code: def subsequent_mask(seq_len):
      """
      ## Subsequent mask to mask out data from future (subsequent) time steps
      """
      mask = (
          torch.tril(torch.ones(seq_len, seq_len))
          .to(torch.bool)
          .unsqueeze(-1)
      )
      return mask
  
label_desc: Use image node_id 1 for calling a global function with example usage: subsequent_mask(seq_len) and returns: mask