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@DanFu09 Thanks for open-sourcing the code!
I see that in your previous fly repo(https://github.com/HazyResearch/fly), you used cast_inputs=torch.float16 for BlockdiagButterflyMultiply, but changed it to bf16 here. I wonder if there's a specific reason (e.g. fp16 training not converging due to range issues)?
Also, I wonder if there are opportunities for fusing the two bmm operations into one kernel? It seems hard to find the exact kernel torch is calling though.
The text was updated successfully, but these errors were encountered:
Edenzzzz
changed the title
torch.bmm kernel fusion and precision casting issue in BlockdiagButterflyMultiply
torch.bmm kernel fusion
May 13, 2024
@DanFu09 Thanks for open-sourcing the code!
I see that in your previous fly repo(https://github.com/HazyResearch/fly), you used cast_inputs=torch.float16 for BlockdiagButterflyMultiply, but changed it to bf16 here. I wonder if there's a specific reason (e.g. fp16 training not converging due to range issues)?
Also, I wonder if there are opportunities for fusing the two bmm operations into one kernel? It seems hard to find the exact kernel torch is calling though.
The text was updated successfully, but these errors were encountered: