code: def test_convert_estimator_to_ndarray(array_namespace, converter):
      """Convert estimator attributes to ndarray."""
      xp = pytest.importorskip(array_namespace)
  
      X = xp.asarray([[1.3, 4.5]])
      est = SimpleEstimator().fit(X)
  
      new_est = _estimator_with_converted_arrays(est, converter)
      assert isinstance(new_est.X_, numpy.ndarray)
  
imports: from functools import partial
  import numpy
  import pytest
  from numpy.testing import assert_allclose
  from sklearn._config import config_context
  from sklearn.base import BaseEstimator
  from sklearn.utils._array_api import _ArrayAPIWrapper, _asarray_with_order, _atol_for_type, _convert_to_numpy, _estimator_with_converted_arrays, _nanmax, _nanmin, _NumPyAPIWrapper, _weighted_sum, get_namespace, supported_float_dtypes, yield_namespace_device_dtype_combinations
  from sklearn.utils._testing import _array_api_for_tests, skip_if_array_api_compat_not_configured
label_desc: Use image node_id 12 for calling a global function with example usage: test_convert_estimator_to_ndarray(array_namespace, converter) without return types