code: def test_pipeline(n_neighbors, radius, global_dtype):
      # check that Isomap works fine as a transformer in a Pipeline
      # only checks that no error is raised.
      # TODO check that it actually does something useful
      X, y = datasets.make_blobs(random_state=0)
      X = X.astype(global_dtype, copy=False)
      clf = pipeline.Pipeline(
          [
              (
                  "isomap",
                  manifold.Isomap(
                      n_neighbors=n_neighbors, radius=radius
                  ),
              ),
              ("clf", neighbors.KNeighborsClassifier()),
          ]
      )
      clf.fit(X, y)
      assert 0.9 < clf.score(X, y)
  
imports: import math
  from itertools import product
  import numpy
  import pytest
  from scipy.sparse import rand
  from sklearn import clone, datasets, manifold, neighbors, pipeline, preprocessing
  from sklearn.datasets import make_blobs
  from sklearn.metrics.pairwise import pairwise_distances
  from sklearn.utils._testing import assert_allclose, assert_allclose_dense_sparse, assert_array_equal
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 5 for calling a global function with example usage: test_pipeline(n_neighbors, radius, global_dtype) without return types