code: def test_sparse_dot(data, request):
      X, _ = request.getfixturevalue(data)
      K = linear_kernel(X)
      K2 = np.zeros_like(K)
      ds = get_dataset(X)
  
      for i in range(X.shape[0]):
          for j in range(i, X.shape[0]):
              K2[i, j] = sparse_dot(ds, i, j)
              K2[j, i] = K[i, j]
  
      np.testing.assert_array_almost_equal(K, K2)
  
file_path: lightning/lightning/impl/tests/test_dual_cd.py
imports: import numpy
  import pytest
  from sklearn.metrics.pairwise import linear_kernel
  from sklearn.datasets import make_regression
  from lightning.impl.dual_cd import LinearSVC
  from lightning.impl.dual_cd import LinearSVR
  from lightning.impl.dual_cd_fast import sparse_dot
  from lightning.impl.dataset_fast import get_dataset
label_desc: Use image node_id 2 for calling a global function with example usage: test_sparse_dot(data, request) without return types