WebSep 16, 2024 · Your script might be already hitting OOM issues and would call empty_cache internally. You can check it via torch.cuda.memory_stats (). If you see that OOMs were detected, lower the batch size as suggested. antran96 (antran96) September 19, 2024, 6:33am 5 Yes, seems like decreasing the batch size resolve the issue. WebMar 7, 2024 · Hi, torch.cuda.empty_cache () (EDITED: fixed function name) will release all the GPU memory cache that can be freed. If after calling it, you still have some memory that is used, that means that you have a python variable (either torch Tensor or torch Variable) that reference it, and so it cannot be safely released as you can still access it.
python - How to fix this strange error: "RuntimeError: CUDA error: out o…
WebMay 25, 2024 · Here’s the memory usage without torch.cuda.empty_cache () 1200×600 26.4 KB It doesn’t say much. I also set up memory profiling found in this topic How to debug causes of GPU memory leaks? … WebJan 8, 2024 · torch.ones ( (d, d)).cuda () will always allocate a contiguous block of GPU RAM (in the virtual address space) Your allocation x3 = mem_get (1024) likely succeeds because PyTorch cudaFree’s x1 on failure and retries the allocation. (And as you saw, the CUDA driver can re-map pages). PyTorch uses “best-fit” among cached blocks (i.e. … citibank personal loan online payment
How can we release GPU memory cache? - PyTorch Forums
WebApr 29, 2024 · Emptying the cache is already done if you’re about to run out of memory so there is no reason for you to do it by hand unless you have multiple processes using the same GPU and you want this process to free up space for the other process to use it. Which is a very very un-usual thing to do. 3 Likes Phu_Do (Phu Do) May 24, 2024, 10:35am 33 WebApr 10, 2024 · I noticed that the memory is not distributed overall GPUs equally which result then in a CUDA out of memory message because GPU0 is full even though the rest has still capacities. The error messages look similar to this: torch.cuda.OutOfMemoryError: CUDA out of memory. WebAug 14, 2024 · These 500MB are most likely just the memory used by the CUDA initialization. So there is not way to remove it unless you kill the process. It seems that the model is only stored in your first process 34296 and the others are using it as expected but just the cuda initialization state is taking a lot of memory citibank personal loan review nerdwallet