code: def test_pca_svd_solver_auto(data, n_components, expected_solver):
      pca_auto = PCA(n_components=n_components, random_state=0)
      pca_test = PCA(
          n_components=n_components,
          svd_solver=expected_solver,
          random_state=0,
      )
      pca_auto.fit(data)
      pca_test.fit(data)
      assert_allclose(pca_auto.components_, pca_test.components_)
  
imports: import re
  import warnings
  import numpy
  import pytest
  import scipy
  from numpy.testing import assert_array_equal
  from sklearn import config_context, datasets
  from sklearn.base import clone
  from sklearn.datasets import load_iris, make_classification
  from sklearn.decomposition import PCA
  from sklearn.decomposition._pca import _assess_dimension, _infer_dimension
  from sklearn.utils._array_api import _atol_for_type, _convert_to_numpy, yield_namespace_device_dtype_combinations
  from sklearn.utils._array_api import device
  from sklearn.utils._testing import _array_api_for_tests, assert_allclose
  from sklearn.utils.estimator_checks import _get_check_estimator_ids, check_array_api_input_and_values
  from sklearn.utils.fixes import CSC_CONTAINERS, CSR_CONTAINERS
label_desc: Use image node_id 29 for calling a global function with example usage: test_pca_svd_solver_auto(data, n_components, expected_solver) without return types