code: def forward(self, x: Dict):
      if isinstance(self.backbone, TabTransformerBackbone):
          if self.hparams.categorical_dim > 0:
              x_cat = self.embed_input(
                  {"categorical": x["categorical"]}
              )
          x = self.compute_backbone(
              {"categorical": x_cat, "continuous": x["continuous"]}
          )
      else:
          x = self.embedding_layer(x)
          x = self.compute_backbone(x)
      return self.compute_head(x)
  
imports: from typing import Dict, Optional, Union
  import torch
  import torch.nn
  from omegaconf import DictConfig, OmegaConf
  from torch import Tensor
  from pytorch_tabular import models
  from pytorch_tabular.config.config import ModelConfig
  from pytorch_tabular.models.common.heads import blocks
  from pytorch_tabular.models.tab_transformer.tab_transformer import TabTransformerBackbone
  from pytorch_tabular.tabular_model import getattr_nested
  from pytorch_tabular.utils import get_logger
  from ..base_model import BaseModel, safe_merge_config
label_desc: Use image node_id 7 for calling the MDNModel obj's underlying member method code with example usage: obj.forward(x) and returns: self