code: def stack_pad_tensor(tensor_list):
      max_len = max([t.size(0) for t in tensor_list])
      for i, tensor in enumerate(tensor_list):
          pad_len = max_len - tensor.size(0)
          tensor_list[i] = F.pad(tensor, (0, 0, 0, pad_len))
      return torch.stack(tensor_list, 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 4 for calling a global function with example usage: stack_pad_tensor(tensor_list) and returns: torch