code: def _build_network(self):
      # Backbone
      self._backbone = GANDALFBackbone(
          cat_embedding_dims=self.hparams.embedding_dims,
          n_continuous_features=self.hparams.continuous_dim,
          gflu_stages=self.hparams.gflu_stages,
          gflu_dropout=self.hparams.gflu_dropout,
          gflu_feature_init_sparsity=self.hparams.gflu_feature_init_sparsity,
          learnable_sparsity=self.hparams.learnable_sparsity,
          batch_norm_continuous_input=self.hparams.batch_norm_continuous_input,
          embedding_dropout=self.hparams.embedding_dropout,
          virtual_batch_size=self.hparams.virtual_batch_size,
      )
      # Embedding Layer
      self._embedding_layer = self._backbone._build_embedding_layer()
      # Head
      self.T0 = nn.Parameter(
          torch.rand(self.hparams.output_dim), requires_grad=True
      )
      self._head = nn.Sequential(
          self._get_head_from_config(), Add(self.T0)
      )
  
imports: import torch
  import torch.nn
  from omegaconf import DictConfig
  from pytorch_tabular.models.common.layers import Add, Embedding1dLayer, GatedFeatureLearningUnit
  from pytorch_tabular.models.common.layers.activations import t_softmax
  from pytorch_tabular.utils import get_logger
  from ..base_model import BaseModel
label_desc: Use image node_id 5 for calling the GANDALFModel obj's underlying member method code with example usage: obj._build_network() without return types