V2V example encounter OOM in 80G A100.
#25
by guyuchao - opened
I try to run the provided example code, and encounter the OOM error at the first spatial attention. I print the shape and dtype at the OOM position: query: torch.Size([240, 9216, 64]) torch.float16 key: torch.Size([240, 9216, 64]) torch.float16. Have you encounter such problem?
Does it need to run with xformer or some other techniques?
Same problem, apparently needs xformers, but I have no idea how to implement it to the python script.
Same problem, apparently needs xformers, but I have no idea how to implement it to the python script.
Just add pipe.enable_xformers_memory_efficient_attention() and the gpu memory usage will be reduced significantly.
For me, it takes ~20.1GB for rendering 1024x576 at 32 frames.