code: def _fit(self, X, num_gpus="auto", **kwargs):
      if not isinstance(num_gpus, str):
          if num_gpus == 0:
              logger.log(
                  30,
                  f"WARNING: Training {self.name} on CPU (no GPU specified). This could take a long time. Use GPU to speed up training.",
              )
      super()._fit(X, num_gpus=num_gpus, **kwargs)
  
file_path: autogluon/tabular/src/autogluon/tabular/models/automm/ft_transformer.py
imports: import logging
  from typing import Dict
  from autogluon.common.features.types import R_CATEGORY, R_FLOAT, R_INT, S_TEXT_NGRAM, S_TEXT_SPECIAL
  from .automm_model import MultiModalPredictorModel
label_desc: Use image node_id 2 for calling the FTTransformerModel obj's underlying member method code with example usage: obj._fit(X, num_gpus) without return types