rasa/core/featurizers.py
def create_encoded_all_actions(self, domain: Domain) -> np.ndarray:
        """Create matrix with all actions from domain
            encoded in rows as bag of words."""
        encoded_all_actions = np.zeros((domain.num_actions,
                                        len(self.bot_vocab)),
                                       dtype=int)
        for idx, name in enumerate(domain.action_names):
            for t in name.split(self.split_symbol):
                encoded_all_actions[idx, self.bot_vocab[t]] = 1
        return encoded_all_actions
Create matrix with all actions from domain
            encoded in rows as bag of words.
Create matrix with all actions from domain
encoded in rows as bag of words.
Create matrix with all actions from domain encoded in rows as bag of words .
def create_encoded_all_actions(self, domain: Domain) -> np.ndarray:
        encoded_all_actions = np.zeros((domain.num_actions,
                                        len(self.bot_vocab)),
                                       dtype=int)
        for idx, name in enumerate(domain.action_names):
            for t in name.split(self.split_symbol):
                encoded_all_actions[idx, self.bot_vocab[t]] = 1
        return encoded_all_actions
def create_encoded_all_actions ( self , domain : Domain ) -> np . ndarray : encoded_all_actions = np . zeros ( ( domain . num_actions , len ( self . bot_vocab ) ) , dtype = int ) for idx , name in enumerate ( domain . action_names ) : for t in name . split ( self . split_symbol ) : encoded_all_actions [ idx , self . bot_vocab [ t ] ] = 1 return encoded_all_actions
Create matrix with all actions from domain
encoded in rows as bag of words.
Create matrix with all actions from domain encoded in rows as bag of words .
"""Create matrix with all actions from domain
            encoded in rows as bag of words."""
self
domain
Domain