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

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红婷 郝
红婷 郝 2020-7-2
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);

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