code: def test_svc_with_custom_kernel(lil_container):
      def kfunc(x, y):
          return safe_sparse_dot(x, y.T)
  
      X_sp = lil_container(X)
      clf_lin = svm.SVC(kernel="linear").fit(X_sp, Y)
      clf_mylin = svm.SVC(kernel=kfunc).fit(X_sp, Y)
      assert_array_equal(clf_lin.predict(X_sp), clf_mylin.predict(X_sp))
  
imports: import numpy
  import pytest
  from scipy import sparse
  from sklearn import base, datasets, linear_model, svm
  from sklearn.datasets import load_digits, make_blobs, make_classification
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.svm.tests import test_svm
  from sklearn.utils._testing import assert_allclose, assert_array_almost_equal, assert_array_equal, ignore_warnings, skip_if_32bit
  from sklearn.utils.extmath import safe_sparse_dot
  from sklearn.utils.fixes import CSR_CONTAINERS, DOK_CONTAINERS, LIL_CONTAINERS
label_desc: Use image node_id 4 for calling a global function with example usage: test_svc_with_custom_kernel(lil_container) and returns: safe_sparse_dot