code: def __init__(self, config: DictConfig, **kwargs):
      encoded_cat_dims = 0
      inferred_config = kwargs.get("inferred_config")
      for card, embd_dim in inferred_config.embedding_dims:
          if card == 2:
              encoded_cat_dims += 1
          elif card <= config.max_onehot_cardinality:
              encoded_cat_dims += card
          else:
              encoded_cat_dims += embd_dim
      config.encoder_config._backbone_input_dim = (
          encoded_cat_dims + len(config.continuous_cols)
      )
      assert (
          config.encoder_config._config_name in self.ALLOWED_MODELS
      ), "Encoder must be one of the following: " + ", ".join(
          self.ALLOWED_MODELS
      )
      if config.decoder_config is not None:
          assert (
              config.decoder_config._config_name in self.ALLOWED_MODELS
          ), "Decoder must be one of the following: " + ", ".join(
              self.ALLOWED_MODELS
          )
          if "-" in config.encoder_config.layers:
              config.decoder_config._backbone_input_dim = int(
                  config.encoder_config.layers.split("-")[-1]
              )
          else:
              config.decoder_config._backbone_input_dim = int(
                  config.encoder_config.layers
              )
      super().__init__(config, **kwargs)
  
imports: from collections import namedtuple
  from typing import Dict
  import torch
  import torch.nn
  from omegaconf import DictConfig
  from ..base_model import SSLBaseModel
  from ..common.heads import MultiTaskHead
  from ..common.layers import MixedEmbedding1dLayer
  from ..common.noise_generators import SwapNoiseCorrupter
label_desc: Use image node_id 1 to create a new DenoisingAutoEncoderModel object from inherited base classes: SSLBaseModel with example: obj = DenoisingAutoEncoderModel(config)