Closed CuberrChen closed 3 years ago
This error is caused by our own implementation of MaxPool2d. It seems you are using max pooling with a large kernel size. Currently, our kernel implementation does not support this case. You can disable our quantized max-pooling layers by deleting these lines https://github.com/ucbrise/actnn/blob/aa4f43cce6631f53c3ed965b34b6de66bfe04c0a/actnn/actnn/module.py#L67-L72 But the memory usage will be higher.
We use our own implementation of MaxPool2d because we found the default one in PyTorch is not memory efficient. If you know how to write CUDA kernel, you can try to extend our code to support larger kernel sizes.
Thank you very much for your detailed answer!
when i did't apply the actnn, there is no the issue. so I dont donw if there is a limitation of the kernel size if i want to use actnn?