code: def _net_call(self, x: torch.Tensor) -> torch.Tensor:
      x = torch.unsqueeze(x, 0) if len(x.shape) < 2 else x
      return self.model(torch.Tensor(), x)
  
file_path: lightwood/lightwood/mixer/tabtransformer.py
imports: from typing import Dict, Optional
  import torch
  from tab_transformer_pytorch import TabTransformer
  from lightwood.helpers.device import get_device_from_name
  from lightwood.data.encoded_ds import EncodedDs
  from lightwood.encoder.base import BaseEncoder
  from lightwood.mixer.neural import Neural
label_desc: Use image node_id 3 for calling the TabTransformerMixer obj's underlying member method code with example usage: obj._net_call(x) and returns: self