# Mapping of signature def key -> SignatureDef.
_SignatureDefMap = Mapping[str, meta_graph_pb2.SignatureDef]


def _serialize_signature_def_map(
    signature_def_map: _SignatureDefMap,
) -> dict[str, bytes]:
  """Serializes SignatureDef values in `signature_def_map`.

  Args:
    signature_def_map: Signature key -> SignatureDef mapping.

  Returns:

using ::stablehlo::quantization::QuantizationConfig;
using ::tensorflow::SignatureDef;
using ::tensorflow::quantization::PyFunctionLibrary;

// Returns signature key -> `SignatureDef` mapping, excluding the signature for
// initialization op, which is only used during initialization.
// TODO: b/314124142 - Remove the need for this function.
absl::flat_hash_map<std::string, SignatureDef> GetSignatureDefMapFromBundle(

#include "tensorflow/core/framework/attr_value.pb.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"

namespace py = pybind11;

namespace {

using ::tensorflow::SignatureDef;
using ::tensorflow::quantization::ExportedModel;
using ::tensorflow::quantization::PyFunctionLibrary;
using ::tensorflow::quantization::QuantizationOptions;
using ::tensorflow::quantization::QuantizeDynamicRangePtq;

#include "tensorflow/core/protobuf/saver.pb.h"
#include "tsl/platform/statusor.h"

namespace mlir::quant::stablehlo {

using ::stablehlo::quantization::QuantizationConfig;
using ::tensorflow::SignatureDef;
using ::tensorflow::quantization::ExportedModel;
using ::tensorflow::quantization::PyFunctionLibrary;

StaticRangePtqComponent::StaticRangePtqComponent(
    absl::Nonnull<MLIRContext*> ctx,

namespace stablehlo::quantization::pywrap {

using ::mlir::quant::stablehlo::QuantizeStaticRangePtq;
using ::mlir::quant::stablehlo::QuantizeWeightOnlyPtq;
using ::tensorflow::SignatureDef;
using ::tensorflow::quantization::PyFunctionLibrary;

// Note for maintainers: the definitions should ONLY mirror existing functions
// defined in different targets. Do not include any extra business logic that

    absl::string_view src_saved_model_path,
    absl::string_view dst_saved_model_path, const QuantizationConfig& config,
    const std::vector<std::string>& signature_keys,
    const absl::flat_hash_map<std::string, tensorflow::SignatureDef>&
        signature_def_map,
    const tensorflow::quantization::PyFunctionLibrary& py_function_library);

// Function used by the pywrap_quantization module to mirror
// `::mlir::quant::stablehlo::QuantizeWeightOnlyPtq`.

# Mapping of signature def key -> SignatureDef.
_SignatureDefMap = Mapping[str, meta_graph_pb2.SignatureDef]


def get_signatures_from_saved_model(
    saved_model_path: str,
    signature_keys: Optional[Sequence[str]] = None,
    tags: Optional[Collection[str]] = None,
) -> Dict[str, meta_graph_pb2.SignatureDef]:
  """Gets a map from signature keys to their SignatureDef.

  Args:

          py_function_library,
      absl::string_view src_saved_model_path,
      std::vector<std::string> signature_keys,
      std::unordered_set<std::string> tags,
      absl::flat_hash_map<std::string, tensorflow::SignatureDef>
          signature_def_map,
      absl::flat_hash_map<FunctionName, FunctionAlias> function_aliases);

  // Runs the static-range post-training quantization (PTQ) on `module_op`.
  absl::StatusOr<ModuleOp> Run(

        )

    self.assertIsNone(repr_dataset.get_num_samples(LenRaisingError()))

  @test_util.deprecated_graph_mode_only
  def test_create_feed_dict_from_input_data(self):
    signature_def = meta_graph_pb2.SignatureDef(
        inputs={'input_tensor': meta_graph_pb2.TensorInfo(name='input:0')}
    )
    rng = np.random.default_rng(seed=14)

    input_tensor_value = rng.random(size=(2, 2))

    sess: session.Session,
    signature_def: meta_graph_pb2.SignatureDef,
    representative_dataset: rd.RepresentativeDataset,
) -> None:
  """Runs the representative dataset through a function for calibration.

  NOTE: This is intended to be run in graph mode (TF1).

  The function is identified by the SignatureDef.

  Args:
    sess: The Session object to run the function in.