ConvergenceWarnings cannot be turned off

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):

```py
from sklearn.covariance import GraphicalLassoCV
import warnings
warnings.filterwarnings("ignore", category=ConvergenceWarning)

model = GraphicalLassoCV(n_jobs=4)
model = model.fit(data)
```

```py
from sklearn.covariance import GraphicalLassoCV
import warnings
warnings.filterwarnings(action='ignore')

model = GraphicalLassoCV(n_jobs=4)
model = model.fit(data)
```

```py
import warnings
with warnings.catch_warnings():
    warnings.simplefilter("ignore", ConvergenceWarning)

    model = GraphicalLassoCV(n_jobs=4)
    model = model.fit(data)
```

```py
from sklearn.covariance import GraphicalLassoCV
def warn(*args, **kwargs):
    pass
import warnings
warnings.warn = warn

model = GraphicalLassoCV(n_jobs=4)
model = model.fit(data)
```

```py
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)
```

```py
import logging
logging.captureWarnings(True)

logging.getLogger("py.warnings").setLevel(logging.ERROR)

model = GraphicalLassoCV(n_jobs=4)
model = model.fit(data)
```

COMMENT:
Ran into this issue as well. Dropping a reproducible example:

```python
import warnings
import numpy as np
import pandas as pd
from sklearn.exceptions import ConvergenceWarning
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import RandomizedSearchCV

warnings.filterwarnings("ignore", category=ConvergenceWarning)

X_train = pd.DataFrame(
    data={
        "a": np.linspace(0, 1, 100),
        "b": 1 + np.linspace(0, 1, 100),
        "c": np.repeat([1, 0], 50),
    }
)

y_train = np.repeat([np.repeat(1, 5), np.repeat(0, 5)], 10)

lr = LogisticRegression(
    penalty="elasticnet",
    l1_ratio=0.5,
    solver="saga",
    max_iter=10,
    random_state=103,
)

log_reg_params = {
    "tol": (1e-3, 5e-2, 1e-2),
    "C": np.linspace(0.01, 0.8, 5),
}


random_search = RandomizedSearchCV(
    estimator=lr,
    param_distributions=log_reg_params,
    cv=5,
    random_state=104,
    n_jobs=-1, # IF N_JOBS IS 1, THEN NO WARNING
)

random_search.fit(X_train, y_train)
```

output repeated: `[/Users/~/.venv/lib/python3.12/site-packages/sklearn/linear_model/_sag.py:349](https://file+.vscode-resource.vscode-cdn.net/Users/~/.venv/lib/python3.12/site-packages/sklearn/linear_model/_sag.py:349):ConvergenceWarning: The max_iter was reached which means the coef_ did not converge
  warnings.warn(`

Machine info
```
Operating System: Darwin
OS Version: Darwin Kernel Version 20.6.0: Thu Jul  6 22:12:47 PDT 2023; root:xnu-7195.141.49.702.12~1/RELEASE_X86_64
Machine Architecture: x86_64
Python Version: 3.12.6
Number of CPU Cores: 4

Scikit-learn and dependencies info:

System:
    python: 3.12.6 (v3.12.6:a4a2d2b0d85, Sep  6 2024, 16:08:03) [Clang 13.0.0 (clang-1300.0.29.30)]
executable: [/Users/~/.venv/bin/python](https://file+.vscode-resource.vscode-cdn.net/Users/~/.venv/bin/python)
   machine: macOS-11.7.10-x86_64-i386-64bit

Python dependencies:
      sklearn: 1.5.2
          pip: 24.2
   setuptools: None
        numpy: 2.1.2
        scipy: 1.14.1
       Cython: None
       pandas: 2.2.3
   matplotlib: 3.9.2
       joblib: 1.4.2
threadpoolctl: 3.5.0
```

Labels: Moderate, help wanted