Timeline for Using Mathematica wlnet model in C++
Current License: CC BY-SA 3.0
12 events
| when toggle format | what | by | license | comment | |
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| Nov 3, 2017 at 11:05 | comment | added | Taliesin Beynon | @yode we don't have any material for that yet, but we hope to have some workflows and tutorials soon that will show how to do it with a worked example. | |
| Oct 9, 2017 at 9:28 | comment | added | yode |
@Taliesin Beynon Since 11.2 has released, could you post a example about How to use the .json and .param file in c++?
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| Sep 15, 2017 at 8:48 | comment | added | yode | @partida Could you give a exmaple how to use the model produced by MMA in C++? | |
| Sep 10, 2017 at 0:40 | comment | added | partida | mathematica.stackexchange.com/questions/155069/… some time it can't using wolfram model in MXNet | |
| Sep 10, 2017 at 0:32 | comment | added | partida | mxnet has a new interface Gluon,is wolfram support it? | |
| Sep 4, 2017 at 12:03 | comment | added | partida |
@nikie Thannnnks,the example image-classification-predict.cc can run in my VS2015.I will write a answer when I know more.
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| Sep 2, 2017 at 15:37 | comment | added | Niki Estner |
I guess you call MXPredSetInput multiple times, once for each input (same for the outputs)
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| Sep 2, 2017 at 14:51 | comment | added | partida | @nikie If want to use prediction or network have multi-port,how should I do | |
| Sep 2, 2017 at 10:36 | comment | added | partida | @nikie thanks! I try | |
| Sep 2, 2017 at 9:45 | comment | added | Niki Estner | @partida: If you only need predictions, you can use the C predict API. Standalone header file, really easy to use. Here's a sample: github.com/apache/incubator-mxnet/blob/master/example/… | |
| Aug 31, 2017 at 3:20 | comment | added | partida | But install MxNet using C++ interface is very difficult because of it need to be compiled and link library and head file.If only need to make a prediction using MxNet,can you provide some example about it. | |
| Aug 16, 2017 at 13:30 | history | answered | Taliesin Beynon | CC BY-SA 3.0 |