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

*   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

## 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)

                "//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",