def test_keras_pruning_callback_monitor_is_invalid() -> None:
study = optuna.create_study(pruner=DeterministicPruner(True))
trial = study.ask()
callback = KerasPruningCallback(trial, "InvalidMonitor")
with pytest.warns(UserWarning):
callback.on_epoch_end(0, {"loss": 1.0})
def test_keras_pruning_callback_observation_isnan() -> None:
study = optuna.create_study(pruner=DeterministicPruner(True))
trial = study.ask()
callback = KerasPruningCallback(trial, "loss")
with pytest.raises(optuna.TrialPruned):
callback.on_epoch_end(0, {"loss": 1.0})
with pytest.raises(optuna.TrialPruned):
callback.on_epoch_end(0, {"loss": float("nan")})
def test_keras_pruning_callback_observation_isnan():
# type: () -> None
study = optuna.create_study(pruner=DeterministicPruner(True))
trial = create_running_trial(study, 1.0)
callback = KerasPruningCallback(trial, "loss")
with pytest.raises(optuna.exceptions.TrialPruned):
callback.on_epoch_end(0, {"loss": 1.0})
with pytest.raises(optuna.exceptions.TrialPruned):
callback.on_epoch_end(0, {"loss": float("nan")})
def test_keras_pruning_callback_observation_isnan():
# type: () -> None
study = optuna.create_study(pruner=DeterministicPruner(True))
trial = study._run_trial(func=lambda _: 1.0, catch=(Exception, ))
callback = KerasPruningCallback(trial, 'loss')
with pytest.raises(optuna.structs.TrialPruned):
callback.on_epoch_end(0, {'loss': 1.0})
with pytest.raises(optuna.structs.TrialPruned):
callback.on_epoch_end(0, {'loss': float('nan')})
def test_keras_pruning_callback_observation_isnan():
# type: () -> None
# TODO(higumachan): remove this "if" section after Tensorflow supports Python 3.7.
if not _available:
pytest.skip(
'This test requires keras '
'but this version can not install keras(tensorflow) with pip.')
study = optuna.create_study(pruner=DeterministicPruner(True))
trial = study._run_trial(func=lambda _: 1.0, catch=(Exception, ))
callback = KerasPruningCallback(trial, 'loss')
with pytest.raises(optuna.structs.TrialPruned):
callback.on_epoch_end(0, {'loss': 1.0})
with pytest.raises(optuna.structs.TrialPruned):
callback.on_epoch_end(0, {'loss': float('nan')})