title: how multiple underscores in a for loop work
body: <p>I am trying to understand the code from this website:
  <a href="https://www.assemblyai.com/blog/end-to-end-speech-recognition-pytorch" rel="nofollow noreferrer">https://www.assemblyai.com/blog/end-to-end-speech-recognition-pytorch</a></p>
  <pre><code>for (waveform, _, utterance, _, _, _) in data:
  </code></pre>
  <p>Can someone please explain,what is the meaning of the above line and how it works ?<br />
  Like are we ignoring some values while unpacking the data or something else.</p>
  <p>Complete code for the function:</p>
  <pre><code>def data_processing(data, data_type=&quot;train&quot;):
      spectrograms = []
      labels = []
      input_lengths = []
      label_lengths = []
      for (waveform, _, utterance, _, _, _) in data:
          if data_type == 'train':
              spec = train_audio_transforms(waveform).squeeze(0).transpose(0, 1)
          elif data_type == 'valid':
              spec = valid_audio_transforms(waveform).squeeze(0).transpose(0, 1)
          else:
              raise Exception('data_type should be train or valid')
          spectrograms.append(spec)
          label = torch.Tensor(text_transform.text_to_int(utterance.lower()))
          labels.append(label)
          input_lengths.append(spec.shape[0]//2)
          label_lengths.append(len(label))
  
      spectrograms = nn.utils.rnn.pad_sequence(spectrograms, batch_first=True).unsqueeze(1).transpose(2, 3)
      labels = nn.utils.rnn.pad_sequence(labels, batch_first=True)
  
      return spectrograms, labels, input_lengths, label_lengths
  </code></pre>