def test_get_test_epochs() -> None: """ Test if the creation of the list of epochs for model testing will always contain at least the last training epoch. """ c = DeepLearningConfig(num_epochs=2, test_start_epoch=100, test_diff_epochs=2, test_step_epochs=10, should_validate=False) assert c.get_test_epochs() == [2] c = DeepLearningConfig(num_epochs=100, test_start_epoch=100, test_diff_epochs=2, test_step_epochs=10, should_validate=False) assert c.get_test_epochs() == [100] c = DeepLearningConfig(num_epochs=150, test_start_epoch=100, test_diff_epochs=2, test_step_epochs=10, should_validate=False) assert c.get_test_epochs() == [100, 110, 150] c = DeepLearningConfig(num_epochs=100, test_start_epoch=100, test_diff_epochs=0, test_step_epochs=10, should_validate=False) assert c.get_test_epochs() == [100] c = DeepLearningConfig(num_epochs=100, test_start_epoch=200, test_diff_epochs=None, test_step_epochs=10, should_validate=False) assert c.get_test_epochs() == [100]
def test_get_test_epochs() -> None: """ Test if the creation of the list of epochs for model testing will always contain at least the last training epoch. """ c = DeepLearningConfig(num_epochs=2, test_start_epoch=100, test_diff_epochs=2, test_step_epochs=10, should_validate=False) assert c.get_test_epochs() == [2] c = DeepLearningConfig(num_epochs=100, test_start_epoch=100, test_diff_epochs=2, test_step_epochs=10, should_validate=False) assert c.get_test_epochs() == [100] c = DeepLearningConfig(num_epochs=150, test_start_epoch=100, test_diff_epochs=2, test_step_epochs=10, should_validate=False) assert c.get_test_epochs() == [100, 110, 150] c = DeepLearningConfig(num_epochs=100, test_start_epoch=100, test_diff_epochs=0, test_step_epochs=10, should_validate=False) assert c.get_test_epochs() == [100] c = DeepLearningConfig(num_epochs=100, test_start_epoch=200, test_diff_epochs=None, test_step_epochs=10, should_validate=False) assert c.get_test_epochs() == [100] c = DeepLearningConfig(num_epochs=100, epochs_to_test=[1, 3, 5], should_validate=False) assert c.get_test_epochs() == [1, 3, 5, 100] # epochs_to_test should have precedence over (test_start_epoch, test_diff_epochs and test_step_epochs) c = DeepLearningConfig(num_epochs=150, epochs_to_test=[1, 3, 5], test_start_epoch=100, test_diff_epochs=2, test_step_epochs=10, should_validate=False) assert c.get_test_epochs() == [1, 3, 5, 150]