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Is your feature request related to a problem? Please describe.
Currently, we have an interesting variety of possible back-ends for mathematical processing. However, to minimize the differences and allow a quick transition between them, frameworks like Ivy are growing and allowing users/developers/researchers/etc to implement their models through an agnostic interface and execute them in any back-end they want. This solution would also make PyTorch not a mandatory dependency for the project, and we would be able to install ClayRS along a specific back-end with commands like pip install clayrs[tf] or pip install clayrs[torch] - which also complies with HuggingFace, for instance.
Describe the solution you'd like
Something like this would be interesting if I have more than one backend available:
Is your feature request related to a problem? Please describe.
Currently, we have an interesting variety of possible back-ends for mathematical processing. However, to minimize the differences and allow a quick transition between them, frameworks like Ivy are growing and allowing users/developers/researchers/etc to implement their models through an agnostic interface and execute them in any back-end they want. This solution would also make PyTorch not a mandatory dependency for the project, and we would be able to install ClayRS along a specific back-end with commands like
pip install clayrs[tf]
orpip install clayrs[torch]
- which also complies with HuggingFace, for instance.Describe the solution you'd like
Something like this would be interesting if I have more than one backend available:
If there is only one backend available, use it as default with an info/warning message in the first usage.
Additional context
Filling this issue while attending Marco Polignano's lecture at RecSys Summer School 2023 :)
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