code: def predict(self, dataframe):
      pred_df, _ = self.ludwig_model.predict(dataframe)
      return pred_df
  
imports: import logging
  import os
  import shutil
  import mlflow
  import yaml
  from mlflow import pyfunc
  from mlflow.exceptions import MlflowException
  from mlflow.models import Model
  from mlflow.models.model import MLMODEL_FILE_NAME
  from mlflow.models.signature import ModelSignature
  from mlflow.models.utils import _save_example, ModelInputExample
  from mlflow.tracking._model_registry import DEFAULT_AWAIT_MAX_SLEEP_SECONDS
  from mlflow.tracking.artifact_utils import _download_artifact_from_uri
  from mlflow.utils.environment import _mlflow_conda_env
  from mlflow.utils.model_utils import _get_flavor_configuration
  from ludwig.api_annotations import DeveloperAPI
  from ludwig.globals import MODEL_HYPERPARAMETERS_FILE_NAME
  from ludwig.utils.data_utils import load_json
label_desc: Use image node_id 2 for calling the _LudwigModelWrapper obj's underlying member method code with example usage: obj.predict(dataframe) and returns: pred_df