submit_predictions.py 文件源码

def load_cv_folds(model_name):
    models = []
    for i in range(5):
        net = np.load(paths.predictions + model_name + '-split_{}.npz'.format(i))
        net = {
            'train': np.average(net['train'], axis=0),
            'val': np.average(net['val'], axis=0),
            'test': np.average(net['test'], axis=0)
        }
        models.append(net)

    labels_df = labels.get_labels_df()
    kf = sklearn.model_selection.KFold(n_splits=5, shuffle=True, random_state=1)
    split = kf.split(labels_df)
    folds = []
    for i, ((train_idx, val_idx), net) in enumerate(zip(split, models)):
        val = labels_df.ix[val_idx]
        train = labels_df.ix[train_idx]
        folds.append((net, val, train))
        print(i)

    return folds

# load_cv_folds takes the model name