message: Enable int64 input tensors to be populated in tflite benchmark
diff: @@ -326,6 +326,12 @@ void BenchmarkTfLiteModel::PrepareInputData() {
  FillRandomValue<float>(t_data.data.f, num_elements, []() {
  return static_cast<float>(rand()) / RAND_MAX - 0.5f;
  });
  + } else if (t->type == kTfLiteInt64) {
  + t_data.bytes = sizeof(int64_t) * num_elements;
  + t_data.data.raw = new char[t_data.bytes];
  + FillRandomValue<int64_t>(t_data.data.i64, num_elements, []() {
  + return static_cast<int64_t>(rand()) % 100;
  + });
  } else if (t->type == kTfLiteInt32) {
  // TODO(yunluli): This is currently only used for handling embedding input
  // for speech models. Generalize if necessary.
  @@ -374,6 +380,9 @@ void BenchmarkTfLiteModel::ResetInputsAndOutputs() {
  } else if (t->type == kTfLiteInt32) {
  std::memcpy(interpreter_->typed_tensor<int32_t>(i),
  inputs_data_[j].data.i32, inputs_data_[j].bytes);
  + } else if (t->type == kTfLiteInt64) {
  + std::memcpy(interpreter_->typed_tensor<int64_t>(i),
  + inputs_data_[j].data.i64, inputs_data_[j].bytes);
  } else if (t->type == kTfLiteInt16) {
  std::memcpy(interpreter_->typed_tensor<int16_t>(i),
  inputs_data_[j].data.i16, inputs_data_[j].bytes);
  