hdjsjyl commented on issue #11980: new rcnn code, gpu memory is increasing and gpu utility is very low, what is the reason? URL: https://github.com/apache/incubator-mxnet/issues/11980#issuecomment-410073662 Thanks for your complete explanation. I am using Faster-RCNN to do face detection. I need to add some tricks and change the network structure. So if the basic Faster-RCNN occupies much memory, it is not good for me. So I think the old one is more suitable for me. But the new Faster-RCNN code is easier to read and modify. Thanks for your excellent work. On Thu, Aug 2, 2018 at 2:25 PM, Jian Guo <[email protected]> wrote: > Occupy more memory (initially): because the maximum reserved shape changed > from (1, 3, 600, 1000) to (1, 3, 1000, 1000). > > Keeps increasing: because MutableModule is replaced by Module which > supports varying input shape. The behavior of Module is to allocate more > and more memory until we can't, but it is safe. MutableModule shared the > initially reserved memory, hence not increasing. > > Lower GPU utilization: because all Cython speedup is removed. > > Changing to the new version makes the example much easier to setup, to use > or to maintain with the price of slower speed. However, research > implementations based on the original example is available elsewhere, for > example https://github.com/msracver/Deformable-ConvNets. For a historical > mind, the old version is available at https://github.com/ijkguo/mx- > rcnn/tree/v5.1. > > — > You are receiving this because you authored the thread. > Reply to this email directly, view it on GitHub > <https://github.com/apache/incubator-mxnet/issues/11980#issuecomment-410039815>, > or mute the thread > <https://github.com/notifications/unsubscribe-auth/AHPQ-64j9naSiy3-LBvKQCmziLVH_ptEks5uM1IkgaJpZM4VrVLs> > . > -- Best wishes! Lei Shi
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