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.

        ":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`.

    "/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.");

#include "tensorflow/cc/saved_model/loader.h"

#include <memory>
#include <string>
#include <unordered_set>
#include <utility>

#include "absl/status/status.h"
#include "absl/strings/str_cat.h"
#include "absl/strings/str_join.h"
#include "tensorflow/cc/saved_model/constants.h"
#include "tensorflow/cc/saved_model/fingerprinting.h"
#include "tensorflow/cc/saved_model/loader_util.h"

  FingerprintDef fingerprint_def;
  SavedModel saved_model;

  // Set the saved_model_checksum.
  TF_ASSIGN_OR_RETURN(uint64_t saved_model_hash,
                      HashFields(chunk_metadata.message(), reader, chunks_info,
                                 {}, &saved_model));
  saved_model_hash = FingerprintCat64(
      saved_model_hash, Fingerprint64(SerializeProto(saved_model)));

==============================================================================*/

#include "tensorflow/cc/saved_model/constants.h"
#include "tensorflow/cc/saved_model/loader.h"
#include "tensorflow/cc/saved_model/metrics.h"
#include "tensorflow/cc/saved_model/reader.h"
#include "tensorflow/cc/saved_model/signature_constants.h"
#include "tensorflow/cc/saved_model/tag_constants.h"
#include "tensorflow/core/example/example.pb.h"

    return 0;
  }
}

uint64_t HashSavedModel(const SavedModel& saved_model) {
  std::string saved_model_serialized;
  {
    // Local scope guarantees coded stream will be trimmed (ensures
    // serialization determinism).
    // Unfortunately the saving process itself isn't deterministic, so the
    // checksum may still change since the saved_model proto may be different.
    StringOutputStream stream(&saved_model_serialized);

#include "tensorflow/c/experimental/saved_model/core/revived_types/tensorhandle_convertible.h"
#include "tensorflow/c/experimental/saved_model/core/revived_types/tf_concrete_function.h"
#include "tensorflow/c/experimental/saved_model/core/revived_types/variable.h"
#include "tensorflow/c/experimental/saved_model/core/saved_model_utils.h"
#include "tensorflow/c/experimental/saved_model/core/signature_def_function.h"