code: def inflate_tensor(tensor, scope):
      max_len = max([le for _, le in scope])
      batch_vecs = []
      for st, le in scope:
          cur_vecs = tensor[st : st + le]
          cur_vecs = F.pad(cur_vecs, (0, 0, 0, max_len - le))
          batch_vecs.append(cur_vecs)
  
      return torch.stack(batch_vecs, dim=0)
  
file_path: DIG/dig/ggraph/method/JTVAE/fast_jtnn/nnutils.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Variable
label_desc: Use image node_id 6 for calling a global function with example usage: inflate_tensor(tensor, scope) and returns: torch