starter.py 文件源码

def start_keras(logger, job_backend):
    if 'KERAS_BACKEND' not in os.environ:
        os.environ['KERAS_BACKEND'] = 'tensorflow'

    from . import keras_model_utils

    # we need to import keras here, so we know which backend is used (and whether GPU is used)
    os.chdir(job_backend.git.work_tree)
    logger.debug("Start simple model")

    # we use the source from the job commit directly
    with job_backend.git.batch_commit('Git Version'):
        job_backend.set_system_info('git_remote_url', job_backend.git.get_remote_url('origin'))
        job_backend.set_system_info('git_version', job_backend.git.job_id)

    # all our shapes are Tensorflow schema. (height, width, channels)
    import keras.backend
    if hasattr(keras.backend, 'set_image_dim_ordering'):
        keras.backend.set_image_dim_ordering('tf')

    if hasattr(keras.backend, 'set_image_data_format'):
        keras.backend.set_image_data_format('channels_last')

    from .KerasCallback import KerasCallback
    trainer = Trainer(job_backend)
    keras_logger = KerasCallback(job_backend, job_backend.logger)

    job_backend.progress(0, job_backend.job['config']['epochs'])

    logger.info("Start training")
    keras_model_utils.job_start(job_backend, trainer, keras_logger)

    job_backend.done()