code: def test_predict_proba_dropout(self):
      class PytorchClassifierImpl(PytorchClassifier):
          def __init__(self):
              self.model = None
              self._create_collate_fn = None
              super().__init__()
  
          def fit(self, train_set, _=None, *args, **kwargs):
              self.model = Mock()
  
              def create_collate_fn():
                  def collate(dataset):
                      return torch.arange(0, len(dataset))
  
                  return collate
  
              self._create_collate_fn = create_collate_fn
  
      clf = PytorchClassifierImpl()
      ds = random_text_classification_dataset()
  
      clf.fit(ds)
  
      with self.assertRaisesRegex(
          NotImplementedError,
          r"_predict_proba_dropout_sampling\(\) needs to be implemented",
      ):
          clf.predict_proba(ds, dropout_sampling=3)
  
imports: import pytest
  import unittest
  from unittest.mock import Mock, patch
  from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
  from small_text.training.model_selection import ModelSelection, NoopModelSelection
  from tests.utils.datasets import random_text_classification_dataset
label_desc: Use image node_id 2 for calling the PytorchClassifierTest obj's underlying member method code with example usage: obj.test_predict_proba_dropout() and returns: collate, torch