code: def _get_dataset(self, num_samples=100, num_classes=4):
      return random_text_classification_dataset(
          num_samples,
          max_length=60,
          num_classes=num_classes,
          multi_label=self.multi_label,
      )
  
imports: import unittest
  import pytest
  import numpy
  from unittest.mock import patch
  from unittest import mock
  from unittest.mock import Mock
  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
label_desc: Use image node_id 1 for calling the _KimCNNClassifierTest obj's underlying member method code with example usage: obj._get_dataset(num_samples, num_classes) and returns: random_text_classification_dataset