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

    "/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.");

namespace tfrt {
class CoreRuntime;
}

namespace mlir {
class ModuleOp;
}

namespace tensorflow {

// TFRTSavedModelSignatureInfo contains the metadata for a signature in the
// savedmodel such as function name, inputs/outputs' names and types. This can
// be used to retrieve these information in a tf_saved_model module.
struct TFRTSavedModelSignatureInfo {
  llvm::StringRef func_name;

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#include "tensorflow/compiler/mlir/tfrt/saved_model/saved_model.h"

#include <utility>

#include "llvm/ADT/STLFunctionalExtras.h"
#include "llvm/ADT/SmallVector.h"
#include "llvm/ADT/StringRef.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project

          " }. To inspect available tag-sets in the SavedModel, please "
          "use the SavedModel CLI: `saved_model_cli`"));
}

// Reads the SavedModel proto from saved_model.pb in `export_dir`.
// Returns a failure status when the SavedModel file does not exist.
Status ReadSavedModel(absl::string_view export_dir,
                      SavedModel* saved_model_proto) {
  LOG(INFO) << "Reading SavedModel from: " << export_dir;

  if (IS_OSS) {