def preprocess(config=None, nsample=None): model_class = config if config is not None else config_default mdict = globals()[model_class]() m = mdict['global_pars'] print(mdict) from source import run_preprocess, run_preprocess_old run_preprocess.run_preprocess(config_name= model_class, path_data = m['path_data_train'], path_output = m['path_model'], path_config_model = m['config_path'], n_sample = nsample if nsample is not None else m['n_sample'], mode = 'run_preprocess')
def preprocess(config=None, nsample=None): config_name = config if config is not None else config_default mdict = globals()[config_name]() m = mdict['global_pars'] print(mdict) from source import run_preprocess run_preprocess.run_preprocess(config_name = config_name, config_path = m['config_path'], n_sample = nsample if nsample is not None else m['n_sample'], ### Optonal mode = 'run_preprocess')
def preprocess(config='', nsample=None): """ """ config_uri, config_name = get_config_path(config) mdict = get_global_pars(config_uri) m = mdict['global_pars'] log(mdict) from source import run_preprocess run_preprocess.run_preprocess( config_name=config_name, config_path=m['config_path'], n_sample=nsample if nsample is not None else m['n_sample'], ### Optonal mode='run_preprocess')