def save_features(df, data_type='train'):
save_path = Path('../configs/feature/all.yml')
dh = DataHandler()
if not save_path.exists():
save_path.touch()
feature_dict = {'features': []}
else:
feature_dict = dh.load(save_path)
new_feature = sorted(set(feature_dict['features'] + df.columns.tolist()))
feature_dict['features'] = new_feature
dh.save(save_path, feature_dict)
for col in df.columns:
df[[col]].reset_index(drop=True).to_feather(f'../features/{col}_{data_type}.feather')
seed_everything, send_line)
warnings.filterwarnings('ignore')
# ===============
# Settings
# ===============
parser = argparse.ArgumentParser()
parser.add_argument('--common', default='../configs/common/compe.yml')
parser.add_argument('--notify', default='../configs/common/notify.yml')
parser.add_argument('-m', '--model')
parser.add_argument('-c', '--comment')
options = parser.parse_args()
dh = DataHandler()
cfg = dh.load(options.common)
cfg.update(dh.load(f'../configs/exp/{options.model}.yml'))
notify_params = dh.load(options.notify)
comment = options.comment
model_name = options.model
now = datetime.datetime.now()
run_name = f'{model_name}_{now:%Y%m%d%H%M%S}'
logger_path = Path(f'../logs/{run_name}')
# ===============
# Main
# ===============
Kaggle, reduce_mem_usage)
warnings.filterwarnings('ignore')
# ===============
# Settings
# ===============
parser = argparse.ArgumentParser()
parser.add_argument('--common', default='../configs/common/compe.yml')
parser.add_argument('--notify', default='../configs/common/notify.yml')
parser.add_argument('-m', '--model')
parser.add_argument('-c', '--comment')
options = parser.parse_args()
dh = DataHandler()
cfg = dh.load(options.common)
cfg.update(dh.load(f'../configs/exp/{options.model}.yml'))
notify_params = dh.load(options.notify)
features_params = dh.load(f'../configs/feature/{cfg.data.features.name}.yml')
features = features_params.features
comment = options.comment
model_name = options.model
now = datetime.datetime.now()
if cfg.model.task_type != 'optuna':
run_name = f'{model_name}_{now:%Y%m%d%H%M%S}'
else:
run_name = f'{model_name}_optuna_{now:%Y%m%d%H%M%S}'