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Generate Cuda code from a pretrained rlDDPGAgent object for NVIDIA board

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I want to use a pretrained rlDDPGAgent for my NVIDIA Jetson Nano.
With this Agent i want to steer a model car, so the actor net ends with a hyperbolic tangent layer.
Is there a way to use for example the GPU Coder to do the transformation or another suggested possibility?
Due to my account at university i have access to all of the matlab content.
Greetings
Oliver

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Accepted Answer

Emmanouil Tzorakoleftherakis
If you see here, tha tanhLayer support code generation with GPU Coder starting in R2019b.

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Oliver Struck
Oliver Struck on 5 Mar 2020
The site of the doc helped a lot and i implemented the following code lines:
generatePolicyFunction(Car_Agent);
cfg = coder.gpuConfig('mex');
cfg.TargetLang = 'C++';
cfg.DeepLearningConfig = coder.DeepLearningConfig('cudnn');
%% Observationinfo
obsInfo = getObservationInfo(Car_Agent);
argstr = '{ones(obsInfo.Dimension(1),obsInfo.Dimension(2))}';
%% Code-Generation
codegen('-config','cfg','evaluatePolicy','-args',argstr,'-report');
For the compilation i selected the Visual C++ 2019 Compiler.
Then the process started and i received a build error with following failures:
  • build/win64/MWTanhLayerImpl.obj step [1/19]
  • build/win64/MWTanhLayer.obj step [2/19]
  • build/win64/cnn_api.obj step [3/19]
  • build/win64/MWCNNLayerImpl.obj step [5/19]
  • build/win64/predict.obj step [6/19]
  • build/win64/_coder_evaluatePolicy_api.obj step [7/19]
  • build/win64/MWTargetNetworkImpl.obj step [8/19]
  • build/win64/DeepLearningNetwork.obj step [9/19]
  • ninja: build stopped: subcommand failed step [10/19]
If it is necessary i can give you the complete build log.
Emmanouil Tzorakoleftherakis
This page has a list with prerequisites you need to have before generating GPU code. Specifically, you need the GPU Coder interface for Deep Learning libraries and the cudnn/tensorrt libraries installed. The env paths should be properly set up as well. Do you have these installed?
Oliver Struck
Oliver Struck on 6 Mar 2020
Finally i got it! All Matlab content was already installed, and the libraries were added to the CUDA Toolkit file, but i forgot to implement the environment variables and i forgot to add them to my Matlab workaround. After i did this the code generation was succesful. Thanks a lot for the good advices.

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