struct PassConfig {
  explicit PassConfig(quant::QuantizationSpecs specs)
      : quant_specs(std::move(specs)) {}

  // If `emit_builtin_tflite_ops` is true, TF Lite legalization passes will be
  // added, which produces TF Lite ops.
  bool emit_builtin_tflite_ops = true;
  // If `lower_tensor_list_ops` is true, tensorlist ops will be lowered to basic
  // TF ops before legalization to TF Lite dialect.

  TF_ASSIGN_OR_RETURN(
      auto module, ConvertGraphdefToMlir(input, debug_info, specs, &context));

  mlir::TFL::PassConfig pass_config(quant_specs);
  bool emit_builtin_tflite_ops = !toco_flags.force_select_tf_ops();
  pass_config.emit_builtin_tflite_ops = emit_builtin_tflite_ops;
  pass_config.unfold_batch_matmul = toco_flags.unfold_batchmatmul();
  pass_config.lower_tensor_list_ops = toco_flags.lower_tensor_list_ops();

    TF_RETURN_IF_ERROR(HandleInputOutputArraysWithModule(model_flags, &module));
  }

  mlir::TFL::PassConfig pass_config(quant_specs);
  bool emit_builtin_tflite_ops = !toco_flags.force_select_tf_ops();
  pass_config.emit_builtin_tflite_ops = emit_builtin_tflite_ops;
  pass_config.enable_tflite_variables =
      toco_flags.enable_tflite_resource_variables();
  pass_config.unfold_batch_matmul = toco_flags.unfold_batchmatmul();

  TF_RETURN_IF_ERROR(internal::RegisterAllCustomOps(toco_flags));

  mlir::TFL::PassConfig pass_config(quant_specs);
  bool emit_builtin_tflite_ops = !toco_flags.force_select_tf_ops();
  pass_config.emit_builtin_tflite_ops = emit_builtin_tflite_ops;
  pass_config.enable_tflite_variables =
      toco_flags.enable_tflite_resource_variables();
  pass_config.unfold_batch_matmul = toco_flags.unfold_batchmatmul();

        "List of output tensors, if different from the default outputs"),
    llvm::cl::init(""));

using llvm::cl::opt;

// These command line flags enable control of the translation implementation.
bool emit_builtin_tflite_ops;
bool emit_custom_ops;
bool emit_select_tf_ops;
bool lower_tensor_list_ops;
bool strip_debug_info;
bool use_buffer_offset;
bool emit_stablehlo_ops;
bool disable_vhlo_to_stablehlo;

// NOLINTNEXTLINE

      return kTrFailure;
    }
    quant_specs.serialized_quant_stats = file->getBuffer().str();
  }

  mlir::TFL::PassConfig pass_config(quant_specs);
  pass_config.emit_builtin_tflite_ops = emit_builtin_tflite_ops;
  pass_config.lower_tensor_list_ops = lower_tensor_list_ops;
  pass_config.unfold_batch_matmul = unfold_batchmatmul;
  pass_config.unfold_large_splat_constant = unfold_large_splat_constant;

#include "tensorflow/lite/toco/toco_flags.pb.h"

namespace tflite {
// Options for exporting to Flatbuffer.
struct FlatbufferExportOptions {
  // TocoFlags proto. The following fields are migrated.
  // bool emit_builtin_tflite_ops  -> !toco_flags.force_select_tf_ops()
  // bool emit_select_tf_ops       -> toco_flags.enable_select_tf_ops()
  // bool emit_custom_ops          -> toco_flags.allow_custom_ops()

  // The tensorflow list is not supported right now by that pass.
  // Enable fusing composite ops that can be lowered to built-in TFLite ops.
  if (pass_config.emit_builtin_tflite_ops &&
      toco_flags.tf_quantization_mode().empty()) {
    pass_manager->addPass(mlir::TFL::CreatePrepareCompositeFunctionsPass());
  }

  pass_manager->addPass(mlir::createInlinerPass());

  }

  // TODO: b/176267167 - Quantize flex fallback in the MLIR pipeline
  if (quant_specs.weight_quantization &&
      (!quant_specs.RunAndRewriteDynamicRangeQuantizationPasses() ||
       !pass_config.emit_builtin_tflite_ops)) {
    // Apply post-training dynamic range quantization from the old TOCO
    // quantizer.Once MLIR has support for this, we can remove this if
    // statement.