code: def test__get_output_config(transform_output):
      """Check _get_output_config works as expected."""
  
      # Without a configuration set, the global config is used
      global_config = get_config()["transform_output"]
      config = _get_output_config("transform")
      assert config["dense"] == global_config
  
      with config_context(transform_output=transform_output):
          # with estimator=None, the global config is used
          config = _get_output_config("transform")
          assert config["dense"] == transform_output
  
          est = EstimatorNoSetOutputWithTransform()
          config = _get_output_config("transform", est)
          assert config["dense"] == transform_output
  
          est = EstimatorWithSetOutput()
          # If estimator has not config, use global config
          config = _get_output_config("transform", est)
          assert config["dense"] == transform_output
  
          # If estimator has a config, use local config
          est.set_output(transform="default")
          config = _get_output_config("transform", est)
          assert config["dense"] == "default"
  
      est.set_output(transform=transform_output)
      config = _get_output_config("transform", est)
      assert config["dense"] == transform_output
  
imports: import importlib
  from collections import namedtuple
  import numpy
  import pytest
  from numpy.testing import assert_array_equal
  from sklearn._config import config_context, get_config
  from sklearn.preprocessing import StandardScaler
  from sklearn.utils._set_output import ADAPTERS_MANAGER, ContainerAdapterProtocol, _get_output_config, _safe_set_output, _SetOutputMixin, _wrap_data_with_container, check_library_installed
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 9 for calling a global function with example usage: test__get_output_config(transform_output) without return types