Mohammed Innat

@muellerdo Hi, could you please transfer this ticket to the discussion tab? I think it suits there more.

@muellerdo Hi. Could you please move this issue to the discussion section? I think it better suits there.

How about running it on TPU (v4 or v5)?

Any update on this feature request (made in 2019)? Please transform this ticket to https://github.com/tensorflow/tensorflow cc. @cantonios

@younesbelkada @sgugger Does this fix (moving label/logit to same device) supposed to work (model parallelism) for all models (listed above)? Or, a crucial step toward it? Also, this design fix...

> I think it is supposed to work for all models listed above, as long as you are loading your model with device_map=xxx I tried with such fix here https://github.com/huggingface/transformers/pull/22591#issuecomment-1498013324...

@sgugger As the goal of this ticket is to enable model parallelism with easy fix, have the merged PR(s) checked on multi-gpu? I couldn't find any test script here https://github.com/huggingface/transformers/pull/22663/...

@markub3327 Could you please test your implementation with this https://github.com/keras-team/tf-keras/issues/251 ? (As this implementation is quite similar to tfa.f1 score.)

You can still try with mirror or single strategy scope. Or, use kaggle env, it provides multi gpu for free and tf 2.11.

@fcossio It's a great paper. To have this in keras cv, I think we need to first add basic UNet. No semantic segmentation model is added until now. You can...