message: Fixes a comment in tf.contrib.seq2seq.monotonic_attention().
diff: @@ -654,7 +654,7 @@ def monotonic_attention(p_choose_i, previous_attention, mode):
  shifted_1mp_choose_i = array_ops.concat(
  [array_ops.ones((batch_size, 1)), 1 - p_choose_i[:, :-1]], 1)
  # Compute attention distribution recursively as
  - # q[i] = (1 - p_choose_i[i])*q[i - 1] + previous_attention[i]
  + # q[i] = (1 - p_choose_i[i - 1])*q[i - 1] + previous_attention[i]
  # attention[i] = p_choose_i[i]*q[i]
  attention = p_choose_i*array_ops.transpose(functional_ops.scan(
  # Need to use reshape to remind TF of the shape between loop iterations
  