def _train(skip_saving=False):
    arg_parser = train_argparser()
    if not skip_saving:
        process_configs(target=__train, arg_parser=arg_parser)
    else:
        run_args = process_configs_serial(arg_parser)
        trained_model = __train(run_args, skip_saving)
        return trained_model
def _eval():
    arg_parser = eval_argparser()
    process_configs(target=__eval, arg_parser=arg_parser)
Exemple #3
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def _predict():
    arg_parser = predict_argparser()
    process_configs(target=__predict, arg_parser=arg_parser)
Exemple #4
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def _train():
    arg_parser = train_argparser()
    process_configs(target=__train, arg_parser=arg_parser)
Exemple #5
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def _train():
    arg_parser = train_argparser()  # this one put relevant arguments in argparser
    process_configs(target=__train, arg_parser=arg_parser)