code: def get_batch(self, batch):
      # sent in batch in decreasing order of lengths
      # batch: (bsize, max_len, word_dim)
      embed = np.zeros((len(batch[0]), len(batch), self.word_emb_dim))
  
      for i in range(len(batch)):
          for j in range(len(batch[i])):
              embed[j, i, :] = self.word_vec[batch[i][j]]
  
      return torch.FloatTensor(embed)
  
imports: import time
  import numpy
  import torch
  from torch import nn
  import textattack
label_desc: Use image node_id 11 for calling the InferSentModel obj's underlying member method code with example usage: obj.get_batch(batch) and returns: torch