Warning: Variable 'rxTrainFrames' was not saved. For variables larger than 2GB use MAT-file version 7.3 or later

How do i keep the rxTrainFrame into workspace? my code is

dataDirectory =  'E:\SNR-Dataset\Data-18-time'
frameDS =  signalDatastore(dataDirectory,'SignalVariableNames',["frame","label"],'IncludeSubfolders',true,'FileExtensions','.mat');
frameDSTrans = transform(frameDS,@helperModClassIQAsPages);
splitPercentages = [percentTrainingSamples,percentValidationSamples,percentTestSamples];
[trainDSTrans,validDSTrans,testDSTrans] = helperModClassSplitData(frameDSTrans,splitPercentages);
% Gather the training and validation frames into the memory
trainFramesTall = tall(transform(trainDSTrans, @helperModClassReadFrame));
rxTrainFrames = gather(trainFramesTall);
rxTrainFrames = cat(4, rxTrainFrames{:});
save('rxTrainFrames.mat', 'rxTrainFrames', '-v7.3')
validFramesTall = tall(transform(validDSTrans, @helperModClassReadFrame));
rxValidFrames = gather(validFramesTall);
rxValidFrames = cat(4, rxValidFrames{:});

% Gather the training and validation labels into the memory
trainLabelsTall = tall(transform(trainDSTrans, @helperModClassReadLabel));
rxTrainLabels = gather(trainLabelsTall);
rxTrainLabels = removecats(rxTrainLabels);
validLabelsTall = tall(transform(validDSTrans, @helperModClassReadLabel));
rxValidLabels = gather(validLabelsTall);
rxValidLabels = removecats(rxValidLabels);
maxEpochs = 100;
miniBatchSize = 128;
options = helperModClassTrainingOptions(maxEpochs,miniBatchSize,...
  numel(rxTrainLabels),rxValidFrames,rxValidLabels);
trainedNet5 = trainNetwork(rxTrainFrames,rxTrainLabels,trainedNet4 ,options);
save trainedNet5

Answer 1

[yanqi liu]

yes，sir，may be

save trainedNet5.mat trainedNet5 rxTrainFrames

then use

load trainedNet5.mat

to get it

[john karli]

when i load load trainedNet5.mat then rxTrainFrames is not showingi n workspace and i got the error that rxTrainFrames is not define.

[yanqi liu]

yes，sir，may be use

save trainedNet5.mat trainedNet5 rxTrainFrames

to get file “trainedNet5.mat”

then，use

clear all;
load trainedNet5.mat
rxTrainFrames

check the rxTrainFrames