I find that minibatchqueue has a 'name,value' pair which is outputCast, 'single' as default. So I assign 'double' to it. But I haven't checked if the GPU training process does use single precision, as mentioned by @Walter Roberson.
minibatchqueue or arrayDatastore drops my data precision from double to single
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I get XTrain from MNIST by processImagesMNIST and put it on GPU, so its type is gpuArray dlarray.
then I use these code to make minibatches:
```
miniBatchSize = 128;
dsTrain = arrayDatastore(XTrain,IterationDimension=4);
% numOutputs = 1;
mbqTest = minibatchqueue(dsTrain,1, ...
MiniBatchSize = miniBatchSize, ...
MiniBatchFcn=@preprocessMiniBatch, ...
MiniBatchFormat="SSCB", ...
PartialMiniBatch="discard");
% numObservationsTrain = size(XTrain,4);
% numIterationsPerEpoch = ceil(numObservationsTrain / miniBatchSize);
% numIterations = numEpochs * numIterationsPerEpoch;
%% test batch order
i=0;
while hasdata(mbqTest)
i = i+1;
x = next(mbqTest);
if ~hasdata(mbqTest)
disp(i)
end
end
```
And I find that x is single gpuArray dlarray, XTrain is gpuArray dlarray.
I wonder which part makes it lower the precision.
And how to avoid this?
답변 (1개)
Walter Roberson
2022년 9월 28일
Gpu training does not support double precision. If you look at the available options, precision cannot be selected.
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