docstr: Pads the list of tensors in 2 dimensions
docstr_tok: ["Pads","the","list","of","tensors","in","2","dimensions"]
code: def double_pad(list_of_different_shape_tensors):
      r"""
      Pads the list of tensors in 2 dimensions
      """
      second_dim_lens = [
          len(a)
          for a in [i[0] for i in list_of_different_shape_tensors]
      ]
      second_dim_max = max(second_dim_lens)
      padded_x = [
          F.pad(x, (0, second_dim_max - len(x[0])))
          for x in list_of_different_shape_tensors
      ]
      return nn.utils.rnn.pad_sequence(padded_x, batch_first=True)
  
imports: from typing import List, Tuple
  import torch
  import torch.nn.functional
  from torch import nn
  from tqdm.auto import tqdm
  from TTS.tts.layers.tacotron.common_layers import Linear
  from TTS.tts.layers.tacotron.tacotron2 import ConvBNBlock
label_desc: Use image node_id 7 for calling the OverflowUtils obj's underlying member method code with example usage: obj.double_pad(list_of_different_shape_tensors) and returns: nn