rasa/core/test.py
def _in_training_data_fraction(action_list):
    """Given a list of action items, returns the fraction of actions

    that were predicted using one of the Memoization policies."""
    from rasa.core.policies import SimplePolicyEnsemble

    in_training_data = [
        a["action"] for a in action_list
        if not SimplePolicyEnsemble.is_not_memo_policy(a["policy"])
    ]

    return len(in_training_data) / len(action_list)
Given a list of action items, returns the fraction of actions

    that were predicted using one of the Memoization policies.
Given a list of action items, returns the fraction of actions
that were predicted using one of the Memoization policies.
Given a list of action items returns the fraction of actions that were predicted using one of the Memoization policies .
def _in_training_data_fraction(action_list):
    from rasa.core.policies import SimplePolicyEnsemble
    in_training_data = [
        a["action"] for a in action_list
        if not SimplePolicyEnsemble.is_not_memo_policy(a["policy"])
    ]
    return len(in_training_data) / len(action_list)
def _in_training_data_fraction ( action_list ) : from rasa . core . policies import SimplePolicyEnsemble in_training_data = [ a [ "action" ] for a in action_list if not SimplePolicyEnsemble . is_not_memo_policy ( a [ "policy" ] ) ] return len ( in_training_data ) / len ( action_list )
Given a list of action items, returns the fraction of actions
that were predicted using one of the Memoization policies.
Given a list of action items returns the fraction of actions that were predicted using one of the Memoization policies .
"""Given a list of action items, returns the fraction of actions

    that were predicted using one of the Memoization policies."""
action_list