code: def _build_network(self):
      # Backbone
      self._backbone = GatedAdditiveTreesBackbone(
          n_continuous_features=self.hparams.continuous_dim,
          cat_embedding_dims=self.hparams.embedding_dims,
          gflu_stages=self.hparams.gflu_stages,
          gflu_dropout=self.hparams.gflu_dropout,
          num_trees=self.hparams.num_trees,
          tree_depth=self.hparams.tree_depth,
          tree_dropout=self.hparams.tree_dropout,
          binning_activation=self.hparams.binning_activation,
          feature_mask_function=self.hparams.feature_mask_function,
          batch_norm_continuous_input=self.hparams.batch_norm_continuous_input,
          chain_trees=self.hparams.chain_trees,
          tree_wise_attention=self.hparams.tree_wise_attention,
          tree_wise_attention_dropout=self.hparams.tree_wise_attention_dropout,
          gflu_feature_init_sparsity=self.hparams.gflu_feature_init_sparsity,
          tree_feature_init_sparsity=self.hparams.tree_feature_init_sparsity,
          virtual_batch_size=self.hparams.virtual_batch_size,
      )
      # Embedding Layer
      self._embedding_layer = self._backbone._build_embedding_layer()
      # Head
      if self.hparams.num_trees == 0:
          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)
          )
      else:
          self._head = CustomHead(
              self.backbone.output_dim, self.hparams
          )
  
imports: import torch
  import torch.nn
  from omegaconf import DictConfig
  from pytorch_tabular.models.common.heads import blocks
  from pytorch_tabular.models.common.layers import Add, Embedding1dLayer, GatedFeatureLearningUnit, NeuralDecisionTree
  from pytorch_tabular.models.common.layers.activations import entmax15, entmoid15, sparsemax, sparsemoid, t_softmax
  from pytorch_tabular.utils import get_logger
  from ..base_model import BaseModel
label_desc: Use image node_id 5 for calling the GatedAdditiveTreeEnsembleModel obj's underlying member method code with example usage: obj._build_network() without return types