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)

5 ビュー (過去 30 日間)
john karli
john karli 2021 年 11 月 24 日
コメント済み: yanqi liu 2021 年 11 月 25 日
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.

回答 (1 件)

yanqi liu
yanqi liu 2021 年 11 月 25 日
sir,may be use
miniBatchSize = 128;
to
miniBatchSize = 1;
  4 件のコメント
yanqi liu
yanqi liu 2021 年 11 月 25 日
yes,sir,may be the gpu memory not enough,so use cpu to test

サインインしてコメントする。

カテゴリ

Community Treasure Hunt

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

Start Hunting!

Translated by