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About speed #9

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jianan86 opened this issue Aug 4, 2017 · 6 comments
Open

About speed #9

jianan86 opened this issue Aug 4, 2017 · 6 comments

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@jianan86
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jianan86 commented Aug 4, 2017

Hi,
thanks for your work.
when I test and train the net, it seems more slowly than alexNet or caffeNet under the same configuration, is this normal? What was your result? thanks!

@farmingyard
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@jianan86
I haven't trained alexnet or caffenet, so I can't compare their speed with shufflenet, but i can give you the shufflenet's training speed on my card: GTX1080, shufflenet_1x_g3_deploy.prototxt, batchsize=64, 40 iters, cost time is about 16 seconds.

@jianan86
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@farmingyard
I will do more tests, thanks again.

@CLAPoo
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CLAPoo commented Aug 23, 2017

@farmingyard
Here is my test for shufflenet with caffe_time (TITAN xp)
Average Forward pass: 9.85734 ms.
Average Backward pass: 9.51034 ms.
And the test for mobilenet you recommended (from https://github.com/farmingyard/caffe-mobilenet )
Average Forward pass: 5.08076 ms.
Average Backward pass: 7.28298 ms.
But as the paper says that Shufflenet performs better. Did you test it before? or any suggestion. Thank you a lot.

@lvboodvl
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lvboodvl commented Sep 7, 2017

@farmingyard @MrAprils
I met the same problem as MrAprils
Here is my test for shufflenet with caffe_time(GTX1080)
Average Forward pass: 8.30279 ms.
Average Backward pass: 9.11459 ms.
Average Forward-Backward: 17.7004 ms.
mobilenet:
Average Forward pass: 6.63855 ms.
Average Backward pass: 15.8861 ms.
Average Forward-Backward: 22.6294 ms.
mobilenet seems to perform better,i don't know why? thank you!

@xiaomr
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xiaomr commented Sep 14, 2017

@farmingyard @jianan86 hello ,have you figure out why shuffle net test slower than mobile_net_1by2 and alexnet ? I use Tesla M40, and batch size 1, the average forward time is shuffle net(13ms), mobile_net_1by2 (7ms), alexnet(3.7ms), any suggestion to improve the implementation speed ?

@Ai-is-light
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@jianan86 @farmingyard @MrAprils @lvboodvl @ @ @xiaomr Did you log the time of the following two model. One is the time of original framework,like VGG(caffe time and caffe train/test time).The another one is the the shuffleNet-VGG's framework,I mean that you only change the convolutions operation's format from the original VGG to the ShuffleNet-convolutions operation's format. Any information is welcome

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