code: def test_no_validation():
      """Check that validation can be skipped for a parameter."""
  
      @validate_params(
          {"param1": [int, None], "param2": "no_validation"},
          prefer_skip_nested_validation=True,
      )
      def f(param1=None, param2=None):
          pass
  
      # param1 is validated
      with pytest.raises(
          InvalidParameterError, match="The 'param1' parameter"
      ):
          f(param1="wrong")
  
      # param2 is not validated: any type is valid.
      class SomeType:
          pass
  
      f(param2=SomeType)
      f(param2=SomeType())
  
imports: from numbers import Integral, Real
  import numpy
  import pytest
  from scipy.sparse import csr_matrix
  from sklearn._config import config_context, get_config
  from sklearn.base import BaseEstimator, _fit_context
  from sklearn.model_selection import LeaveOneOut
  from sklearn.utils import deprecated
  from sklearn.utils._param_validation import HasMethods, Hidden, Interval, InvalidParameterError, MissingValues, Options, RealNotInt, StrOptions, _ArrayLikes, _Booleans, _Callables, _CVObjects, _InstancesOf, _IterablesNotString, _NanConstraint, _NoneConstraint, _PandasNAConstraint, _RandomStates, _SparseMatrices, _VerboseHelper, generate_invalid_param_val, generate_valid_param, make_constraint, validate_params
label_desc: Use image node_id 28 for calling a global function with example usage: test_no_validation() without return types