Code generation error (loadDeepLearningNetwork)
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Chanhyeok
el 9 de Jul. de 2023
Comentada: wtg Wtg
el 4 de Dic. de 2024
I saw the example and followed.
However, I would like to replace my newly created resnet50 neural network, not the pre-trained resnet50 neural network provided by Matlab. I actually made it, and it works well on the Matlb. However, when deploying to Raspberry Pi, loadDeeplelearningnetwork function keeps failing. What's the cause?
Does it matter if my gpu is AMD? Matlab coder is NVIDIA compatible..
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this is my function
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this is deploy function
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errors
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4 comentarios
Ram Kokku
el 11 de Jul. de 2023
@Chanhyeok, The coders will use the second argument as the recommended name for the C++ class generated for the deep learning network. you can give a simple dummy character array, preferable a single word - for example, 'MyDLClass' or 'my_dummy_string'.
you can find more about this argument here : https://www.mathworks.com/help/gpucoder/ref/coder.loaddeeplearningnetwork.html#d124e9416
Respuesta aceptada
Sayan Saha
el 11 de Jul. de 2023
Editada: Sayan Saha
el 11 de Jul. de 2023
Hello @Chanhyeok, are you trying to codegen in a folder that has non-ASCII characters in it's path? If so, can you change to a directory that has only ASCII characters in it's full-path and see if that resolves the issue. Note that codegen is not currently supported for non-ASCII characters https://www.mathworks.com/help/coder/ug/code-generation-for-characters.html.
1 comentario
wtg Wtg
el 4 de Dic. de 2024
I run gpu checks on r2024a/b over Nvidia RTX4080 Laptop with all combinations of VS2017/2019/2022 + Cuda11.8-12.2/cuDNN8.7-9.2/TensorRT8.5.1.7-8.6.1.6, and always got the deepcodegen & deepcodeexec fails as below :
>>gpuEnvObj = coder.gpuEnvConfig('host');
gpuEnvObj.BasicCodegen = 1;
gpuEnvObj.BasicCodeexec = 1;
gpuEnvObj.DeepLibTarget = 'cudnn';
gpuEnvObj.DeepCodegen = 1;
gpuEnvObj.DeepCodeexec = 1;
results = coder.checkGpuInstall(gpuEnvObj)
Compatible GPU : PASSED
CUDA Environment : PASSED
Runtime : PASSED
cuFFT : PASSED
cuSOLVER : PASSED
cuBLAS : PASSED
cuDNN Environment : PASSED
Host Compiler : PASSED
Basic Code Generation : PASSED
Basic Code Execution : PASSED
Deep Learning (cuDNN) Code Generation: FAILED (GPU code generation failed with an error. View report for further information: View report)
results =
struct with fields:
gpu: 1
cuda: 1
cudnn: 1
tensorrt: 0
hostcompiler: 1
basiccodegen: 1
basiccodeexec: 1
deepcodegen: 0
tensorrtdatatype: 0
deepcodeexec: 0
The Error Report always shows as below :
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Could you help ?
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