Function TEST

tensorflow/lite/kernels/basic_rnn_test.cc:258–283

};

TEST(RnnOpTest, BlackBoxTest) {
  RNNOpModel rnn(2, 16, 8);
  rnn.SetWeights(rnn_weights);
  rnn.SetBias(rnn_bias);
  rnn.SetRecurrentWeights(rnn_recurrent_weights);

  const int input_sequence_size = sizeof(rnn_input) / sizeof(float) /
                                  (rnn.input_size() * rnn.num_batches());

  for (int i = 0; i < input_sequence_size; i++) {
    float* batch_start = rnn_input + i * rnn.input_size();
    float* batch_end = batch_start + rnn.input_size();
    rnn.SetInput(0, batch_start, batch_end);
    rnn.SetInput(rnn.input_size(), batch_start, batch_end);

    rnn.Invoke();

    float* golden_start = rnn_golden_output + i * rnn.num_units();
    float* golden_end = golden_start + rnn.num_units();
    std::vector<float> expected;
    expected.insert(expected.end(), golden_start, golden_end);
    expected.insert(expected.end(), golden_start, golden_end);

    EXPECT_THAT(rnn.GetOutput(), ElementsAreArray(ArrayFloatNear(expected)));
  }
}

TEST(HybridRnnOpTest, BlackBoxTestUint8) {
  HybridRNNOpModel rnn(2, 16, 8, TensorType_UINT8);