I have a problem about " out of memory" for running VGG16 for image classification

Hello Andrea and ioannisbaptista.

I have a problem when I am training the program for image classification. The error message is "out of memory". My GPU specification bellow.

Name: 'GeForce GTX 1650'

Index: 1

ComputeCapability: '7.5'

SupportsDouble: 1

DriverVersion: 11.1000

ToolkitVersion: 11

MaxThreadsPerBlock: 1024

MaxShmemPerBlock: 49152

MaxThreadBlockSize: [1024 1024 64]

MaxGridSize: [2.1475e+09 65535 65535]

SIMDWidth: 32

TotalMemory: 4.2950e+09

AvailableMemory: 3.3381e+09

MultiprocessorCount: 14

ClockRateKHz: 1710000

ComputeMode: 'Default'

GPUOverlapsTransfers: 1

KernelExecutionTimeout: 1

CanMapHostMemory: 1

DeviceSupported: 1

DeviceAvailable: 1

DeviceSelected: 1

I try to training for alexnet, it's not problem. When I training for VGG16, the problem occured as "out of memory".

This part is where the error occurs. I am set teh minibatch size=5. epoch =10. Amount of pictures are 300 only.

featuresTrain = activations(netTransfer,augimdsTrain,layer,'OutputAs','rows');

I need your help.

I still have to train also the Resnet 110 and iceptionV3 architecture. I need the help of both of you. God bless all fo you.

Answer 1

[Joss Knight]

It doesn't look as though you're setting the MiniBatchSize on the call to activations which means it's using the default value of 128 - no doubt this is too high for your GPU. Make sure you set this property: https://uk.mathworks.com/help/deeplearning/ref/seriesnetwork.activations.html#mw_366511e3-c444-4c5d-baad-e7c016a559fd