explicit LiftQuantizableSpotsAsFunctionsDRQPass(
      const QuantMethod quantization_method, const OpSet target_opset,
      const int min_num_elements_for_weights) {
    quantization_method_ = quantization_method;
    target_opset_ = target_opset;
    min_num_elements_for_weights_ = min_num_elements_for_weights;
  }

  LiftQuantizableSpotsAsFunctionsDRQPass(
      const LiftQuantizableSpotsAsFunctionsDRQPass& other) {

  // supported for Post-training Dynamic Range Quantization. By default, it is
  // set to 1024. To disable this, set the value to -1 explicitly.
  int64 min_num_elements_for_weights = 8;

  // When set to `true`, freezes all variables in the model into constants.
  // When set to `false` the model's large constants are converted to variables.

  quant_specs.inference_type = tflite::TflTypeToTfType(inference_type);
  quant_specs.weight_quantization = true;
  quant_specs.weight_only_quantization = weight_only_quantization;
  quant_specs.minimum_elements_for_weights = minimum_elements_for_weights;
  quant_specs.disable_per_channel = disable_per_channel;
  quant_specs.legacy_float_scale = legacy_float_scale;
  quant_specs.ops_blocklist = denylisted_mlir_op_names;

    const tflite::TensorType& inference_type,
    const absl::flat_hash_set<std::string>& denylisted_ops,
    const CustomOpMap& custom_op_map,
    int64_t minimum_elements_for_weights = 1024,
    bool disable_per_channel = false, bool weight_only_quantization = false,
    bool legacy_float_scale = false);

// Overloading methods to support old quantizer versions API