code: def test_convergence_warning(Estimator, solver):
      convergence_warning = "Maximum number of iterations 1 reached. Increase it to improve convergence."
      A = np.ones((2, 2))
      with pytest.warns(ConvergenceWarning, match=convergence_warning):
          Estimator(max_iter=1, **solver).fit(A)
  
imports: import re
  import sys
  import warnings
  from io import StringIO
  import numpy
  import pytest
  from scipy import linalg
  from sklearn.base import clone
  from sklearn.decomposition import NMF, MiniBatchNMF, non_negative_factorization
  from sklearn.decomposition import _nmf
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.utils._testing import assert_allclose, assert_almost_equal, assert_array_almost_equal, assert_array_equal, ignore_warnings
  from sklearn.utils.extmath import squared_norm
  from sklearn.utils.fixes import CSC_CONTAINERS, CSR_CONTAINERS
label_desc: Use image node_id 1 for calling a global function with example usage: test_convergence_warning(Estimator, solver) without return types