Open connormeaton opened 3 years ago
I've encountered same issue even though I have 8 gpus, with 11178MiB per gpu
RuntimeError: CUDA out of memory. Tried to allocate 20.00 MiB (GPU 0; 10.92 GiB total capacity; 10.11 GiB already allocated; 7.38 MiB free; 10.12 GiB reserved in total by PyTorch)
I am also facing same issue , I have 4 gpus with same free available memory
Thanks for providing your great code. I have ran the wav2vec emotion classification of greek audio and it works great. However, I keep running into memory errors when changing the dataset.
I am trying to do emotion classification on the IEMOCAP dataset (https://sail.usc.edu/iemocap/), but it breaks due to running out of memory. I am changing nothing in your code except for the dataset (which fits into your pipeline well).
I made an SO post describing my issues. Do you have any ideas? I am trying to run a p2.8xlarge instance with 100 GiB mounted, so I can't imagine I don't have enough compute.
SO post: https://stackoverflow.com/questions/68624392/running-out-of-memory-with-pytorch
Thanks!