Function Expect

tensorflow/core/kernels/quantized_instance_norm_test.cc:83–122

}

void Expect(const Tensor& input, float x_min, float x_max,
            bool output_range_given, float give_y_min, float given_y_max) {
  Scope root = Scope::NewRootScope();

  auto input_ph = Placeholder(root, DT_QUINT8);

  const float variance_eps = 1e-5;
  auto instance_norm = QuantizedInstanceNorm(
      root, input_ph, x_min, x_max,
      QuantizedInstanceNorm::Attrs().VarianceEpsilon(variance_eps));

  Status s = root.status();
  EXPECT_TRUE(s.ok());

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

  s = session.Run({{input_ph, input}},
                  {instance_norm.y, instance_norm.y_min, instance_norm.y_max},
                  &outputs);

  EXPECT_TRUE(s.ok());
  Tensor expected(DT_FLOAT, input.shape());

  ReferenceImpl(input.flat<quint8>().data(), x_min, x_max, input.shape(),
                variance_eps, expected.flat<float>().data());

  auto out = outputs[0].flat<quint8>();

  float out_min = outputs[1].flat<float>()(0);
  float out_max = outputs[2].flat<float>()(0);
  float out_scale = (out_max - out_min) / 255.0f;

  Eigen::Tensor<float, 0, Eigen::RowMajor> max_diff =
      (expected.flat<float>() - (out_min + out_scale * out.cast<float>()))
          .abs()
          .maximum();
  EXPECT_LE(max_diff(), 0.1);
  LOG(INFO) << "max diff " << max_diff();
}

void TestBasic() {
  Tensor input_tensor(DT_QUINT8, {1, 4, 4, 32});