code: def test_column_or_1d():
      EXAMPLES = [
          ("binary", ["spam", "egg", "spam"]),
          ("binary", [0, 1, 0, 1]),
          ("continuous", np.arange(10) / 20.0),
          ("multiclass", [1, 2, 3]),
          ("multiclass", [0, 1, 2, 2, 0]),
          ("multiclass", [[1], [2], [3]]),
          ("multilabel-indicator", [[0, 1, 0], [0, 0, 1]]),
          ("multiclass-multioutput", [[1, 2, 3]]),
          ("multiclass-multioutput", [[1, 1], [2, 2], [3, 1]]),
          ("multiclass-multioutput", [[5, 1], [4, 2], [3, 1]]),
          ("multiclass-multioutput", [[1, 2, 3]]),
          ("continuous-multioutput", np.arange(30).reshape((-1, 3))),
      ]
  
      for y_type, y in EXAMPLES:
          if y_type in ["binary", "multiclass", "continuous"]:
              assert_array_equal(column_or_1d(y), np.ravel(y))
          else:
              with pytest.raises(ValueError):
                  column_or_1d(y)
  
imports: import string
  import timeit
  import warnings
  from copy import copy
  from itertools import chain
  import numpy
  import pytest
  from sklearn import config_context
  from sklearn.utils import _approximate_mode, _determine_key_type, _get_column_indices, _is_polars_df, _message_with_time, _print_elapsed_time, _safe_assign, _safe_indexing, _to_object_array, check_random_state, column_or_1d, deprecated, gen_even_slices, get_chunk_n_rows, is_scalar_nan, resample, safe_mask, shuffle
  from sklearn.utils._mocking import MockDataFrame
  from sklearn.utils._testing import _convert_container, assert_allclose_dense_sparse, assert_array_equal, assert_no_warnings
  from sklearn.utils.fixes import CSC_CONTAINERS, CSR_CONTAINERS
label_desc: Use image node_id 9 for calling a global function with example usage: test_column_or_1d() without return types