def test_all_networks(): for name, network in construct_all_classifiers(SMALL_NB_EPOCHS).items(): print("\n\t\t" + name + " testing started") # test_basic_univariate(network) test_basic_multivariate(network) # test_pipeline(network) test_highLevelsktime(network) print("\t\t" + name + " testing finished")
def test_all_networks(): networks = { **construct_all_classifiers(SMALL_NB_EPOCHS), **construct_all_regressors(SMALL_NB_EPOCHS), } for name, network in networks.items(): print("\n\t\t" + name + " is_fitted testing started") test_is_fitted(network) print("\t\t" + name + " is_fitted testing finished")
def test_all_networks(): networks = { **construct_all_classifiers(SMALL_NB_EPOCHS), **construct_all_regressors(SMALL_NB_EPOCHS), } # these networks do not support validation data as yet networks.pop('MCNNClassifier_quick') networks.pop('TWIESNClassifier_quick') # networks = [ # MLPClassifier(nb_epochs=SMALL_NB_EPOCHS), # ResNetClassifier(nb_epochs=SMALL_NB_EPOCHS), # InceptionTimeClassifier(nb_epochs=SMALL_NB_EPOCHS), # ] for name, network in networks.items(): print("\n\t\t" + name + " validation testing started") test_validation(network) print("\t\t" + name + " validation testing finished")