Function Prepare

tensorflow/lite/kernels/pow.cc:48–78

}

TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
  TF_LITE_ENSURE_EQ(context, NumInputs(node), 2);
  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);

  OpData* data = reinterpret_cast<OpData*>(node->user_data);

  const TfLiteTensor* input1 = GetInput(context, node, kInputTensor1);
  const TfLiteTensor* input2 = GetInput(context, node, kInputTensor2);
  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);

  TF_LITE_ENSURE_EQ(context, input1->type, input2->type);

  const TfLiteType type = input1->type;
  if (type != kTfLiteInt32 && type != kTfLiteFloat32) {
    context->ReportError(context, "Unsupported data type %d.", type);
    return kTfLiteError;
  }
  output->type = type;

  data->requires_broadcast = !HaveSameShapes(input1, input2);

  TfLiteIntArray* output_size = nullptr;
  if (data->requires_broadcast) {
    TF_LITE_ENSURE_OK(context, CalculateShapeForBroadcast(
                                   context, input1, input2, &output_size));
  } else {
    output_size = TfLiteIntArrayCopy(input1->dims);
  }

  return context->ResizeTensor(context, output, output_size);
}

template <typename T>
void PowImpl(const TfLiteTensor* input1, const TfLiteTensor* input2,