code: def test_predict_model_not_training(model, use_gpu):
      predictor = TorchPredictor(model=model, use_gpu=use_gpu)
  
      data_batch = np.array([1])
      predictor.predict(data_batch)
  
      assert not predictor.model.training
  
imports: import re
  import numpy
  import pandas
  import pytest
  import torch
  from ray.air.constants import MAX_REPR_LENGTH
  from ray.air.util.data_batch_conversion import _convert_batch_type_to_pandas, _convert_pandas_to_batch_type
  from ray.train.predictor import TYPE_TO_ENUM
  from ray.train.tests.dummy_preprocessor import DummyPreprocessor
  from ray.train.torch import TorchCheckpoint, TorchPredictor
label_desc: Use image node_id 5 for calling a global function with example usage: test_predict_model_not_training(model, use_gpu) without return types