def before_rnn()

in iep/models/seq2seq.py [0:0]

• 12 lines of code
• 6 McCabe index (conditional complexity)

  def before_rnn(self, x, replace=0):
    # TODO: Use PackedSequence instead of manually plucking out the last
    # non-NULL entry of each sequence; it is cleaner and more efficient.
    N, T = x.size()
    idx = torch.LongTensor(N).fill_(T - 1)

    # Find the last non-null element in each sequence. Is there a clean
    # way to do this?
    x_cpu = x.cpu()
    for i in range(N):
      for t in range(T - 1):
        if x_cpu.data[i, t] != self.NULL and x_cpu.data[i, t + 1] == self.NULL:
          idx[i] = t
          break
    idx = idx.type_as(x.data)
    x[x.data == self.NULL] = replace
    return x, Variable(idx)