code: def __init__(
      self,
      num_features,
      logdet=False,
      affine=True,
      allow_reverse_init=False,
  ):
      assert affine
      super().__init__()
      self.logdet = logdet
      self.loc = nn.Parameter(torch.zeros(1, num_features, 1, 1))
      self.scale = nn.Parameter(torch.ones(1, num_features, 1, 1))
      self.allow_reverse_init = allow_reverse_init
  
      self.register_buffer(
          "initialized", torch.tensor(0, dtype=torch.uint8)
      )
  
file_path: generative-models/sgm/modules/autoencoding/lpips/util.py
imports: import hashlib
  import os
  import requests
  import torch
  import torch.nn
  from tqdm import tqdm
label_desc: Use image node_id 1 to create a new ActNorm object from inherited base classes: nn with example: obj = ActNorm(num_features, logdet, affine, allow_reverse_init)