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STT-tensorflow/tensorflow/python/keras
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api
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applications
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benchmark
Add fused/non-fused inference/training overhead benchmarks for
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datasets
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distribute
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engine
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estimator
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feature_column
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initializers
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integration_test
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layers
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legacy_tf_layers
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mixed_precision
Allow tf.distribute.TPUStrategy to be used with TPUEmbedding API and ensure that LossScaleOptimizer properly rejects it.
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optimizer_v2
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premade
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preprocessing
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protobuf
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tests
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utils
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wrappers
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__init__.py
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activations_test.py
fix conflict
2020-03-11 11:09:44 -07:00
activations.py
Merge pull request #27814 from Bharat123rox:update-elu
2020-06-10 14:16:42 -07:00
backend_config_test.py
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backend_config.py
Add dispatch support to more Python APIs.
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backend_test.py
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backend.py
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BUILD
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callbacks_test.py
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callbacks_v1_test.py
Update tests under keras to use combinations.
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callbacks_v1.py
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callbacks.py
Fix the api docstrings for on_*_batch_begin methods in callbacks.Callback
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combinations_test.py
Add test combinations for Keras test.
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combinations.py
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constraints_test.py
Update tests under Keras to use combination.
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constraints.py
Improve keras.constraints docstrings.
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initializers_test.py
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keras_parameterized_test.py
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keras_parameterized.py
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losses_test.py
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losses.py
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metrics_confusion_matrix_test.py
Fix bug in SensitivitySpecificityBase derived metrics.
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metrics_correctness_test.py
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metrics_functional_test.py
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metrics_test.py
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metrics.py
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models_test.py
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models.py
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optimizers_test.py
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optimizers.py
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README.md
Branch 167812735 (#12867)
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regularizers_test.py
Stop skipping KerasTensors for Keras tests that now work with KerasTensors.
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regularizers.py
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testing_utils.py
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README.md

Keras is an object-oriented API for defining and training neural networks.

This module contains a pure-TensorFlow implementation of the Keras API, allowing for deep integration with TensorFlow functionality.

See keras.io for complete documentation and user guides.