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models.BUILD
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SECURITY.md
TensorFlow [**models**](https://developers.google.com/machine-learning/glossary/#model) (to use a term commonly used by machine learning practitioners) are expressed as programs that TensorFlow executes. TensorFlow programs are encoded as computation [**graphs**](https://developers.google.com/machine-learning/glossary/#graph). Since models are practically programs that TensorFlow executes, using untrusted
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README.md
## Resources * [TensorFlow.org](https://www.tensorflow.org) * [TensorFlow Tutorials](https://www.tensorflow.org/tutorials/) * [TensorFlow Official Models](https://github.com/tensorflow/models/tree/master/official) * [TensorFlow Examples](https://github.com/tensorflow/examples) * [TensorFlow Codelabs](https://codelabs.developers.google.com/?cat=TensorFlow)
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RELEASE.md
* For Keras model, the individual call of `Model.evaluate` uses no cached data for evaluation, while `Model.fit` uses cached data when `validation_data` arg is provided for better performance. * Adds a `save_traces` argument to `model.save`/ `tf.keras.models.save_model` which determines whether the SavedModel format stores the Keras model/layer
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tensorflow/BUILD
"//tensorflow/c:logging", "//tensorflow/c:ops", "//tensorflow/cc/saved_model:fingerprinting_impl", "//tensorflow/cc/saved_model:loader_lite_impl", "//tensorflow/cc/saved_model:metrics_impl", "//tensorflow/compiler/tf2tensorrt:op_converter_registry_impl", "//tensorflow/core/common_runtime:core_cpu_impl",
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