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memory_efficient_attention
: torch.compile
compatibility
#920
Comments
Hi, |
Ah, okay, thanks! Is there an issue that tracks this that we could follow? We'd love to support torch.compile+xformers attention in our repo. |
torch.compile
torch.compile
memory_efficient_attention
: torch.compile
compatibility
We can use this issue to track. However this particular error might be related to FSDP ... |
🐛 Bug
Using xformers.memory_efficient_attention with FSDP and torch.compile fails when using bfloat16, but works when using float32. It's unclear to me if this is an xformers bug, an FSDP bug, or a torch.compile bug. It might be related to pytorch/pytorch#112164, and it came up in our codebase where we use xformers: mlfoundations/open_lm#72
Command
torchrun --nproc_per_node 2 script.py
To Reproduce
Steps to reproduce the behavior:
torchrun --nproc_per_node 2 script.py
Expected behavior
Code runs without error.
Environment
Please copy and paste the output from the
environment collection script from PyTorch
(or fill out the checklist below manually).
You can run the script with:
# For security purposes, please check the contents of collect_env.py before running it. python -m torch.utils.collect_env
Additional context
xformers version: 0.0.22.
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