code: def test_consistent_proba():
      a = svm.SVC(probability=True, max_iter=1, random_state=0)
      with ignore_warnings(category=ConvergenceWarning):
          proba_1 = a.fit(X, Y).predict_proba(X)
      a = svm.SVC(probability=True, max_iter=1, random_state=0)
      with ignore_warnings(category=ConvergenceWarning):
          proba_2 = a.fit(X, Y).predict_proba(X)
      assert_allclose(proba_1, proba_2)
  
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 17 for calling a global function with example usage: test_consistent_proba() without return types