code: def check_array_api_get_precision(
      name, estimator, array_namespace, device, dtype_name
  ):
      xp = _array_api_for_tests(array_namespace, device)
      iris_np = iris.data.astype(dtype_name)
      iris_xp = xp.asarray(iris_np, device=device)
  
      estimator.fit(iris_np)
      precision_np = estimator.get_precision()
      covariance_np = estimator.get_covariance()
  
      with config_context(array_api_dispatch=True):
          estimator_xp = clone(estimator).fit(iris_xp)
          precision_xp = estimator_xp.get_precision()
          assert precision_xp.shape == (4, 4)
          assert precision_xp.dtype == iris_xp.dtype
  
          assert_allclose(
              _convert_to_numpy(precision_xp, xp=xp),
              precision_np,
              atol=_atol_for_type(dtype_name),
          )
          covariance_xp = estimator_xp.get_covariance()
          assert covariance_xp.shape == (4, 4)
          assert covariance_xp.dtype == iris_xp.dtype
  
          assert_allclose(
              _convert_to_numpy(covariance_xp, xp=xp),
              covariance_np,
              atol=_atol_for_type(dtype_name),
          )
  
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 44 for calling a global function with example usage: check_array_api_get_precision(name, estimator, array_namespace, device, dtype_name) without return types