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How can I use the example Transfer Learning Using Alexnet with Vgg16?

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Claudio Mor
Claudio Mor on 12 Nov 2018
Answered: xu lu on 4 Jan 2019
I tried to use 'Transfer Learning Using AlexNet' with Vgg16 but it failed to start the Training iterations. How can I use this example with Vgg16?
[netTransfer, info] = trainNetwork(augimdsTrain,layers,options);
Error using trainNetwork (line 150) GPU out of memory. Try reducing 'MiniBatchSize' using the trainingOptions function.
*Error in TL_CM_V3_Test_IM_VGG16 (line 68) [netTransfer, info] = trainNetwork(augimdsTrain,layers,options);
Caused by: Error using .* Out of memory on device. To view more detail about available memory on the GPU, use 'gpuDevice()'. If the problem persists, reset the GPU by calling 'gpuDevice(1)'.*
My gpu is CUDADevice with properties:
Name: 'GeForce 930MX'
Index: 1
ComputeCapability: '5.0'

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Accepted Answer

Johannes Bergstrom
Johannes Bergstrom on 12 Nov 2018
Vgg16 requires a lot of GPU memory and you don't have very much of it. The error message says "Try reducing 'MiniBatchSize' using the trainingOptions function." Did you try that? Otherwise, I would recommend using a network that uses less memory, for example, GoogLeNet or SqueezeNet.
You can use any pretriained network available in MATLAB for transfer learning in this example: https://www.mathworks.com/help/deeplearning/examples/train-deep-learning-network-to-classify-new-images.html
For a list of pretrained networks, see https://www.mathworks.com/help/deeplearning/ug/pretrained-convolutional-neural-networks.html

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Claudio Mor
Claudio Mor on 12 Nov 2018
Thank you! I tried setting the minimum 'MiniBatchSize'=1 but without success. Unfortunately, I need to use Vgg16 or a custom (shallower) miniVgg for my project; I'm going to use a Nvidia Gtx1080 8Gb, can this be enough?

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More Answers (1)

xu lu
xu lu on 4 Jan 2019
I have tried many times but failed to install Vgg16 successfully. The installation always stops when the download reaches 18%.Can you help me?

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