code: def test_pickle_classification(moment):
      expgrad = ExponentiatedGradient(
          LogisticRegression(),
          constraints=moment(),
          eps=0.01,
          nu=0.01,
          max_iter=50,
      )
      X, y, A = _get_data(A_two_dim=False, y_as_scores=False)
  
      expgrad.fit(X, y, sensitive_features=A)
  
      # The following should not throw an exception
      pickle.dumps(expgrad)
  
file_path: fairlearn/test/unit/reductions/exponentiated_gradient/test_pickle.py
imports: import copy
  import pickle
  import pytest
  from sklearn.linear_model import LinearRegression, LogisticRegression
  from fairlearn.reductions import DemographicParity, TruePositiveRateParity, FalsePositiveRateParity, ErrorRateParity
  from fairlearn.reductions import BoundedGroupLoss
  from fairlearn.reductions import AbsoluteLoss, SquareLoss, ZeroOneLoss
  from fairlearn.reductions import ExponentiatedGradient
  from .test_utilities import _get_data
label_desc: Use image node_id 1 for calling a global function with example usage: test_pickle_classification(moment) without return types