// applicable
  pm.addPass(mlir::quant::CreateQuantizeCompositeFunctionsPass(
      quantization_options.quantization_method().preset_method(),
      quantization_options.op_set(),
      quantization_options.enable_per_channel_quantization(),
      quantization_options.min_num_elements_for_weights(),
      quantization_options.enable_legacy_weight_only(), mlir_dump_file_prefix));
  pm.addPass(mlir::createSymbolDCEPass());

std::unique_ptr<OperationPass<ModuleOp>> CreateQuantizeCompositeFunctionsPass(
    tensorflow::quantization::QuantizationMethod::PresetMethod
        quantization_method,
    tensorflow::quantization::OpSet target_opset,
    bool enable_per_channel_quantization, int min_num_elements_for_weights,
    bool enable_legacy_weight_only = false,
    std::optional<const absl::string_view> mlir_dump_file_prefix =
        std::nullopt);

        ),
        _DYNAMIC_RANGE_DEFAULT_MIN_NUM_ELEMENTS_FOR_WEIGHTS,
    )

  if not quantization_options.HasField('enable_per_channel_quantization'):
    quantization_options.enable_per_channel_quantization = False

  if quantization_options.enable_per_channel_quantization and not (
      (
          quantization_options.op_set == quant_opts_pb2.OpSet.UNIFORM_QUANTIZED

  // TODO: b/331302857 - Remove `enable_per_channel_quantized_weight` usage.
  quantization_config.mutable_static_range_ptq_preset()
      ->set_enable_per_channel_quantized_weight(
          quantization_options.enable_per_channel_quantization());
  // When targeting server TPUs quantized types should be unpacked into
  // integer ops.
  quantization_config.mutable_pipeline_config()->set_unpack_quantized_types(
      true);