namespace tflite {

int8_t ConvertBuiltinCodeToDeprecatedBuiltinCode(
    const BuiltinOperator builtin_code);

// The following methods are for backward compatibility for the early version
// three, which does not have an extended builtin code.
flatbuffers::Offset<OperatorCode> CreateOperatorCode(
    flatbuffers::FlatBufferBuilder &_fbb,
    BuiltinOperator builtin_code = BuiltinOperator_ADD,

// the `builtin_code` as the right value.

BuiltinOperator GetBuiltinCode(const OperatorCode* op_code) {
  // Caller should guarantee that the given argument value is not a nullptr.
  TFLITE_DCHECK(op_code != nullptr);

  return std::max(
      op_code->builtin_code(),
      static_cast<BuiltinOperator>(op_code->deprecated_builtin_code()));
}

BuiltinOperator GetBuiltinCode(const OperatorCodeT* op_code) {

// problem. The new builtin operator will be assigned to the extended builtin
// code field in the flatbuffer schema. Those methods helps to hide builtin code
// details.
BuiltinOperator GetBuiltinCode(const OperatorCode *op_code);

BuiltinOperator GetBuiltinCode(const OperatorCodeT *op_code);

}  // namespace tflite

#include "tensorflow/compiler/mlir/lite/schema/schema_conversion_utils.h"

#include <algorithm>

namespace tflite {

int8_t ConvertBuiltinCodeToDeprecatedBuiltinCode(
    const BuiltinOperator builtin_code) {
  return (builtin_code < BuiltinOperator_PLACEHOLDER_FOR_GREATER_OP_CODES)
             ? static_cast<int8_t>(builtin_code)
             : static_cast<int8_t>(

struct CustomOpInfo {
  std::vector<std::int32_t> quantizable_input_indices;
  bool is_weight_only = false;
  bool no_side_effect = true;
};

using BuiltinOperatorSet = absl::flat_hash_set<tflite::BuiltinOperator>;
// Map from custom op code to custom op quantization information.
using CustomOpMap = std::unordered_map<std::string, CustomOpInfo>;

// Applies dynamic range quantization for the given model wehre the input_model

    }
    return false;
  }

  // Returns the producer op code of the specified tensor_idx.
  bool GetProducerOpCode(const Model* model, uint32_t subgraph_idx,
                         uint32_t tensor_idx, BuiltinOperator* op_code) {
    const auto subgraph = model->subgraphs()->Get(subgraph_idx);
    for (size_t op_idx = 0; op_idx < subgraph->operators()->size(); ++op_idx) {
      const auto op = subgraph->operators()->Get(op_idx);

// ones, but not by much. Moreover, while custom operators accept an opaque
// object containing configuration parameters, builtins have a predetermined
// set of acceptable options.
// LINT.IfChange
enum BuiltinOperator : int32 {
  ADD = 0,
  AVERAGE_POOL_2D = 1,
  CONCATENATION = 2,
  CONV_2D = 3,
  DEPTHWISE_CONV_2D = 4,
  DEPTH_TO_SPACE = 5,
  DEQUANTIZE = 6,
  EMBEDDING_LOOKUP = 7,
  FLOOR = 8,

    return "LSTM";
  }
  return name.upper();
}

// Emits a function that returns built-in operator code for each TFLite op.
//
// The signature of the function is:
//
//   std::optional<tflite::BuiltinOperator>
//   mlir::GetBuiltinOpCode(mlir::Operation* op);
//
// TODO(hinsu): Consider converting this to a static constant associative
// container instead of a series of if conditions, if required.

std::string GetMlirOpNameFromOpCode(const ::tflite::OperatorCodeT &op_code);

// Returns the builtin op code for the given MLIR operation on success; emits
// error and returns std::nullopt on failure.
std::optional<tflite::BuiltinOperator> GetBuiltinOpCode(Operation *mlir_op);

// Packs the given MLIR operation into a TFLite FlatBuffer operator object.
// Returns the FlatBuffer offset for the operator on success; emits error and

// ones, but not by much. Moreover, while custom operators accept an opaque
// object containing configuration parameters, builtins have a predetermined
// set of acceptable options.
// LINT.IfChange
enum BuiltinOperator : int32 {
  ADD = 0,
  AVERAGE_POOL_2D = 1,
  CONCATENATION = 2,
  CONV_2D = 3,
  DEPTHWISE_CONV_2D = 4,
  DEPTH_TO_SPACE = 5,
  DEQUANTIZE = 6,
  EMBEDDING_LOOKUP = 7,
  FLOOR = 8,