code: def test_regression_metrics_do_not_support_weighted_multioutput(
      metric_pairs,
  ):
      m1, _ = metric_pairs
  
      a = da.random.uniform(size=(100, 3), chunks=(25, 3))
      b = da.random.uniform(size=(100, 3), chunks=(25, 3))
      weights = da.random.uniform(size=(3,))
  
      if m1.__name__ == "r2_score":
          error_msg = "'multioutput' must be 'uniform_average'"
      else:
          error_msg = "Weighted 'multioutput' not supported."
  
      with pytest.raises(
          (NotImplementedError, ValueError), match=error_msg
      ):
          _ = m1(a, b, multioutput=weights)
  
file_path: dask-ml/tests/metrics/test_regression.py
imports: import numbers
  import dask.array
  import numpy
  import pytest
  import sklearn.metrics
  from dask.array.utils import assert_eq
  import dask_ml.metrics
label_desc: Use image node_id 6 for calling a global function with example usage: test_regression_metrics_do_not_support_weighted_multioutput(metric_pairs) without return types