I want to log some python code which loads in a trained keras model. For some reason, (python) logging doesn't not work if the keras `load_model` is imported. But (python) logging works fine if I don't import keras.

This works:

```
import logging

LOG_FORMAT = "%(levelname)s %(asctime)s - %(message)s"
logging.basicConfig(filename="logs/my_logs.log",
                    level=logging.DEBUG,
                    format=LOG_FORMAT)
logger = logging.getLogger()

def do_stuff():
    logging.info("About to do stuff")
    ... stuff gets done here...

```

This doesn't work

```
import logging
from keras.models import load_model

my_model = load_model("fetch_preprocess/lstm_model.h5")

LOG_FORMAT = "%(levelname)s %(asctime)s - %(message)s"
logging.basicConfig(filename="logs/my_logs.log",
                    level=logging.DEBUG,
                    format=LOG_FORMAT)
logger = logging.getLogger()

def do_stuff():
    logging.info("About to do stuff")
    pred = my_model.predict(data)
    ... stuff gets done here...

```

By "doesn't work", I mean the `logging` module doesn't

* create a new log file
* write to that file anytime `logging` is called

but no error's are ever thrown. So I find this strange.

I believe Keras / tensorflow is interfering with the logging (as the only change I make to the code is to exclude Keras and then logging works fine).

Is there some way to suppress whatever keras is doing in the background so I can use the python logging?