code: def test_dtype_correctness(Estimator):
      X = np.array(
          [[1, 1], [3, 4], [5, 7], [4, 1], [2, 6], [3, 10], [3, 2]]
      )
      y = np.array([1, 2, 3, 2, 0, 4, 5]).T
      model = Estimator()
      coef_32 = model.fit(X.astype(np.float32), y).coef_
      coef_64 = model.fit(X.astype(np.float64), y).coef_
      np.testing.assert_allclose(coef_32, coef_64, rtol=1e-4)
  
imports: from math import log
  import numpy
  import pytest
  from sklearn import datasets
  from sklearn.linear_model import ARDRegression, BayesianRidge, Ridge
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import assert_almost_equal, assert_array_almost_equal, assert_array_less
  from sklearn.utils.extmath import fast_logdet
label_desc: Use image node_id 15 for calling a global function with example usage: test_dtype_correctness(Estimator) without return types