# BEGIN TF CACHE HELPER OPTIONS
# Options when using remote execution

### Bug Fixes and Other Changes

*   `tf.SavedModel`:
    * Introduced new class `tf.saved_model.experimental.Fingerprint` that contains the fingerprint of the SavedModel. See the [SavedModel Fingerprinting RFC](https://github.com/tensorflow/community/pull/415) for details.
    * Introduced API `tf.saved_model.experimental.read_fingerprint(export_dir)` for reading the fingerprint of a SavedModel.
* `tf.random`

    ```bash
    bazel test ${flags} tensorflow/python/kernel_tests/nn_ops:softmax_op_test
    ```

    For a single/parameterized test e.g. `test_capture_variables` in
    `tensorflow/python/saved_model/load_test.py`:

    (Requires `python>=3.7`)

    ```bash
    bazel test ${flags} //tensorflow/python/saved_model:load_test --test_filter=*LoadTest.test_capture_variables*
    ```

#include "tensorflow/c/tf_buffer.h"
#include "tensorflow/c/tf_buffer_internal.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/cc/saved_model/signature_constants.h"
#include "tensorflow/cc/saved_model/tag_constants.h"
#include "tensorflow/core/example/example.pb.h"
#include "tensorflow/core/example/feature.pb.h"
#include "tensorflow/core/framework/api_def.pb.h"

#include "tensorflow/cc/framework/gradients.h"
#include "tensorflow/cc/framework/ops.h"
#include "tensorflow/cc/framework/scope_internal.h"
#include "tensorflow/cc/ops/while_loop.h"
#include "tensorflow/cc/saved_model/loader.h"
#include "tensorflow/core/distributed_runtime/server_lib.h"
#include "tensorflow/core/framework/logging.h"
#include "tensorflow/core/framework/op_gen_lib.h"

should be used with caution when working with untrusted models.

### Saved graphs and checkpoints

When loading untrusted serialized computation graphs (in form of a `GraphDef`,
`SavedModel`, or equivalent on-disk format), the set of computation primitives
available to TensorFlow is powerful enough that you should assume that the
TensorFlow process effectively executes arbitrary code.

setattr(_current_module, "initializers", _initializers)


# Do an eager load for Keras' code so that any function/method that needs to
# happen at load time will trigger, eg registration of optimizers in the
# SavedModel registry.
# See b/196254385 for more details.
try:
  if _tf_uses_legacy_keras:
    importlib.import_module("tf_keras.src.optimizers")
  else:
    importlib.import_module("keras.src.optimizers")