8da4857396fcedb1abd19a08cd4de40d16c7bc50,research/audioset/yamnet/yamnet_test.py,YAMNetTest,clip_test,#YAMNetTest#,39

Before Change

        np.reshape(waveform, [1, -1]), steps=1)[0], axis=0)
      top_n_class_names = YAMNetTest._yamnet_classes[
        np.argsort(prediction)[-top_n:]]
      self.assertIn(expected_class_name, top_n_class_names)

  def testZeros(self):
    self.clip_test(
        waveform=np.zeros((1, int(3 * params.SAMPLE_RATE))),

After Change

  def clip_test(self, waveform, expected_class_name, top_n=10):
    Run the model on the waveform, check that expected class is in top-n.
    predictions, embeddings, log_mel_spectrogram = YAMNetTest._yamnet(waveform)
    clip_predictions = np.mean(predictions, axis=0)
    top_n_indices = np.argsort(clip_predictions)[-top_n:]
    top_n_scores = clip_predictions[top_n_indices]
    top_n_class_names = YAMNetTest._yamnet_classes[top_n_indices]
    top_n_predictions = list(zip(top_n_class_names, top_n_scores))

Instances