ConvergenceWarnings cannot be turned off #29294
Description
Hi, I'm unable to turn off convergence warnings from GraphicalLassoCV.
I've tried most of the solutions from, and none of them worked (see below for actual implementations):
https://stackoverflow.com/questions/879173/how-to-ignore-deprecation-warnings-in-python
https://stackoverflow.com/questions/32612180/eliminating-warnings-from-scikit-learn/33812427#33812427
https://stackoverflow.com/questions/53968004/how-to-silence-all-sklearn-warning
https://stackoverflow.com/questions/14463277/how-to-disable-python-warnings
Contrary to what the designers of the sklearn's exceptions must have thought when it was implemented, some of us actually use stdout to log important information of the host program for diagnostics purposes. Flooding it with garbage that cannot be turned off, as is in the case with cross-validation, is not ok.
To briefly speak to the severity of the issue, the above sklearn-specific questions relating to suppressing warnings have been viewed ~500K times with combined ~400 upvotes, and dates back 7 years.
I've tried the following (n_jobs parameter does not appear to affect the result):
from sklearn.covariance import GraphicalLassoCV
import warnings
warnings.filterwarnings("ignore", category=ConvergenceWarning)
model = GraphicalLassoCV(n_jobs=4)
model = model.fit(data)from sklearn.covariance import GraphicalLassoCV
import warnings
warnings.filterwarnings(action='ignore')
model = GraphicalLassoCV(n_jobs=4)
model = model.fit(data)import warnings
with warnings.catch_warnings():
warnings.simplefilter("ignore", ConvergenceWarning)
model = GraphicalLassoCV(n_jobs=4)
model = model.fit(data)from sklearn.covariance import GraphicalLassoCV
def warn(*args, **kwargs):
pass
import warnings
warnings.warn = warn
model = GraphicalLassoCV(n_jobs=4)
model = model.fit(data)import contextlib
import os, sys
@contextlib.contextmanager
def suppress_stdout():
with open(os.devnull, 'w') as fnull:
old_stdout = sys.stdout
sys.stdout = fnull
try:
yield
finally:
sys.stdout = old_stdout
with suppress_stdout():
model = GraphicalLassoCV(n_jobs=4)
model = model.fit(data)import logging
logging.captureWarnings(True)
logging.getLogger("py.warnings").setLevel(logging.ERROR)
model = GraphicalLassoCV(n_jobs=4)
model = model.fit(data)