def test_is_not_in_training_data(
policy_name: Text, confidence: Optional[float], not_in_training_data: bool
):
assert (
SimplePolicyEnsemble.is_not_in_training_data(policy_name, confidence)
== not_in_training_data
)
def _in_training_data_fraction(action_list: List[Dict[Text, Any]]) -> float:
"""Given a list of action items, returns the fraction of actions
that were predicted using one of the Memoization policies."""
from rasa.core.policies.ensemble import SimplePolicyEnsemble
in_training_data = [
a["action"] for a in action_list if a["policy"]
and not SimplePolicyEnsemble.is_not_in_training_data(a["policy"])
]
return len(in_training_data) / len(action_list) if action_list else 0