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')