code: def load(cls, path: str, reset_paths=True, verbose=True):
      model = super().load(
          path=path, reset_paths=reset_paths, verbose=verbose
      )
      if model._load_model:
          try_import_autogluon_multimodal()
          from autogluon.multimodal import MultiModalPredictor
  
          model.model = MultiModalPredictor.load(
              os.path.join(path, cls._NN_MODEL_NAME)
          )
      model._load_model = None
      return model
  
imports: import logging
  import os
  from typing import Dict, Optional
  import pandas
  from autogluon.common.features.types import R_CATEGORY, R_FLOAT, R_INT, R_OBJECT, S_IMAGE_PATH, S_TEXT, S_TEXT_AS_CATEGORY, S_TEXT_NGRAM, S_TEXT_SPECIAL
  from autogluon.common.utils.resource_utils import ResourceManager
  from autogluon.common.utils.try_import import try_import_autogluon_multimodal
  from autogluon.core.constants import BINARY, MULTICLASS, REGRESSION
  from autogluon.core.models import AbstractModel
label_desc: Use image node_id 10 for calling the MultiModalPredictorModel obj's underlying member method code with example usage: obj.load(cls, path, reset_paths, verbose) and returns: model