code: def _build_network(self):
      self._featurizer = DenoisingAutoEncoderFeaturizer(
          self.encoder, self.hparams
      )
      self._embedding = self._featurizer._build_embedding_layer()
      self.reconstruction = MultiTaskHead(
          self.decoder.output_dim,
          n_binary=len(self._embedding._binary_feat_idx),
          n_categorical=len(self._embedding._onehot_feat_idx),
          n_numerical=self._embedding.embedded_cat_dim
          + len(self.hparams.continuous_cols),
          cardinality=[
              self._embedding.categorical_embedding_dims[i][0]
              for i in self._embedding._onehot_feat_idx
          ],
      )
      self.mask_reconstruction = nn.Linear(
          self.decoder.output_dim,
          len(self._featurizer.swap_noise.probas),
      )
  
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 5 for calling the DenoisingAutoEncoderModel obj's underlying member method code with example usage: obj._build_network() without return types