code: def test_lda_numeric_consistency_float32_float64():
      for solver, shrinkage in solver_shrinkage:
          clf_32 = LinearDiscriminantAnalysis(
              solver=solver, shrinkage=shrinkage
          )
          clf_32.fit(X.astype(np.float32), y.astype(np.float32))
          clf_64 = LinearDiscriminantAnalysis(
              solver=solver, shrinkage=shrinkage
          )
          clf_64.fit(X.astype(np.float64), y.astype(np.float64))
  
          # Check value consistency between types
          rtol = 1e-6
          assert_allclose(clf_32.coef_, clf_64.coef_, rtol=rtol)
  
imports: import numpy
  import pytest
  from scipy import linalg
  from sklearn.cluster import KMeans
  from sklearn.covariance import LedoitWolf, ShrunkCovariance, ledoit_wolf
  from sklearn.datasets import make_blobs
  from sklearn.discriminant_analysis import LinearDiscriminantAnalysis, QuadraticDiscriminantAnalysis, _cov
  from sklearn.preprocessing import StandardScaler
  from sklearn.utils import _IS_WASM, check_random_state
  from sklearn.utils._testing import _convert_container, assert_allclose, assert_almost_equal, assert_array_almost_equal, assert_array_equal
label_desc: Use image node_id 14 for calling a global function with example usage: test_lda_numeric_consistency_float32_float64() without return types