code: def subsequent_mask(size: int, device: str = 'cpu') -> torch.Tensor:
      
      mask = torch.tril(torch.ones(size, size, device=device, dtype=torch.int32)).unsqueeze(0)
      return mask
docs: Mask out subsequent positions.