'use_multiprocessing=True' in Mask RCNN with Keras 2.x & Tensorflow 2.x

Question

I am using Keras 2.9.0 and Tensorflow 2.9.2 and already managed to make the necessary changes to compile the Mask-RCNN model (there are many compatability issues as it is a 2017 model).
The code is running on Colab with GPU.

I get now the following warning:

WARNING:tensorflow:Using a generator with `use_multiprocessing=True` and multiple workers may duplicate your data. Please consider using the `keras.utils.Sequence` class.

This comes from the following lines in the model.py file:

        self.keras_model.fit(
            train_generator,
            initial_epoch=self.epoch,
            epochs=epochs,
            steps_per_epoch=self.config.STEPS_PER_EPOCH,
            callbacks=callbacks,
            validation_data=val_generator,
            validation_steps=self.config.VALIDATION_STEPS,
            max_queue_size=100,
            workers=workers,
            use_multiprocessing=True,
        )

The problem is that the training is stuck at Epoch 1/XXX before even starting to really train.
I am pretty sure this is due tot he multiprocessing warning (from other threads here).
this thread is referring here but its a very different approach to generating the data than in Mask RCNN and therefore I'd like to avoid making such a big change (potentially will create many other issues).

Moreover, if I set use_multiprocessing=False (default) there is the following error:

RuntimeError: Your generator is NOT thread-safe.Keras requires a thread-safe generator when use_multiprocessing=False, workers > 1

as far as I understand, the solutions suggested here are not directly the mask-rcnn model.

Question: is there a way to resolve the issue with Mask-RCNN? preferably keep the option to run with multiprocessing (to be faster) ?

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EDIT:
even if I reduce the original amount of workers (12) to 1 (as hinted in the warning message), the model is still stuck at the same stage.