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Change default gpu metric backend (pytorch#2501)
Summary: The current GPU memory metric backend includes dcgm and nvml. They are reported from hardware and should be accurate. This PR adds the native torch way to collect GPU memory usage. It uses `torch.cuda.max_memory_allocated()`. The benefit is that it has lower overhead and is accurate on a shared GPU server when there are mutliple GPU processes from other users. It is because we don't implement the process filter for the other two backends. Use `--metrics-gpu-backend torch` to set the backend. Pull Request resolved: pytorch#2501 Reviewed By: xuzhao9 Differential Revision: D64253410 Pulled By: FindHao fbshipit-source-id: 09b0579846a6830e0e9735e8daeba4abd88bab17
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