Check passing initialized modules

[kulbachcedric]

This issue proposes changes to enhance flexibility in handling PyTorch modules by allowing initialized modules to be passed to the base classes. This could help streamline workflows where pre-initialized or pre-trained models are frequently used.

Current Implementation

The current Regressor and similar classes require a module type (Type[torch.nn.Module]) to instantiate a model internally. This design works well for simple use cases but restricts flexibility when users need to use pre-initialized modules.

Discussion Points

1. Impact on Existing Workflows:
   Will allowing initialized modules complicate initialization for existing users?

2. Documentation Updates:
   How should we structure documentation to highlight this change?

However, with this change we would diverge from skorch.

Best
Cedric

[kulbachcedric]

Hi @hoanganhngo610 , @lucasczz

I worked a little bit on the code, what do you think ?
We could still have all the features, however, all tests need to be refactored ...

Best
Cedric

[lucasczz]

Hi @kulbachcedric,
That looks good 👍
I think it's a good idea to allow already initialized modules for. Makes it easier if you want to set some model hyperparameters before passing the module to DeepRiver.