code: def test_pickle(writable_kwargs, metric_param_grid, X):
      metric, param_grid = metric_param_grid
      keys = param_grid.keys()
      for vals in itertools.product(*param_grid.values()):
          if any(isinstance(val, np.ndarray) for val in vals):
              vals = copy.deepcopy(vals)
              for val in vals:
                  if isinstance(val, np.ndarray):
                      val.setflags(write=writable_kwargs)
          kwargs = dict(zip(keys, vals))
          dm = DistanceMetric.get_metric(metric, X.dtype, **kwargs)
          D1 = dm.pairwise(X)
          dm2 = pickle.loads(pickle.dumps(dm))
          D2 = dm2.pairwise(X)
          assert_allclose(D1, D2)
  
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 7 for calling a global function with example usage: test_pickle(writable_kwargs, metric_param_grid, X) without return types