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With PEP 703 being accepted and implementation of it underway python/cpython#108219 I think it would be great to prepare the Monai transforms early for execution on multiple threads. Especially with the large tensor sizes and the advantages of running transforms on GPU, I'm hoping for free-threading to have a big benefit in (3D) medical imaging AI.
I think the biggest issue here would be the Randomizable transforms, which currently can't be executed inside a threaded environment.
AFAIK, the free-threading is pushed by Meta, and I'm therefore expecting pytorch to be compatible with it relatively early, since one of the talks on no-gil python talked about testing it with a pytorch DL project internally at Meta.
This might be a great opportunity to work on #6854 as well, which might eventually require breaking changes in the Randomizable API as well.
The text was updated successfully, but these errors were encountered:
johnzielke
changed the title
Make Monai (Random) Transform work in a multi-threaded environment
Make Monai (Random) Transforms work in a multi-threaded environment
Mar 27, 2024
With PEP 703 being accepted and implementation of it underway python/cpython#108219 I think it would be great to prepare the Monai transforms early for execution on multiple threads. Especially with the large tensor sizes and the advantages of running transforms on GPU, I'm hoping for free-threading to have a big benefit in (3D) medical imaging AI.
I think the biggest issue here would be the Randomizable transforms, which currently can't be executed inside a threaded environment.
AFAIK, the free-threading is pushed by Meta, and I'm therefore expecting pytorch to be compatible with it relatively early, since one of the talks on no-gil python talked about testing it with a pytorch DL project internally at Meta.
This might be a great opportunity to work on #6854 as well, which might eventually require breaking changes in the Randomizable API as well.
The text was updated successfully, but these errors were encountered: