How to make LightGBM to suppress output?

Question

I have tried for a while to figure out how to "shut up" LightGBM. Especially, I would like to suppress the output of LightGBM during training (i.e. feedback on the boosting steps).

My model:

params = {
            'objective': 'regression',
            'learning_rate' :0.9,
            'max_depth' : 1,
            'metric': 'mean_squared_error',
            'seed': 7,
            'boosting_type' : 'gbdt'
        }

gbm = lgb.train(params,
                lgb_train,
                num_boost_round=100000,
                valid_sets=lgb_eval,
                early_stopping_rounds=100)

I tried to add verbose=0 as suggested in the docs, but this does not work. https://github.com/microsoft/LightGBM/blob/master/docs/Parameters.rst

Does anyone know how to suppress LightGBM output during training?

Perhaps it's `verbose_eval` you're looking for? https://lightgbm.readthedocs.io/en/latest/Python-API.html — bradS, Jun 17 '19 at 15:12
Yep, got rid of most feedback! Thanks! Any idea how I can also suppress warnings, because I still receive a lot of warnings as feedback. — Peter, Jun 17 '19 at 15:17
It is „No further splits with positive gain“, likely caused by min_data_in_leaf. However, I would like to keep the configuration. My current application is a parameter search. — Peter, Jun 17 '19 at 21:08
This is the latest I update on the issue that I can see: https://github.com/Microsoft/LightGBM/issues/1157#issuecomment-417373690 — bradS, Jun 17 '19 at 21:13
Thanks! I‘ll check it soon. If you feel like, post your combined answers/suggestions in as answer, so others can follow it and I can vote it up. Cheers! — Peter, Jun 17 '19 at 21:21

banderlog013 · Answer 1 · 2021-10-19T22:14:17.537

8

Solution for sklearn API (checked on v3.3.0):

import lightgbm as lgb


param = {'objective': 'binary', "is_unbalance": 'true',
         'metric': 'average_precision'}
model_skl = lgb.sklearn.LGBMClassifier(**param)

# early stopping and verbosity
# it should be 0 or False, not -1/-100/etc
callbacks = [lgb.early_stopping(10, verbose=0), lgb.log_evaluation(period=0)]

# train
model_skl.fit(x_train, y_train,
              eval_set=[(x_train, y_train), (x_val, y_val)],
              eval_names=['train', 'valid'],
              eval_metric='average_precision',
              callbacks=callbacks)

edited Oct 19 '21 at 22:14

answered Oct 19 '21 at 20:14

banderlog013

181
1
3

1

Confirmed. `log_evaluation(0)` is the important piece for turning off the booster updates. – Josephine Moeller Dec 15 '21 at 00:16

score 8 · Accepted Answer · answered Jun 18 '19 at 08:21

As @Peter has suggested, setting verbose_eval = -1 suppresses most of LightGBM output (link: here).

However, LightGBM may still return other warnings - e.g. No further splits with positive gain. This can be suppressed as follows (source: here ):

lgb_train = lgb.Dataset(X_train, y_train, params={'verbose': -1}, free_raw_data=False)
lgb_eval = lgb.Dataset(X_test, y_test, params={'verbose': -1},free_raw_data=False)
gbm = lgb.train({'verbose': -1}, lgb_train, valid_sets=lgb_eval, verbose_eval=False)

score 6 · Answer 3 · answered Jun 18 '19 at 07:05

To suppress (most) output from LightGBM, the following parameter can be set.

Suppress warnings: 'verbose': -1 must be specified in params={}.

Suppress output of training iterations: verbose_eval=False must be specified in the train{} parameter.

Minimal example:

params = {
            'objective': 'regression',
            'learning_rate' : 0.9, 
            'max_depth' : 1, 
            'metric': 'mean_squared_error',
            'seed': 7,
            'verbose': -1,
            'boosting_type' : 'gbdt'
        }

gbm = lgb.train(params,
                lgb_train,
                num_boost_round=100000,
                valid_sets=lgb_eval,
                verbose_eval=False,
                early_stopping_rounds=100)

score 4 · Answer 4 · edited Jul 14 '21 at 16:27

4

Follow these points.

Use verbose= False in fit method.
Use verbose= -100 when you call the classifier.
Keep silent = True (default).

edited Jul 14 '21 at 16:27

Ethan

1,625
8
23
39

answered Jul 14 '21 at 14:50

bharat bhimshetty

41
1

score 1 · Answer 5 · answered Oct 14 '22 at 14:13

1

I read all the answers and issues, and tried all these approaches and yet LGBM still outputs some info (which drives me crazy). If you want to completely suppress any output during the training try this out:

with open(os.devnull, "w") as f, contextlib.redirect_stdout(f):
    gbm = lgb.cv(param, lgb_dataset)

answered Oct 14 '22 at 14:13

Dmitriy Serebryanskiy

11
1

This was the only way it worked right now. Thanks. – igorkf Feb 15 '23 at 15:52

How to make LightGBM to suppress output?

5 Answers5