Code generation error (loadDeepLearningNetwork)
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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..

this is my function

this is deploy function

errors

4 Comments
@Chanhyeok, thank you for reaching out. I dont see any obvious issue with the code causing the error, but you may be able to work around the issue by passing a dummy character array as a second argument for coder.loadDeepLearningNetwork.
for example,
net = coder.loadDeepLearningNetwork('dataset800.mat', 'my_dummy_name');
Regarding your inquiry concerning AMD and NVIDIA GPUs, if your target is the Raspberry Pi or any other CPU-based platform, the GPU on the target platform or host is inconsequential.
Chanhyeok
on 10 Jul 2023
Ram Kokku
on 11 Jul 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
Chanhyeok
on 11 Jul 2023
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