code: def exact_match(l_outputs, d_outputs):
      # Check shapes
      assert l_outputs.shape == d_outputs.shape
  
      # Predictions should match
      correct_queries = (l_outputs == d_outputs).all(axis=1)
      assert np.mean(correct_queries) > 0.95
  
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 3 for calling a global function with example usage: exact_match(l_outputs, d_outputs) without return types