code: def test_make_regression():
      X, y = dask_ml.datasets.make_regression(
          n_samples=150, n_features=75, chunks=(50, 75), random_state=0
      )
      assert isinstance(X, da.Array)
      assert X.shape == (150, 75)
      assert X.compute().shape == X.shape
  
      assert isinstance(y, da.Array)
      assert y.shape == (150,)
      assert y.compute().shape == y.shape
  
      X, y, coef = dask_ml.datasets.make_regression(
          n_samples=150,
          n_features=75,
          chunks=(50, 75),
          random_state=0,
          coef=True,
          bias=1.0,
          noise=2.0,
      )
      assert isinstance(coef, np.ndarray)
  
      e = y - X.dot(coef)
      mean, std = dask.compute(e.mean(0), e.std(0))
  
      assert abs(mean - 1.0) <= 0.1
      assert abs(std - 2.0) <= 0.1
  
file_path: dask-ml/tests/test_datasets.py
imports: from datetime import date
  import dask
  import dask.array
  import numpy
  import pytest
  from dask.array.utils import assert_eq
  import dask_ml.datasets
label_desc: Use image node_id 2 for calling a global function with example usage: test_make_regression() without return types