/// SavedModel.
  virtual Session* GetSession() const = 0;

  /// Returns a map from signature name to SignatureDef for all signatures in
  /// in the SavedModel.
  virtual const protobuf::Map<string, SignatureDef>& GetSignatures() const = 0;
};

/// SavedModel representation once the SavedModel is loaded from storage.
///

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;

/// Classification API constants.

/// Classification inputs.
static constexpr char kClassifyInputs[] = "inputs";

/// Classification method name used in a SignatureDef.
static constexpr char kClassifyMethodName[] = "tensorflow/serving/classify";

/// Classification classes output.
static constexpr char kClassifyOutputClasses[] = "classes";

/// Classification scores output.

#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,

    tags = {tag_constants.SERVING}
    signature_key = signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY

    input_placeholder = self._create_and_save_tf1_conv_model(
        self._input_saved_model_path,
        signature_key,
        tags,
        input_key='p',
        output_key='output',
        use_variable=False,
    )

    signature_keys = [signature_key]

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`.

// https://github.com/tensorflow/tensorflow/blob/9bcefa44cd335c1db4a703a13da09f29ae1bbdb2/tensorflow/python/saved_model/signature_serialization.py#L181-L230
// One of the critical requirements of SignatureDef functions is that their
// inputs and outputs are "named". For example, a `.signatures` function:
// a. Requires users to pass: kwargs of all inputs:

          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(