mlir::quant::QuantizationSpecs quant_specs;
  if (mlir::quant::ParseInputNodeQuantSpecs(
          input_arrays, min_values, max_values, inference_type, &quant_specs)) {
    llvm::errs() << "Failed to get input quant spec.";
    return kTrFailure;
  }
  if (weight_quantization != "NONE") {
    quant_specs.weight_quantization = true;
    if (weight_quantization == "INT8") {

  const mlir::quant::QuantizationSpecs& quant_specs = pass_config.quant_specs;
  OpOrArgLocNameMapper op_or_arg_name_mapper;
  tflite::FlatbufferExportOptions options;
  std::string translated_result;
  options.toco_flags = toco_flags;
  options.saved_model_tags = saved_model_tags;
  options.op_or_arg_name_mapper = &op_or_arg_name_mapper;
  if (quant_specs.support_mask !=

// Creates an instance of the TensorFlow Lite dialect Quantize pass.
// Use quant_specs.ops_blocklist and quant_specs.nodes_blocklist if possible
// as they are now structure variables of QuantizationSpecs.
std::unique_ptr<OperationPass<func::FuncOp>> CreateQuantizePass(
    const quant::QuantizationSpecs& quant_specs,
    const absl::flat_hash_set<std::string>& ops_blocklist = {},

  // Initialize for tests.
  void initializeForTest() {
    if (!test_mode_) return;

    tensorflow::quantization::QuantizationComponentSpec quant_spec;
    quant_spec.set_quantization_component(
        tensorflow::quantization::QuantizationComponentSpec::COMPONENT_WEIGHT);
    quant_spec.set_tensor_type(
        tensorflow::quantization::QuantizationComponentSpec::TENSORTYPE_INT_8);

std::unique_ptr<OperationPass<func::FuncOp>> CreateQuantizePass(
    QuantizationSpecs quant_specs,
    tensorflow::quantization::OpSet target_opset);

// Creates an instance of the PrepareQuantize pass, which will perform similar
// transformations as TFL::PrepareQuantizePass.
std::unique_ptr<OperationPass<func::FuncOp>> CreatePrepareQuantizePass(
    const QuantizationSpecs& quant_specs,
    tensorflow::quantization::QuantizationMethod::PresetMethod

    absl::flat_hash_set<std::string> ops_blocklist =
        quant_params_.quant_spec.ops_blocklist;
    absl::flat_hash_set<std::string> nodes_blocklist =
        quant_params_.quant_spec.nodes_blocklist;
    CustomMap custom_map = quant_params_.quant_spec.custom_map;

    // Rewrite the floating-point ops to the quantized version, by fusing
    // preceding dequantize ops and succeding quantize ops.

                              absl::string_view max_values,
                              absl::string_view inference_type,
                              QuantizationSpecs* quant_specs);

// Gets the quantization specification for input arrays. The array names are not
// stored in the spec, and will be matched by position. The min/max will be