code: def subsequent_mask(size: int, device: torch.device):
      """
      Mask out subsequent positions. Mainly used in the decoding process,
      in which an item should not attend subsequent items.
  
      mask_ijk = 0 if the item should be ignored; 1 if the item should be paid attention
      """
      subsequent_mask = ~torch.triu(
          torch.ones(1, size, size, device=device, dtype=torch.bool),
          diagonal=1,
      )
      return subsequent_mask
  
imports: import copy
  import logging
  import math
  from enum import Enum
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 3 for calling a global function with example usage: subsequent_mask(size, device) and returns: subsequent_mask