error using nnet.inter​nal.cnn.la​yer.util.f​ullyConnec​tedGPUImag​eStrategy

조회 수: 11 (최근 30일)
红婷 郝
红婷 郝 2020년 7월 2일
disp('Track: network training section begins!')
trainOpt = trainingOptions('adam', ...
'InitialLearnRate',options.learningRate, ...
'LearnRateSchedule','piecewise', ...
'LearnRateDropFactor',options.dropFactor, ...
'LearnRateDropPeriod',options.learnRateSch, ...
'L2Regularization',options.weightDecay, ...
'MaxEpochs',options.maxNumEpochs, ...
'MiniBatchSize',options.batchSize, ...
'Shuffle','every-epoch', ...
'ValidationData',dataPrep.val, ...
'ValidationFrequency',options.valFreq, ...
'ExecutionEnvironment','gpu', ...
'ValidationPatience', 10, ... % Disables automatic training break-off
'Plots','none');
gpuDevice(1)
[trainedNet, trainingInfo] = trainNetwork(dataPrep.train{1,:}, dataPrep.train{2,:}, net, trainOpt);
save([options.netSaveDir,'net_ant=',num2str(options.ch(i)),'_pilot=',num2str(options.pilotSize)], 'trainedNet')
% show NMSE on validation dataset
nanLoc = isnan(trainingInfo.ValidationLoss);
valNMSE = trainingInfo.ValidationLoss(~nanLoc);
options.valNMSE = valNMSE;
R_NMSE(j, i) = options.valNMSE(end);

답변 (0개)

카테고리

Help CenterFile Exchange에서 Deep Learning Toolbox에 대해 자세히 알아보기

태그

Community Treasure Hunt

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

Start Hunting!

Translated by