids], outputs=[preds])
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if initial_weights:
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model.set_weights(initial_weights)
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optimizer_fn = gradient_descent_keras.SGD
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model.compile(
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optimizer=optimizer_fn(learning_rate=0.1),
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loss="sparse_categorical_crossentropy",
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metrics=["sparse_categorical_accuracy"],
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)
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return model
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# TODO(jhseu): Disabled to fix b/130808953. Need to investigate why it
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# doesn't work and enable for DistributionStrategy more generally.
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@tf.__internal__.distribute.combinations.generate(
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test_combinations_for_stateful_embedding_model()
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)
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def disabled_test_stateful_lstm_model_correctness(
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self, distribution, use_numpy, use_validation_data
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):
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self.run_correctness_test(
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distribution, use_numpy, use_validation_data, is_stateful_model=True
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)
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@tf.__internal__.distribute.combinations.generate(
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tf.__internal__.test.combinations.times(
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keras_correctness_test_base.test_combinations_with_tpu_strategies_graph() # noqa: E501
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)
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)
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def test_incorrectly_use_multiple_cores_for_stateful_lstm_model(
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self, distribution, use_numpy, use_validation_data
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):
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with self.assertRaisesRegex(
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ValueError, "not yet supported with tf.distribute.Strategy"
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):
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self.run_correctness_test(
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distribution,
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use_numpy,
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use_validation_data,
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is_stateful_model=True,
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)
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if __name__ == "__main__":
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tf.test.main()
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