code: def test_nmf_n_components_auto(Estimator):
      # Check that n_components is correctly inferred
      # from the provided custom initialization.
      rng = np.random.RandomState(0)
      X = rng.random_sample((6, 5))
      W = rng.random_sample((6, 2))
      H = rng.random_sample((2, 5))
      est = Estimator(
          n_components="auto",
          init="custom",
          random_state=0,
          tol=1e-6,
      )
      est.fit_transform(X, W=W, H=H)
      assert est._n_components == H.shape[0]
  
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 36 for calling a global function with example usage: test_nmf_n_components_auto(Estimator) without return types