code: def test_pyfunc_metric():
      X = np.random.random((10, 3))
  
      euclidean = DistanceMetric.get_metric("euclidean")
      pyfunc = DistanceMetric.get_metric("pyfunc", func=dist_func, p=2)
  
      # Check if both callable metric and predefined metric initialized
      # DistanceMetric object is picklable
      euclidean_pkl = pickle.loads(pickle.dumps(euclidean))
      pyfunc_pkl = pickle.loads(pickle.dumps(pyfunc))
  
      D1 = euclidean.pairwise(X)
      D2 = pyfunc.pairwise(X)
  
      D1_pkl = euclidean_pkl.pairwise(X)
      D2_pkl = pyfunc_pkl.pairwise(X)
  
      assert_allclose(D1, D2)
      assert_allclose(D1_pkl, D2_pkl)
  
imports: import copy
  import itertools
  import pickle
  import numpy
  import pytest
  from scipy.spatial.distance import cdist
  from sklearn.metrics import DistanceMetric
  from sklearn.metrics._dist_metrics import BOOL_METRICS, DistanceMetric32, DistanceMetric64
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import assert_allclose, create_memmap_backed_data
  from sklearn.utils.fixes import CSR_CONTAINERS, parse_version, sp_version
label_desc: Use image node_id 10 for calling a global function with example usage: test_pyfunc_metric() without return types