paddlenlp/metrics/chunk.py
def accumulate(self):
        """
        This function returns the mean precision, recall and f1 score for all accumulated minibatches.

        Returns:
            tuple: Returns tuple (`precision, recall, f1 score`).
        """
        precision = float(
            self.num_correct_chunks /
            self.num_infer_chunks) if self.num_infer_chunks else 0.
        recall = float(self.num_correct_chunks /
                       self.num_label_chunks) if self.num_label_chunks else 0.
        f1_score = float(2 * precision * recall / (
            precision + recall)) if self.num_correct_chunks else 0.
        return precision, recall, f1_score

        This function returns the mean precision, recall and f1 score for all accumulated minibatches.

        Returns:
            tuple: Returns tuple (`precision, recall, f1 score`).
        
This function returns the mean precision, recall and f1 score for all accumulated minibatches.
This function returns the mean precision recall and f1 score for all accumulated minibatches .
def accumulate(self):
        precision = float(
            self.num_correct_chunks /
            self.num_infer_chunks) if self.num_infer_chunks else 0.
        recall = float(self.num_correct_chunks /
                       self.num_label_chunks) if self.num_label_chunks else 0.
        f1_score = float(2 * precision * recall / (
            precision + recall)) if self.num_correct_chunks else 0.
        return precision, recall, f1_score
def accumulate ( self ) : precision = float ( self . num_correct_chunks / self . num_infer_chunks ) if self . num_infer_chunks else 0. recall = float ( self . num_correct_chunks / self . num_label_chunks ) if self . num_label_chunks else 0. f1_score = float ( 2 * precision * recall / ( precision + recall ) ) if self . num_correct_chunks else 0. return precision , recall , f1_score
This function returns the mean precision, recall and f1 score for all accumulated minibatches.
This function returns the mean precision recall and f1 score for all accumulated minibatches .
"""
        This function returns the mean precision, recall and f1 score for all accumulated minibatches.

        Returns:
            tuple: Returns tuple (`precision, recall, f1 score`).
        """
Returns tuple (`precision, recall, f1 score`).
Returns tuple ( ` precision recall f1 score ` ) .
tuple
self