code: def test_pairwise_distances_argmin_min(X_blobs):
      centers = X_blobs[::100].compute()
  
      # X_blobs has 500 rows per block.
      # Ensure 500 rows in the scikit-learn version too.
      working_memory = float(80 * 500) / 2**20
  
      ctx = sklearn.config_context(working_memory=working_memory)
  
      with ctx:
          a_, b_ = sklearn.metrics.pairwise_distances_argmin_min(
              X_blobs.compute(), centers
          )
          a, b = dask_ml.metrics.pairwise_distances_argmin_min(
              X_blobs, centers
          )
          a, b = dask.compute(a, b)
  
      npt.assert_array_equal(a, a_)
      npt.assert_array_equal(b, b_)
  
file_path: dask-ml/tests/metrics/test_metrics.py
imports: import dask
  import dask.array
  import numpy
  import numpy.testing
  import pytest
  import sklearn
  import sklearn.linear_model
  import sklearn.metrics
  from dask.array.utils import assert_eq
  import dask_ml.metrics
  import dask_ml.wrappers
label_desc: Use image node_id 2 for calling a global function with example usage: test_pairwise_distances_argmin_min(X_blobs) without return types