metrics/accuracy.py

import re

PATTERN = re.compile(r'\b[A-D]\b')


def find_answer(s):
    match = PATTERN.search(s)
    if match is None:
        return None
    return match.group()


def accuracy_score(prediction, ground_truth):
    letter_ground_truth = find_answer(ground_truth)
    assert letter_ground_truth in ["A", "B", "C", "D"], f"Invalid ground truth: {ground_truth}"
    letter_prediction = find_answer(str(prediction))
    return letter_prediction == letter_ground_truth


def metric_max_over_ground_truths(metric_fn, prediction, ground_truths):
    scores_for_ground_truths = []
    for ground_truth in ground_truths:
        score = metric_fn(prediction, ground_truth)
        scores_for_ground_truths.append(score)
    return max(scores_for_ground_truths)


def compute_accuracy(predictions, references):
    accuracy = 0
    for prediction, ground_truths in zip(predictions, references):
        accuracy += metric_max_over_ground_truths(accuracy_score, prediction, ground_truths)
    return 100.0 * accuracy / len(predictions)