code: def __init__(self, net, pad_value=0):
      super().__init__()
      self.seq_len = net.seq_len
      self.pad_value = pad_value
      self.net = net
  
file_path: mixture-of-attention/mixture_of_attention/autoregressive_wrapper.py
imports: import torch
  from torch import nn
  import torch.nn.functional
  from einops import rearrange
label_desc: Use image node_id 1 to create a new AutoregressiveWrapper object from inherited base classes: nn with example: obj = AutoregressiveWrapper(net, pad_value)