Pytorch train network with gpu memory free problems

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I use pytorch train network with same batch size 32. But network input size were different, such as 320x320, 416x416, 512x512. I use command “nvidia-smi -l” to watch gpu memory occupation. Gpu memory was
cost with max input size 512x512, and never reduced when input size was 320x320 or 416x416. How to release the unused memory cache?

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Hi,

We use a special caching allocator that is much faster than the regular allocator. If you don’t need that memory, I would advise against clearing the cache. If you really need that memory, you can use cuda.empty_cache() to release it.

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