code: def test_masked_column_median(failure_logger, mask_dataset):
      mask_value, X_np, X = mask_dataset
      median = _masked_column_median(X, mask_value).get()
      mask = ~sk_get_mask(X_np, value_to_mask=mask_value)
      n_columns = X.shape[1]
      for i in range(n_columns):
          column_mask = mask[:, i]
          column_median = np.median(X_np[:, i][column_mask])
          assert column_median == median[i]
  
imports: import platform
  from sklearn.preprocessing import normalize
  from cuml.testing.test_preproc_utils import assert_allclose
  from cuml.thirdparty_adapters.sparsefuncs_fast import csr_mean_variance_axis0, csc_mean_variance_axis0, _csc_mean_variance_axis0, inplace_csr_row_normalize_l1, inplace_csr_row_normalize_l2
  from sklearn.utils._mask import _get_mask
  from cuml.thirdparty_adapters.adapters import check_array, _get_mask, _masked_column_median, _masked_column_mean, _masked_column_mode
  from cuml.internals.safe_imports import cpu_only_import_from
  from cuml.internals.safe_imports import gpu_only_import_from
  from cuml.internals.safe_imports import cpu_only_import
  import pytest
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 10 for calling a global function with example usage: test_masked_column_median(failure_logger, mask_dataset) without return types