code: def test_sample_weights(lil_container):
      # Test weights on individual samples
      X_sp = lil_container(X)
  
      clf = svm.SVC()
      clf.fit(X_sp, Y)
      assert_array_equal(clf.predict([X[2]]), [1.0])
  
      sample_weight = [0.1] * 3 + [10] * 3
      clf.fit(X_sp, Y, sample_weight=sample_weight)
      assert_array_equal(clf.predict([X[2]]), [2.0])
  
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 11 for calling a global function with example usage: test_sample_weights(lil_container) without return types