code: def __init__(self, net, ignore_index=0, pad_value=0):
      super().__init__()
      self.pad_value = pad_value
      self.ignore_index = ignore_index
  
      self.net = net
      self.max_seq_len = net.max_seq_len
  
file_path: performer-pytorch/performer_pytorch/autoregressive_wrapper.py
imports: from functools import partial
  import torch
  from torch import nn
  import torch.nn.functional
  from torch.nn.utils.rnn import pad_sequence
label_desc: Use image node_id 1 to create a new AutoregressiveWrapper object from inherited base classes: nn with example: obj = AutoregressiveWrapper(net, ignore_index, pad_value)