def test_prepared_data_for_threshold_prediction(
self,
trained_policy: UnexpecTEDIntentPolicy,
default_domain: Domain,
stories_path: Path,
):
training_trackers = train_trackers(default_domain,
stories_path,
augmentation_factor=0)
training_model_data, _ = trained_policy._prepare_for_training(
training_trackers, default_domain, precomputations=None)
data_for_prediction = trained_policy._prepare_data_for_prediction(
training_model_data)
assert set(
data_for_prediction.data.keys()).issubset(PREDICTION_FEATURES)
def test_post_training_threshold_computation(
self,
trained_policy: UnexpecTEDIntentPolicy,
default_domain: Domain,
stories_path: Path,
):
training_trackers = train_trackers(default_domain,
stories_path,
augmentation_factor=0)
training_model_data, label_ids = trained_policy._prepare_for_training(
training_trackers, default_domain, precomputations=None)
trained_policy.compute_label_quantiles_post_training(
training_model_data, label_ids)
computed_thresholds = trained_policy.label_quantiles
# -1 is used for padding and hence is not expected in the keys
expected_keys = list(np.unique(label_ids))
expected_keys.remove(-1)
assert sorted(list(
computed_thresholds.keys())) == sorted(expected_keys)