code: def forward(self, frames: pd.DataFrame) -> pd.DataFrame:
      predictions, _ = self.model.predict(
          frames, return_type=pd.DataFrame
      )
      # Ludwig may return a Dask DataFrame when dask is installed
      try:
          import dask
  
          if isinstance(predictions, dask.dataframe.core.DataFrame):
              predictions = predictions.compute()
      except ImportError:
          pass
      return predictions
  
file_path: evadb/evadb/functions/ludwig.py
imports: import pandas
  from evadb.functions.abstract.abstract_function import AbstractFunction
  from evadb.utils.generic_utils import try_to_import_ludwig
label_desc: Use image node_id 3 for calling the GenericLudwigModel obj's underlying member method code with example usage: obj.forward(frames) and returns: predictions