from tensorflow.python.framework import ops
from tensorflow.python.lib.io import file_io
from tensorflow.python.saved_model import builder
from tensorflow.python.saved_model import constants as saved_model_constants
from tensorflow.python.saved_model import loader_impl as saved_model_loader
from tensorflow.python.saved_model import tag_constants
from tensorflow.python.training import saver

# Mapping of signature def key -> SignatureDef.

    dst_saved_model_path: str,
    config: qc.QuantizationConfig,
) -> None:
  """Quantizes a saved model.

  Args:
    src_saved_model_path: Path to the directory for the source SavedModel.
    dst_saved_model_path: Path to the directory for the destination SavedModel.
    config: Quantization configuration.

  Raises:
    ValueError: When `config` was not configured for static-range PTQ
    single representative dataset.
  """

        ":pywrap_quantize_model",
        "//tensorflow:tensorflow_py",
        "//tensorflow/python/platform:client_testlib",
    ],
)

pytype_strict_library(
    name = "save_model",
    srcs = [
        "save_model.py",
    ],
    deps = [
        "//tensorflow/core:protos_all_py",
        "//tensorflow/python/client:session",
        "//tensorflow/python/framework:importer",

from tensorflow.compiler.mlir.quantization.tensorflow.python import save_model
from tensorflow.core.protobuf import meta_graph_pb2
from tensorflow.python.lib.io import file_io
from tensorflow.python.saved_model import load as saved_model_load
from tensorflow.python.saved_model import loader_impl as saved_model_loader
from tensorflow.python.saved_model import signature_constants
from tensorflow.python.saved_model import tag_constants

    """Saves `ExportedModel` to `dst_saved_model_path` as a SavedModel.

    Args:
      dst_saved_model_path: Destination path to save the exported model.
      exported_model_serialized: Exported model to export as SavedModel.
      src_saved_model_path: Path to the source SavedModel. This will be used to
        copy the asset files to `dst_saved_model_path`.

from tensorflow.python.saved_model import builder
from tensorflow.python.saved_model import loader_impl as saved_model_loader
from tensorflow.python.saved_model import save as saved_model_save
from tensorflow.python.saved_model import save_options
from tensorflow.python.saved_model import signature_constants
from tensorflow.python.saved_model import signature_def_utils_impl

// SavedModel proto filename prefix.
inline constexpr char kSavedModelFilenamePrefix[] = "saved_model";
// SavedModel proto filename.
inline constexpr char kSavedModelFilenamePb[] = "saved_model.pb";

// SavedModel chunked proto filename.
inline constexpr char kSavedModelFilenameCpb[] = "saved_model.cpb";

// SavedModel text format proto filename.
inline constexpr char kSavedModelFilenamePbTxt[] = "saved_model.pbtxt";

#include <vector>

#include "tensorflow/c/experimental/saved_model/public/saved_model_api.h"
#include "tensorflow/cc/experimental/base/public/runtime.h"
#include "tensorflow/cc/experimental/base/public/status.h"
#include "tensorflow/cc/saved_model/experimental/public/concrete_function.h"
#include "tensorflow/cc/saved_model/experimental/public/concrete_function_list.h"
#include "tensorflow/cc/saved_model/experimental/public/signature_def_function.h"

    "/tensorflow/core/saved_model/read/fingerprint",
    "The fingerprint (saved_model_checksum) of the loaded SavedModel.");

// Gauge that contains the path (saved_model_path) of the loaded SavedModel.
auto* saved_model_read_path = monitoring::Gauge<std::string, 0>::New(
    "/tensorflow/core/saved_model/read/path",
    "The path (saved_model_path) of the loaded SavedModel.");

# Tensorflow C SavedModel API

## Overview

These are the new experimental C SavedModel APIs for loading and running
SavedModels in a TF2-idiomatic fashion. See
[RFC 207](https://github.com/tensorflow/community/pull/207) for additional
context.

The directory structure is as follows:

```none
saved_model/

  public/

  internal/

  core/

```

## saved_model/public