code: def test_unknown_chunks_ok(fit_intercept):
      # https://github.com/dask/dask-ml/issues/145
      X = dd.from_pandas(
          pd.DataFrame(np.random.uniform(size=(10, 5))), 2
      ).values
      y = dd.from_pandas(
          pd.Series(np.random.uniform(size=(10,))), 2
      ).values
  
      reg = LinearRegression(fit_intercept=fit_intercept)
      reg.fit(X, y)
  
imports: import dask.array
  import dask.dataframe
  import numpy
  import numpy.linalg
  import pandas
  import pytest
  import sklearn.linear_model
  from dask.dataframe.utils import assert_eq
  from dask_glm.regularizers import Regularizer
  from sklearn.pipeline import make_pipeline
  import dask_ml.linear_model
  from dask_ml.datasets import make_classification, make_counts, make_regression
  from dask_ml.linear_model import LinearRegression, LogisticRegression, PoissonRegression
  from dask_ml.linear_model.utils import add_intercept
  from dask_ml.model_selection import GridSearchCV
label_desc: Use image node_id 13 for calling a global function with example usage: test_unknown_chunks_ok(fit_intercept) without return types