code: def test_fit(self, perform_model_selection_mock, fake_train):
      model_args = TransformerModelArguments(
          "sshleifer/tiny-distilroberta-base"
      )
      clf = TransformerBasedClassification(
          model_args, 4, multi_label=self.multi_label, num_epochs=1
      )
  
      train_set = self._get_dataset(num_samples=20)
      clf.fit(train_set)
  
      # basically tests _get_layer_params for now
  
      fake_train.assert_called()
      perform_model_selection_mock.assert_called()
  
imports: import unittest
  import pytest
  import warnings
  import numpy
  from unittest import mock
  from unittest.mock import patch, Mock
  from parameterized import parameterized_class
  from scipy.sparse import issparse
  from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
  from small_text.training.early_stopping import EarlyStopping, NoopEarlyStopping
  from small_text.training.metrics import Metric
  from small_text.training.model_selection import ModelSelection, NoopModelSelection
  from tests.utils.datasets import twenty_news_transformers
  from tests.utils.testing import assert_array_not_equal
label_desc: Use image node_id 2 for calling the _TransformerBasedClassificationTest obj's underlying member method code with example usage: obj.test_fit(perform_model_selection_mock, fake_train) without return types