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", ...
% numObservationsTrain = size(XTrain,4);
% numIterationsPerEpoch = ceil(numObservationsTrain / miniBatchSize);
% numIterations = numEpochs * numIterationsPerEpoch;
%% test batch order
while hasdata(mbqTest)
i = i+1;
x = next(mbqTest);
if ~hasdata(mbqTest)
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?
  1 Comment
Runcong Kuang
Runcong Kuang on 29 Sep 2022
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.
But thanks for your input @Walter Roberson.

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Answers (1)

Walter Roberson
Walter Roberson on 28 Sep 2022
Gpu training does not support double precision. If you look at the available options, precision cannot be selected.




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