code: def test_predict_1D_labels(input_type, client):
      # Testing that nothing crashes with 1D labels
  
      X, y = make_classification(n_samples=10000)
      if input_type == "array":
          dX = da.from_array(X)
          dy = da.from_array(y)
      elif input_type == "dataframe":
          X = cudf.DataFrame(X)
          y = cudf.Series(y)
          dX = dd.from_pandas(X, npartitions=1)
          dy = dd.from_pandas(y, npartitions=1)
  
      clf = dKNNClf()
      clf.fit(dX, dy)
      clf.predict(dX)
  
file_path: cuml/python/cuml/tests/dask/test_dask_kneighbors_classifier.py
imports: from cuml.internals.safe_imports import gpu_only_import
  from cuml.internals.safe_imports import cpu_only_import
  import pytest
  from cuml.testing.utils import unit_param, quality_param, stress_param
  from cuml.neighbors import KNeighborsClassifier
  from cuml.dask.neighbors import KNeighborsClassifier
  from sklearn.datasets import make_multilabel_classification
  from sklearn.datasets import make_classification
  from sklearn.model_selection import train_test_split
  import dask.array
  import dask.dataframe
  from cuml.dask.common.dask_arr_utils import to_dask_cudf
  from cuml.internals.safe_imports import gpu_only_import_from
label_desc: Use image node_id 7 for calling a global function with example usage: test_predict_1D_labels(input_type, client) without return types