Function TimeAdd

tensorflow/core/kernels/quantized_add_op_test.cc:137–183

}

void TimeAdd(const std::vector<int64>& x_shape,
             const std::vector<int64>& y_shape, int64 iterations) {
  TestAddShape(x_shape, y_shape);

  Scope root = Scope::NewRootScope();

  Tensor x_quantized_tensor(DT_QUINT8, TensorShape(x_shape));
  Output placeholder = Placeholder(root.WithOpName("placeholder"), DT_QUINT8);
  Output x_min = Const(root.WithOpName("x_min"), 0.0f);
  Output x_max = Const(root.WithOpName("x_max"), 1.0f);

  Tensor y_quantized_tensor(DT_QUINT8, TensorShape(y_shape));
  Output y =
      Const(root.WithOpName("y"), Input::Initializer(y_quantized_tensor));
  Output y_min = Const(root.WithOpName("y_min"), 0.0f);
  Output y_max = Const(root.WithOpName("y_max"), 1.0f);

  ops::QuantizedAdd add = ops::QuantizedAdd(root.WithOpName("add"), placeholder,
                                            y, x_min, x_max, y_min, y_max);

  TF_EXPECT_OK(root.status());

  ClientSession session(root);
  std::vector<Tensor> outputs;

  int64 total_duration = 0;
  for (int i = 0; i < iterations; ++i) {
    const int64 start_time = Env::Default()->NowMicros();
    TF_EXPECT_OK(session.Run({{placeholder, x_quantized_tensor}},
                             {add.z, add.min_z, add.max_z}, &outputs));
    const int64 end_time = Env::Default()->NowMicros();
    total_duration += end_time - start_time;
  }
  const int64 one_run_duration = total_duration / iterations;

  const int64 num_ops = outputs[0].NumElements();

  const double million_ops_per_second =
      (iterations * num_ops) / static_cast<double>(total_duration);

  LOG(INFO) << "TimeAdd: " << TensorShape(x_shape).DebugString() << " * "
            << TensorShape(y_shape).DebugString()
            << ": iterations=" << iterations
            << ", MOps/s=" << million_ops_per_second
            << ", one_run_duration=" << one_run_duration
            << ", total_duration=" << total_duration;
}

void TestManualScalar() {
  TestAdd(