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)

6 views (last 30 days)
john karli
john karli on 24 Nov 2021
Commented: yanqi liu on 25 Nov 2021
I want to train the model in .mat dataset but i am getting the memory error my dataset size is [256,340,2] when i try
gpuDevice(1)
ans =
CUDADevice with properties:
Name: 'NVIDIA GeForce GTX 1080 Ti'
Index: 1
ComputeCapability: '6.1'
SupportsDouble: 1
DriverVersion: 11.4000
ToolkitVersion: 11
MaxThreadsPerBlock: 1024
MaxShmemPerBlock: 49152
MaxThreadBlockSize: [1024 1024 64]
MaxGridSize: [2.1475e+09 65535 65535]
SIMDWidth: 32
TotalMemory: 1.1811e+10
AvailableMemory: 1.0615e+10
MultiprocessorCount: 28
ClockRateKHz: 1620000
ComputeMode: 'Default'
GPUOverlapsTransfers: 1
KernelExecutionTimeout: 1
CanMapHostMemory: 1
DeviceSupported: 1
DeviceAvailable: 1
DeviceSelected: 1
code is
location = 'D:\data-11\sir task\dataset\';
imds = imageDatastore(location, 'FileExtensions', '.mat', 'IncludeSubfolders',1, ...
'LabelSource','foldernames',...
'ReadFcn',@matReader);
[imdsTrain,imdsValidation] = splitEachLabel(imds,0.7, 'randomized');
net = lgraph_1;
inputSize = lgraph_1.Layers(1).InputSize;
[learnableLayer,classLayer] = findLayersToReplace(lgraph_1);
[learnableLayer,classLayer]
numClasses = numel(categories(imdsTrain.Labels));
if isa(learnableLayer,'nnet.cnn.layer.FullyConnectedLayer')
newLearnableLayer = fullyConnectedLayer(numClasses, ...
'Name','new_fc', ...
'WeightLearnRateFactor',10, ...
'BiasLearnRateFactor',10);
elseif isa(learnableLayer,'nnet.cnn.layer.Convolution2DLayer')
newLearnableLayer = convolution2dLayer(1,numClasses, ...
'Name','new_conv', ...
'WeightLearnRateFactor',10, ...
'BiasLearnRateFactor',10);
end
lgraph_1 = replaceLayer(lgraph_1,learnableLayer.Name,newLearnableLayer);
newClassLayer = classificationLayer('Name','new_classoutput');
lgraph_1 = replaceLayer(lgraph_1,classLayer.Name,newClassLayer);
miniBatchSize = 128;
valFrequency = floor(numel(imdsTrain.Files)/miniBatchSize);
checkpointPath = pwd;
options = trainingOptions('sgdm', ...
'MiniBatchSize',miniBatchSize, ...
'MaxEpochs',100, ...
'InitialLearnRate',1e-3, ...
'Shuffle','every-epoch', ...
'ValidationData',imdsValidation, ...
'ValidationFrequency',valFrequency, ...
'Verbose',false, ...
'Plots','training-progress', ...
'CheckpointPath',checkpointPath);
net = trainNetwork(imdsTrain,lgraph_1,options);
I have also tried to change the batch size to 8 but it does't work.

Answers (1)

yanqi liu
yanqi liu on 25 Nov 2021
sir,may be use
miniBatchSize = 128;
to
miniBatchSize = 1;
  4 Comments

Sign in to comment.

Categories

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!