code: def test_init_parameters(self):
      num_classes = 2
      multi_label = True
      device = "cpu"
      num_epochs = 5
      mini_batch_size = 30
      max_seq_len = 100
      out_channels = 80
      filter_padding = 0
      dropout = 0.4
      validation_set_size = 0.15
      embedding_matrix = np.random.rand(5, 10)
      padding_idx = 1
      early_stopping = 10
      early_stopping_acc = 0.95
  
      classifier = KimCNNClassifier(
          num_classes,
          multi_label=multi_label,
          device="cpu",
          num_epochs=num_epochs,
          mini_batch_size=mini_batch_size,
          max_seq_len=max_seq_len,
          out_channels=out_channels,
          filter_padding=filter_padding,
          dropout=dropout,
          validation_set_size=validation_set_size,
          embedding_matrix=embedding_matrix,
          padding_idx=padding_idx,
          early_stopping=early_stopping,
          early_stopping_acc=early_stopping_acc,
      )
  
      self.assertEqual(num_classes, classifier.num_classes)
      self.assertEqual(multi_label, classifier.multi_label)
      self.assertEqual(device, classifier.device)
      self.assertEqual(num_epochs, classifier.num_epochs)
      self.assertEqual(mini_batch_size, classifier.mini_batch_size)
      self.assertIsNone(classifier.criterion)
      self.assertIsNone(classifier.optimizer)
      self.assertIsNone(classifier.scheduler)
      self.assertEqual(max_seq_len, classifier.max_seq_len)
      self.assertEqual(out_channels, classifier.out_channels)
      self.assertEqual(filter_padding, classifier.filter_padding)
      self.assertEqual(dropout, classifier.dropout)
      self.assertEqual(
          validation_set_size, classifier.validation_set_size
      )
      np.testing.assert_equal(
          embedding_matrix, classifier.embedding_matrix
      )
      self.assertEqual(padding_idx, classifier.padding_idx)
      self.assertEqual(early_stopping, classifier.early_stopping)
      self.assertEqual(
          early_stopping_acc, classifier.early_stopping_acc
      )
      self.assertIsNone(classifier.model)
  
imports: import unittest
  import pytest
  import numpy
  from unittest.mock import patch
  from small_text.base import LABEL_UNLABELED
  from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
  from small_text.training.metrics import Metric
  from small_text.training.early_stopping import EarlyStopping, EarlyStoppingOrCondition
label_desc: Use image node_id 3 for calling the KimCNNTest obj's underlying member method code with example usage: obj.test_init_parameters() without return types