code: def create_mask(x, N, device=None):
      x = x.data
      mask = np.zeros((x.size(0), N))
      for i in range(x.size(0)):
          mask[i, : x[i]] = 1
      return torch.Tensor(mask).to(device)
  
imports: import random
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from graph4nlp.pytorch.modules.utils.tree_utils import Tree, to_cuda
  from .attention import Attention
  from .base import RNNTreeDecoderBase
label_desc: Use image node_id 1 for calling a global function with example usage: create_mask(x, N, device) and returns: torch