from .nmt_uni import train
from .config import pretrain_config


def main(job_id, params):
    print('pretraining settings:')
    for c, v in sorted(list(params.items()), key=lambda a: a[0]):
        print('{}: {}'.format(c, v))
    validerr = train(**params)
    return validerr


if __name__ == '__main__':
    main(0, pretrain_config())

7d30df9c7c18277b4c65d045341196facd7ae9da
<mask token>

<mask token>


def main(job_id, params):
    print('pretraining settings:')
    for c, v in sorted(list(params.items()), key=lambda a: a[0]):
        print('{}: {}'.format(c, v))
    validerr = train(**params)
    return validerr


<mask token>

<mask token>


def main(job_id, params):
    print('pretraining settings:')
    for c, v in sorted(list(params.items()), key=lambda a: a[0]):
        print('{}: {}'.format(c, v))
    validerr = train(**params)
    return validerr


if __name__ == '__main__':
    main(0, pretrain_config())

from .nmt_uni import train
from .config import pretrain_config


def main(job_id, params):
    print('pretraining settings:')
    for c, v in sorted(list(params.items()), key=lambda a: a[0]):
        print('{}: {}'.format(c, v))
    validerr = train(**params)
    return validerr


if __name__ == '__main__':
    main(0, pretrain_config())
