code: def test_check_training_data_multi_label_sample_weights(self):
      ds_train = random_sklearn_dataset(8, multi_label=True)
      ds_train.y = csr_matrix(
          np.array(
              [
                  [0, 0],
                  [1, 0],
                  [1, 0],
                  [1, 0],
                  [0, 1],
                  [1, 1],
                  [1, 1],
                  [0, 1],
              ]
          )
      )
      weights = np.random.randn(8)
      weights = weights - weights.min() + 1e-8
  
      ds_valid = random_sklearn_dataset(2, multi_label=True)
      # should not raise an error
      check_training_data(ds_train, ds_valid, weights=weights)
  
file_path: small-text/tests/unit/small_text/utils/test_data.py
imports: import unittest
  import numpy
  from scipy.sparse import csr_matrix
  from small_text.base import LABEL_UNLABELED
  from small_text.utils.data import check_training_data, list_length
  from tests.utils.datasets import random_sklearn_dataset
label_desc: Use image node_id 10 for calling the DataUtilsTest obj's underlying member method code with example usage: obj.test_check_training_data_multi_label_sample_weights() without return types