code: def subsequent_mask(size, device="cpu", dtype=torch.bool):
      """Create mask for subsequent steps (size, size).
  
      :param int size: size of mask
      :param str device: "cpu" or "cuda" or torch.Tensor.device
      :param torch.dtype dtype: result dtype
      :rtype: torch.Tensor
      >>> subsequent_mask(3)
      [[1, 0, 0],
       [1, 1, 0],
       [1, 1, 1]]
      """
      ret = torch.ones(size, size, device=device, dtype=dtype)
      return torch.tril(ret, out=ret)
  
label_desc: Use image node_id 1 for calling a global function with example usage: subsequent_mask(size, device, dtype) and returns: torch