code: def test_regression_metrics_raw_values(metric_pairs, compute):
      m1, m2 = metric_pairs
  
      if m1.__name__ == "r2_score":
          pytest.skip(
              "r2_score does not support multioutput='raw_values'"
          )
  
      a = da.random.uniform(size=(100, 3), chunks=(25, 3))
      b = da.random.uniform(size=(100, 3), chunks=(25, 3))
  
      result = m1(a, b, multioutput="raw_values", compute=compute)
      expected = m2(a, b, multioutput="raw_values")
  
      if compute:
          assert isinstance(result, np.ndarray)
      else:
          assert isinstance(result, da.Array)
  
      assert_eq(result, expected)
      assert result.shape == (3,)
  
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 5 for calling a global function with example usage: test_regression_metrics_raw_values(metric_pairs, compute) without return types