// Metadata key/value pairs to write to the flatbuffer.
  std::map<std::string, std::string> metadata;
  // OpOrArgNameMapper to convert location of the op to name in flatbuffer.
  // If not set, a default mapper will be used.
  tensorflow::OpOrArgNameMapper* op_or_arg_name_mapper = nullptr;
  // User-specified value of flatbuffer alignment requirement for custom

              << "Converts TensorFlowLite flatbuffer to textual output format. "
              << "One positional input argument representing the source of the "
              << "flatbuffer is supported.\n";
    return 1;
  }

  std::string serialized_model;
  if (tflite::ReadAndVerify(argv[1], &serialized_model)) return 1;
#if FLATBUFFERS_LITTLEENDIAN == 0
  // If the flatbuffer model comes from stdin, convert its tensor content from

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s

// Tests input and output names from FlatBuffer are added to `tf.entry_function` attribute.

// CHECK-LABEL: @main
func.func @main(%arg0: tensor<4xi8>, %arg1: tensor<4xi32>) -> (tensor<4xi32>, tensor<4xi8>)
// CHECK: attributes {tf.entry_function = {inputs = "input0,input1", outputs = "output0,output1"}}

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s
// Confirm float constants and operators survive a roundtrip

func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
  // CHECK:      [[CONST:%.*]] = "tfl.pseudo_const"() <{value = dense<1.000000e+00> : tensor<4xf32>}> : () -> tensor<4xf32>

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate -input-arrays=squared_difference --experimental-prune-unreachable-nodes-unconditionally --tflite-flatbuffer-to-mlir - -o -
// TODO(b/329300758): re-enable filecheck | FileCheck %s
// Tests -input-arrays flag.

func.func @main(%arg0: tensor<4xf32>) -> tensor<4xf32> {
  %0 = "tfl.pseudo_const" () {value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")

// RUN: tf-opt --tfl-legalize-tf-while %s -o - | flatbuffer_translate -mlir-to-tflite-flatbuffer - -o -  | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s

// CHECK-LABEL: main
func.func @main(%arg0: tensor<*xf32>) -> tensor<*xf32> {
  // CHECK:     %{{.*}} = tfl.add %{{.*}}, %{{.*}} {fused_activation_function = "NONE"} : tensor<*xf32>
  // CHECK:     return %{{.*}} : tensor<*xf32>

#include "tensorflow/compiler/mlir/op_or_arg_name_mapper.h"

namespace tflite {

// Translates the given MLIR `module` into a FlatBuffer and stores the
// serialized flatbuffer into the string. This uses OpOrArgLocNameMapper to
// convert location of the op to name in flatbuffer. Returns true if translation
// fails, otherwise returns false.
bool MlirToFlatBufferTranslateFunction(mlir::ModuleOp module,

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s

func.func @main(%arg0: tensor<32x4x4x128xf32>, %arg1: tensor<1x32x42x128xf32>, %arg2: tensor<4xi32>) -> tensor<1x64x84x32xf32> {

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate -tflite-flatbuffer-to-mlir - -o - | FileCheck --check-prefix=IMPORT %s

func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
// CHECK: {
// CHECK-NEXT:   version: 3,
// CHECK-NEXT:     operator_codes: [ {
// CHECK-NEXT:       deprecated_builtin_code: 80,

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s

func.func @main(%arg0 : tensor<!tf_type.variant<tensor<2xi32>>>, %arg1: tensor<!tf_type.variant<tensor<*xi32>>>) -> tensor<!tf_type.variant<tensor<2xi32>>> {
  func.return %arg0 : tensor<!tf_type.variant<tensor<2xi32>>>
}