models.py 文件源码

def get_predicted_antecedents(self, antecedents, antecedent_scores):
        """
        Forms a list of predicted antecedent labels
        Args:
            antecedents: [] get from C++ function
            antecedent_scores: [num_mentions, max_ant + 1] output of fully-connected network
                that compute antecedent_scores

        Returns: a list of predicted antecedent labels

        """
        predicted_antecedents = []
        for i, index in enumerate(np.argmax(antecedent_scores, axis=1) - 1):
            if index < 0:
                predicted_antecedents.append(-1)
            else:
                predicted_antecedents.append(antecedents[i, index])
        return predicted_antecedents