code: def test_pca_score_consistency_solvers(svd_solver):
      # Check the consistency of score between solvers
      X, _ = datasets.load_digits(return_X_y=True)
      pca_full = PCA(n_components=30, svd_solver="full", random_state=0)
      pca_other = PCA(
          n_components=30, svd_solver=svd_solver, random_state=0
      )
      pca_full.fit(X)
      pca_other.fit(X)
      assert_allclose(pca_full.score(X), pca_other.score(X), rtol=5e-6)
  
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 27 for calling a global function with example usage: test_pca_score_consistency_solvers(svd_solver) without return types