Warnings cannot be ignored

[jaydu1]

When running
statsmodels.discrete.discrete_model.NegativeBinomial(...).fit_regularized(...), I encountered a warning from

statsmodels/statsmodels/base/l1_solvers_common.py

Lines 70 to 71 in 192670b

	import warnings
	warnings.warn(message, ConvergenceWarning)

Even though the results from model.summary look ok, the warning cannot be turned off and ignored with warnings.filterwarnings('ignore').
Below is the code that reproduces the problem:

import statsmodels as stats
import statsmodels.api as sm
import numpy as np
import warnings
with warnings.catch_warnings():
    warnings.filterwarnings("ignore")
    np.random.seed(0)
    Y = np.random.negative_binomial(1, 0.5, size=(100, ))
    
    X = np.random.normal( size=(100, 5))

    mod = stats.discrete.discrete_model.NegativeBinomial(Y, X).fit_regularized(
        method='l1', alpha=1e-12, trim_mode='off',
        method_kwargs={'warn_convergence': False}, qc_verbose=False, disp=False)

Thanks

[josef-pkt]

Thanks, confirmed, (it's not notebook specific)
There is a hardcoded

        with warnings.catch_warnings():
                warnings.simplefilter("always")

but strange part is that it is when computing start_params, not in the main fit.
When I provide start_params in the example, then the warning does not show up.

my guess is that this was supposed to set "ignore" instead of "always" to suppress problems in start_params computation.

The same pattern shows up in many/all fit_regualrized in discrete_models
GenericZeroInflated fit_regularized does not do anything with warnings.
_get_start_params for regular fit in ZI subclasses uses "ignore": warnings.simplefilter("ignore", category=ConvergenceWarning)