code: def test_fit_and_validate(self):
      ds = self._get_dataset()
  
      num_classes = 4
  
      embedding_matrix = torch.FloatTensor(np.random.rand(10, 100))
      clf = KimCNNClassifier(
          num_classes,
          multi_label=self.multi_label,
          embedding_matrix=embedding_matrix,
      )
      clf.fit(ds)
  
      with mock.patch.object(
          clf.model, "eval", wraps=clf.model.eval
      ) as model_eval_spy, mock.patch.object(
          clf.model, "train", wraps=clf.model.train
      ) as model_train_spy:
          loss, acc = clf.validate(ds)
          self.assertTrue(loss >= 0)
          self.assertTrue(0 <= acc <= 1)
  
          model_eval_spy.assert_called()
          model_train_spy.assert_called_once_with(False)
  
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 6 for calling the _KimCNNClassifierTest obj's underlying member method code with example usage: obj.test_fit_and_validate() without return types