def dev_eval()

in scripts/adapet/ADAPET/src/eval/eval_model.py [0:0]

• 34 lines of code
• 4 McCabe index (conditional complexity)

def dev_eval(config, model, batcher, num_batches, dict_avg_val=None):
    '''
    Evaluates the accuracy on the dev partition

    :param config:
    :param model:
    :param batcher: batcher to get batches of data
    :param num_batches:
    :param dict_avg_val: dictionary storing metrics

    :return: currrent dev score
    '''

    dict_eval = {}
    dict_eval["num_batches"] = num_batches

    if dict_avg_val is not None:
        dict_eval.update(dict_avg_val)

    # Get train Score
    if config.eval_train:
        train_scorer = Scorer(config, config.dataset)
        train_iter = batcher.get_eval_train_batch()
        eval(config, model, train_iter, train_scorer)
        _, train_scores = train_scorer.get_score("train")
        dict_eval.update(train_scores)

    # Get dev Score
    if config.eval_dev:
        dev_scorer = Scorer(config, config.dataset)
        dev_iter = batcher.get_dev_batch()
        eval(config, model, dev_iter, dev_scorer)
        score_eval, dev_scores = dev_scorer.get_score("dev")
        dict_eval.update(dev_scores)
        dev_logits = dev_scorer.get_logits()
    else:
        score_eval = 0
        dev_logits = None

    with open(config.dev_score_file, 'a+') as f_out:
        f_out.write(json.dumps(dict_eval))
        f_out.write('\n')

    return score_eval, dev_logits