code: def get_namespace(*arrays):
      """Get namespace of arrays.
  
      Introspect `arrays` arguments and return their common Array API
      compatible namespace object, if any. NumPy 1.22 and later can
      construct such containers using the `numpy.array_api` namespace
      for instance.
  
      See: https://numpy.org/neps/nep-0047-array-api-standard.html
  
      If `arrays` are regular numpy arrays, an instance of the
      `_NumPyAPIWrapper` compatibility wrapper is returned instead.
  
      Namespace support is not enabled by default. To enabled it
      call:
  
        sklearn.set_config(array_api_dispatch=True)
  
      or:
  
        with sklearn.config_context(array_api_dispatch=True):
            # your code here
  
      Otherwise an instance of the `_NumPyAPIWrapper`
      compatibility wrapper is always returned irrespective of
      the fact that arrays implement the `__array_namespace__`
      protocol or not.
  
      Parameters
      ----------
      *arrays : array objects
          Array objects.
  
      Returns
      -------
      namespace : module
          Namespace shared by array objects. If any of the `arrays` are not arrays,
          the namespace defaults to NumPy.
  
      is_array_api_compliant : bool
          True if the arrays are containers that implement the Array API spec.
          Always False when array_api_dispatch=False.
      """
      array_api_dispatch = get_config()["array_api_dispatch"]
      if not array_api_dispatch:
          return _NUMPY_API_WRAPPER_INSTANCE, False
  
      _check_array_api_dispatch(array_api_dispatch)
  
      # array-api-compat is a required dependency of scikit-learn only when
      # configuring `array_api_dispatch=True`. Its import should therefore be
      # protected by _check_array_api_dispatch to display an informative error
      # message in case it is missing.
      import array_api_compat
  
      namespace, is_array_api_compliant = (
          array_api_compat.get_namespace(*arrays),
          True,
      )
  
      if namespace.__name__ in {"numpy.array_api", "cupy.array_api"}:
          namespace = _ArrayAPIWrapper(namespace)
  
      return namespace, is_array_api_compliant
  
imports: import math
  from functools import wraps
  import numpy
  import scipy.special
  from .._config import get_config
  from .fixes import parse_version
label_desc: Use image node_id 9 for calling a global function with example usage: get_namespace() and returns: namespace,  is_array_api_compliant, _NUMPY_API_WRAPPER_INSTANCE,  False