&mlir::OpBuilder::setInsertionPoint))
      .def("saveInsertionPoint", &mlir::OpBuilder::saveInsertionPoint)
      .def("restoreInsertionPoint", &mlir::OpBuilder::restoreInsertionPoint)
      .def(
          "create",
          [](mlir::OpBuilder& opb, mlir::OperationState& state) {
            return opb.create(state);
          },
          py::return_value_policy::reference)
      .def("getContext", &mlir::OpBuilder::getContext,

                                  OpBuilder builder);

  mlir::Type input_type;
  mlir::Type output_type;
};

LogicalResult ModifyIONodesPass::SetupInputOutputTypesIfNull(
    OpBuilder builder) {
  if (input_type && output_type) return success();

  auto convert_str_to_type = [&builder](absl::string_view str) -> Type {
    if (str == "int8") {
      return builder.getIntegerType(8);
    } else if (str == "uint8") {

  let extraClassDeclaration = [{
    OpBuilder getThenBodyBuilder(OpBuilder::Listener *listener = nullptr) {
      Block* body = getBody(0);
      return getResults().empty() ? OpBuilder::atBlockTerminator(body, listener)
                               : OpBuilder::atBlockEnd(body, listener);
    }
    OpBuilder getElseBodyBuilder(OpBuilder::Listener *listener = nullptr) {
      Block* body = getBody(1);

  TF_Status* status = TF_NewStatus();

  TF_OpDefinitionBuilder* op_builder =
      TF_NewOpDefinitionBuilder("MergeSummary");
  TF_OpDefinitionBuilderAddInput(op_builder, "inputs: N * string");
  TF_OpDefinitionBuilderAddOutput(op_builder, "summary: string");
  TF_OpDefinitionBuilderAddAttr(op_builder, "N: int >= 1");
  TF_OpDefinitionBuilderSetShapeInferenceFunction(
      op_builder, &merge_summary_shape_inference_fn);

      .def("create",
           [](mlir::OpBuilder& opb, mlir::Location loc, mlir::Value x,
              mlir::Value y) -> mlir::Operation* {
             return opb.create<mlir::TF::AddV2Op>(loc, x, y).getOperation();
           });

  py::class_<mlir::TF::AnyOp>(m, "Tf_AnyOp")
      .def("create",
           [](mlir::OpBuilder& opb, mlir::Location loc, mlir::Value input,

    resultType = $_builder.getNoneType();
  }
  return build($_builder, $_state, resultType, x, y);
}]>];
}

// Mixin class defining a builder for comparison ops supporting broadcast
// behavior. The result type has bool element type.
class WithBroadcastableCmpOpBuilder {
  list<OpBuilder> builders = [
    OpBuilder<(ins "Value":$x, "Value":$y),
    [{
  Type resultType;

  "CreateCastToInt32($0, $_loc, $_builder)">;

def CreateInt32ConstOrCast : NativeCodeCall<
  "CreateInt32ConstOrCast($0, $_loc, $_builder)">;

// Creates an int32 constant op from an integer attribute $0.
def CreateInt32ConstOpFromIntAttr

  "CreateCastToInt32($0, $_loc, $_builder)">;
// TODO: b/304003568 - Add TF_TransposeOp folding logic to tflite.
def LegalizeTranspose : Pat<(MHLO_TransposeOp $arg, $perm),
                            (TFL_TransposeOp $arg,
                            (CreateTFLCastToInt32Op (TFL_ConstOp $perm)))>;


def ConvertDotGeneralOp : NativeCodeCall<"ConvertDotGeneralOp($_builder, "

// op. The `ConstOp` will be created at `builder`'s current insertion point.
TF::ConstOp CreateTensorNamesConst(const ArrayRef<std::string> tensor_names,
                                   OpBuilder& builder) {
  const auto loc = NameLoc::get(builder.getStringAttr("tensor_names"));
  return Create1DStringConst(tensor_names, loc, builder);
}

// Creates a 1D string array constant for "shape_and_slices" input of

}

void RegisterBitcastOp() {
  TF_Status* status = TF_NewStatus();

  TF_OpDefinitionBuilder* op_builder = TF_NewOpDefinitionBuilder("Bitcast");
  TF_OpDefinitionBuilderAddInput(op_builder, "input: T");
  TF_OpDefinitionBuilderAddOutput(op_builder, "output: type");
  TF_OpDefinitionBuilderAddAttr(
      op_builder,
      "T: {bfloat16, half, float, double, int64, int32, uint8, uint16, "