def test_init_custom_parameters():
 tpot_obj = TPOTClassifier(population_size=500, generations=1000, mutation_rate=0.05, crossover_rate=0.9, scoring='accuracy', num_cv_folds=10, verbosity=1, random_state=42, disable_update_check=True)
 assert (tpot_obj.population_size == 500)
 assert (tpot_obj.generations == 1000)
 assert (tpot_obj.mutation_rate == 0.05)
 assert (tpot_obj.crossover_rate == 0.9)
 assert (tpot_obj.scoring_function == 'accuracy')
 assert (tpot_obj.num_cv_folds == 10)
 assert (tpot_obj.max_time_mins is None)
 assert (tpot_obj.verbosity == 1)
 assert (tpot_obj._optimized_pipeline is None)
 assert (tpot_obj._fitted_pipeline is None)
 assert (not (tpot_obj._pset is None))
 assert (not (tpot_obj._toolbox is None))

def test_init_custom_parameters ( ) : tpot_obj = TPOTClassifier ( population_size = 500 , generations = 1000 , mutation_rate = 0.05 , crossover_rate = 0.9 , scoring = 'accuracy' , num_cv_folds = 10 , verbosity = 1 , random_state = 42 , disable_update_check = True ) assert ( tpot_obj . population_size == 500 ) assert ( tpot_obj . generations == 1000 ) assert ( tpot_obj . mutation_rate == 0.05 ) assert ( tpot_obj . crossover_rate == 0.9 ) assert ( tpot_obj . scoring_function == 'accuracy' ) assert ( tpot_obj . num_cv_folds == 10 ) assert ( tpot_obj . max_time_mins is None ) assert ( tpot_obj . verbosity == 1 ) assert ( tpot_obj . _optimized_pipeline is None ) assert ( tpot_obj . _fitted_pipeline is None ) assert ( not ( tpot_obj . _pset is None ) ) assert ( not ( tpot_obj . _toolbox is None ) )
assert that the tpot instantiator stores the tpot variables properly .