def test_classifier_accuracy(save_path):
    cortex_dataset = CortexDataset(save_path=save_path)
    cls = Classifier(cortex_dataset.nb_genes, n_labels=cortex_dataset.n_labels)
    cls_trainer = ClassifierTrainer(cls, cortex_dataset, metrics_to_monitor=['accuracy'], frequency=1, early_stopping_kwargs={'early_stopping_metric': 'accuracy', 'save_best_state_metric': 'accuracy'})
    cls_trainer.train(n_epochs=2)
    cls_trainer.train_set.accuracy()
def test_classifier_accuracy(save_path):
    cortex_dataset = CortexDataset(save_path=save_path)
    cls = Classifier(cortex_dataset.nb_genes, n_labels=cortex_dataset.n_labels)
    cls_trainer = ClassifierTrainer(cls, cortex_dataset, metrics_to_monitor=['accuracy'], frequency=1, early_stopping_kwargs={'early_stopping_metric': 'accuracy', 'save_best_state_metric': 'accuracy'})
    cls_trainer.train(n_epochs=2)
    cls_trainer.train_set.accuracy()