code: def test_third_party_estimator():
      """Check that the validation from a scikit-learn estimator inherited by a third
      party estimator does not impose a match between the dict of constraints and the
      parameters of the estimator.
      """
  
      class ThirdPartyEstimator(_Estimator):
          def __init__(self, b):
              self.b = b
              super().__init__(a=0)
  
          def fit(self, X=None, y=None):
              super().fit(X, y)
  
      # does not raise, even though "b" is not in the constraints dict and "a" is not
      # a parameter of the estimator.
      ThirdPartyEstimator(b=0).fit()
  
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 32 for calling a global function with example usage: test_third_party_estimator() without return types