[GitHub] Bumblebee1964 commented on issue #7835: C++ batchnorm CPU version training well, but validation wrong

[GitBox]

Bumblebee1964 commented on issue #7835: C++ batchnorm CPU version training 
well, but validation wrong
URL: 
https://github.com/apache/incubator-mxnet/issues/7835#issuecomment-374851572
 
 
   Hi,
   
   thanks for addressing.
   
   We went on using Python only. As MxNet moved ahead, we will try to use the 
c++ package again later this year. For time being, I have closed the thread.
   
   Regards,
   
   Fred
   
   -- Original Message --
   From: "Anirudh Subramanian" 
>
   To: "apache/incubator-mxnet" 
>
   Cc: "Fred Hugen" >; "Mention" 
>
   Sent: 20/03/2018 23:28:00
   Subject: Re: [apache/incubator-mxnet] C++ batchnorm CPU version training 
well, but validation wrong (#7835)
   
   
   @relaxli00 
@Bumblebee1964 can you provide a minimum 
reproducible example ?
   
   —
   You are receiving this because you were mentioned.
   Reply to this email directly, view it on 
GitHub,
 or mute the 
thread.
   


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[GitHub] Bumblebee1964 commented on issue #7835: C++ batchnorm CPU version training well, but validation wrong

[GitBox]

Bumblebee1964 commented on issue #7835: C++ batchnorm CPU version training 
well, but validation wrong
URL: 
https://github.com/apache/incubator-mxnet/issues/7835#issuecomment-374850940
 
 
   We wnt on using Python only. As MxNet moved ahead, we will try to use the 
c++ package again later this year. For time being, let's close it.


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[GitHub] Bumblebee1964 commented on issue #7835: C++ batchnorm CPU version training well, but validation wrong

[git]

Bumblebee1964 commented on issue #7835: C++ batchnorm CPU version training 
well, but validation wrong
URL: 
https://github.com/apache/incubator-mxnet/issues/7835#issuecomment-330607688
 
 
   Having same problem. Noticed that the Mathematica version 11.2 (using MxNet 
under the hood) is not able to reproduce my earlier modified InceptionV3 
network tested in version 10. Also the my c++/windows MxNetwork seem to have 
this decreasing loss but almost equal loss validation rates.
 

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