def test_pytorch_lightning_pruning_callback_monitor_is_invalid() -> None: study = optuna.create_study(pruner=DeterministicPruner(True)) trial = study.ask() callback = PyTorchLightningPruningCallback(trial, "InvalidMonitor") trainer = pl.Trainer( max_epochs=1, enable_checkpointing=False, callbacks=[callback], ) model = Model() with pytest.warns(UserWarning): callback.on_validation_end(trainer, model)
def test_pytorch_lightning_pruning_callback_monitor_is_invalid() -> None: study = optuna.create_study(pruner=DeterministicPruner(True)) trial = create_running_trial(study, 1.0) callback = PyTorchLightningPruningCallback(trial, "InvalidMonitor") trainer = pl.Trainer( min_epochs=0, # Required to fire the callback after the first epoch. max_epochs=1, checkpoint_callback=False, callbacks=[callback], ) model = Model() with pytest.warns(UserWarning): callback.on_validation_end(trainer, model)