code: def __init__(self, **kwargs):
      if "lossconfig" in kwargs:
          kwargs["loss_config"] = kwargs.pop("lossconfig")
      super().__init__(
          regularizer_config={
              "target": (
                  "sgm.modules.autoencoding.regularizers"
                  ".DiagonalGaussianRegularizer"
              )
          },
          **kwargs,
      )
  
imports: import logging
  import math
  import re
  from abc import abstractmethod
  from contextlib import contextmanager
  from typing import Any, Dict, List, Optional, Tuple, Union
  import pytorch_lightning
  import torch
  import torch.nn
  from einops import rearrange
  from packaging import version
  from ..modules.autoencoding.regularizers import AbstractRegularizer
  from ..modules.ema import LitEma
  from ..util import default, get_nested_attribute, get_obj_from_str, instantiate_from_config
label_desc: Use image node_id 1 to create a new AutoencoderKL object from inherited base classes: AutoencodingEngineLegacy with example: obj = AutoencoderKL()