code: def test_unique_labels_non_specific(setup):
      # Test unique_labels with a variety of collected examples
  
      # Smoke test for all supported format
      for format in ["binary", "multiclass", "multilabel-indicator"]:
          for y in EXAMPLES[format]:
              unique_labels(y).execute()
  
      # We don't support those format at the moment
      for example in NON_ARRAY_LIKE_EXAMPLES:
          with pytest.raises(ValueError):
              unique_labels(example).execute()
  
      for y_type in [
          "unknown",
          "continuous",
          "continuous-multioutput",
          "multiclass-multioutput",
      ]:
          for example in EXAMPLES[y_type]:
              with pytest.raises(ValueError):
                  unique_labels(example).execute()
  
file_path: mars/mars/learn/utils/tests/test_multiclass.py
imports: from itertools import product
  import numpy
  import pytest
  import scipy.sparse
  from scipy.sparse import csr_matrix
  from sklearn.utils._testing import assert_array_equal
  from sklearn.utils.estimator_checks import _NotAnArray
  from sklearn.utils.multiclass import is_multilabel, type_of_target
  from ....None import tensor
  from ..multiclass import is_multilabel, unique_labels, type_of_target
label_desc: Use image node_id 2 for calling a global function with example usage: test_unique_labels_non_specific(setup) without return types