// Deletes a TF_SavedModel, and frees any resources owned by it.
TF_CAPI_EXPORT extern void TF_DeleteSavedModel(TF_SavedModel* model);

// Retrieve a function from the TF2 SavedModel via function path.
//
// Params:
//  model - The TF2 SavedModel to load a function from.
//  function_path - A string containing the path from the root saved python
//                  object to a tf.function method.

// this class. Eventually we want to remove this virtual base class indirection
// and have only a single implementation.
class SavedModelAPI {
 public:
  // Retrieve a function from the TF2 SavedModel, using the "path" to a function
  // in a TF2 savedmodel.
  //
  // Note: `function` is a double pointer, so that implementations are
  // able to return a pointer to an internal member.

namespace experimental {
namespace cc {

// SavedModelAPI offers a way to load Tensorflow Saved Models
// (https://www.tensorflow.org/guide/saved_model) and execute saved
// tf.functions or legacy SignatureDefs in a TF2-idiomatic fashion.
// See RFC 207
// (https://github.com/tensorflow/community/blob/master/rfcs/20200218-tf-c-saved-model.md)
// TODO(bmzhao): Add an e2e example here, once ConcreteFunction::Run is added.
class SavedModelAPI {

	tf11 = tf1 / 0 /* ERROR "division by zero" */
	tf12 = tf3 /* ERROR "mismatched types" */ / tf0

	tf16 = tf2 /* ERROR "mismatched types" */ & tf3
	tf17 = tf2 /* ERROR "mismatched types" */ | tf3
	tf18 = tf2 /* ERROR "mismatched types" */ ^ tf3

	// complex values
	tc0 = 0.i
	tc1 = 1.i
	tc2 = 4.2e1i
	tc3 = 3.141592653589793238462643383279502884197169399375105820974944592307816406286i
	tc4 = 1e-1i

  // of the inputs and outputs of a function.
  // Note(bmzhao): saved_concrete_func_ is guaranteed to be non-null.
  const SavedConcreteFunction* saved_concrete_func;

  // This field is only present on TF2 ConcreteFunctions, and is useful for
  // determining the original argument *names* of the function, (since the
  // "canonicalized_input_signature" may append extra uniquifying integers).

)
```

When this option is enabled, exported SavedModels with proto size > 2GB will
automatically save with the new format (`.cpb` instead of `.pb`).

<!-- **Compatibility** -->

The official TF APIs (TF1/TF2 python or C++ loading) have already been
integrated to handle the new format, but some downstream converters may not

namespace tensorflow {
namespace experimental {
namespace cc {

// SignatureDefFunctions are functions that correspond to either:
// "signatures" saved from a TF2 SavedModel APIs:
// https://github.com/tensorflow/tensorflow/blob/8ce0600f58ed84a8c84a7bbdb014d1f09e44f4c8/tensorflow/python/saved_model/save.py#L830-L854
// Or the "SignatureDefMap" saved from TF1 SavedModel APIs:

namespace tensorflow {

// RestoredResource represents a TF2 "Resource" object loaded from a savedmodel,
// analogous to the Python _RestoredResource object:
// https://github.com/tensorflow/tensorflow/blob/fda326e542ca67534e8411edb180e8760a4828b7/tensorflow/python/saved_model/load.py#L481
// TF2 resource objects typically extend TrackableResource:

from tensorflow.python.util.lazy_loader import KerasLazyLoader as _KerasLazyLoader

# Make sure code inside the TensorFlow codebase can use tf2.enabled() at import.
_os.environ["TF2_BEHAVIOR"] = "1"
from tensorflow.python import tf2 as _tf2
_tf2.enable()

# API IMPORTS PLACEHOLDER

# WRAPPER_PLACEHOLDER

# Make sure directory containing top level submodules is in

"""Serves as a common "main" function for all the SavedModel tests.

There is a fair amount of setup needed to initialize tensorflow and get it
into a proper TF2 execution mode. This hides that boilerplate.
"""

import tempfile

from absl import app
from absl import flags
from absl import logging
import tensorflow.compat.v2 as tf