def test_does_model_improve(
previous_best: Dict[Text, float],
current_values: Dict[Text, float],
improved: bool,
tmpdir: Path,
):
checkpoint = RasaModelCheckpoint(tmpdir)
checkpoint.best_metrics_so_far = previous_best
# true iff all values are equal or better and at least one is better
assert checkpoint._does_model_improve(current_values) == improved
def test_on_epoch_end_saves_checkpoints_file(
previous_best: Dict[Text, float],
current_values: Dict[Text, float],
improved: bool,
tmp_path: Path,
trained_ted: TEDPolicy,
):
model_name = "checkpoint"
best_model_file = tmp_path / model_name
assert not best_model_file.exists()
checkpoint = RasaModelCheckpoint(tmp_path)
checkpoint.best_metrics_so_far = previous_best
checkpoint.model = trained_ted.model
checkpoint.on_epoch_end(1, current_values)
if improved:
assert best_model_file.exists()
else:
assert not best_model_file.exists()