code: def verify_predictor_save_load_for_semantic_seg(
      predictor, df, as_multiclass, cls=MultiModalPredictor
  ):
      root = str(uuid.uuid4())
      os.makedirs(root, exist_ok=True)
      predictor.save(root)
      predictions = predictor.predict(df, as_pandas=False)
      # Test fit_summary()
      predictor.fit_summary()
  
      loaded_predictor = cls.load(root)
      # Test fit_summary()
      loaded_predictor.fit_summary()
  
      predictions2 = loaded_predictor.predict(df, as_pandas=False)
      for prediction, prediction2 in zip(predictions, predictions2):
          npt.assert_equal(prediction, prediction2)
  
      predictions_prob = predictor.predict_proba(
          df, as_pandas=False, as_multiclass=as_multiclass
      )
      predictions2_prob = loaded_predictor.predict_proba(
          df, as_pandas=False, as_multiclass=as_multiclass
      )
      for prediction_prob, prediction2_prob in zip(
          predictions_prob, predictions2_prob
      ):
          npt.assert_equal(prediction_prob, prediction2_prob)
  
      shutil.rmtree(root)
  
imports: import os
  import shutil
  import uuid
  import numpy
  import numpy.testing
  import pandas
  import pytest
  import torch
  from autogluon.core.utils.loaders import load_zip
  from autogluon.multimodal import MultiModalPredictor
label_desc: Use image node_id 10 for calling a global function with example usage: verify_predictor_save_load_for_semantic_seg(predictor, df, as_multiclass, cls) without return types