code: def test_random_state(self):
      seed = None
      dataset_1 = ActiveLearningDataset(MyDataset(), random_state=seed)
      dataset_1.label_randomly(10)
      dataset_2 = ActiveLearningDataset(MyDataset(), random_state=seed)
      dataset_2.label_randomly(10)
      assert not np.allclose(dataset_1.labelled, dataset_2.labelled)
  
      seed = 50
      dataset_1 = ActiveLearningDataset(MyDataset(), random_state=seed)
      dataset_1.label_randomly(10)
      dataset_2 = ActiveLearningDataset(MyDataset(), random_state=seed)
      dataset_2.label_randomly(10)
      assert np.allclose(dataset_1.labelled, dataset_2.labelled)
  
      seed = np.random.RandomState(50)
      dataset_1 = ActiveLearningDataset(MyDataset(), random_state=seed)
      dataset_1.label_randomly(10)
      dataset_2 = ActiveLearningDataset(MyDataset(), random_state=seed)
      dataset_2.label_randomly(10)
      assert not np.allclose(dataset_1.labelled, dataset_2.labelled)
  
imports: import pickle
  import unittest
  import unittest.mock
  import warnings
  import datasets
  import numpy
  import pytest
  import torch.utils.data
  from torchvision.transforms import Lambda
  from baal.active import ActiveLearningDataset
label_desc: Use image node_id 10 for calling the ActiveDatasetTest obj's underlying member method code with example usage: obj.test_random_state() without return types