invalid training data for following code?

Error : The output size [132 132132 6] of the last payer does not match the response size [132 132 132 3]

My code is following

imageDir=fullfile(tempdir,'PP');

if ~exist(imageDir,'dir')

mkdir(imageDir);

end

sourceDatalaoc=[imageDir filesep 'Brain'];

volc=fullfile (sourceDatalaoc, 'AA')

if~ exist(volc,'dir')

mkdir(volc);

end

loc=fullfile (sourceDatalaoc, 'BB')

if~ exist(loc,'dir')

mkdir(loc);

end

%matReader = @samplePXDSMatReader;

imds = imageDatastore(volc,'FileExtensions','.nii','ReadFcn',@sampleReadeFcn);

%auimds = augmentedImageDatastore([64 64 64 ],imds)

classNames = ["edema","nonEnhancingTumor","enhancingTumour"];

pixelLabelID = [1 2 3];

pxds = pixelLabelDatastore(loc,classNames,pixelLabelID,'FileExtensions','.nii','ReadFcn',@sampleReadeFcn);

V = read(imds);

L = read(pxds);

%h = labelvolshow(L,V(:,:,:,1));

pximds = pixelLabelImageDatastore(imds,pxds);

inputPatchSize = [132 132 132 4];

numClasses = 2;

patchSize = [132 132 132];

patchPerImage = 8;

miniBatchSize = 16;

patchds = randomPatchExtractionDatastore(imds,pxds,patchSize, ...

'PatchesPerImage',patchPerImage);

patchds.MiniBatchSize = miniBatchSize;

layers = [

image3dInputLayer([132 132 132 4])

convolution3dLayer(3,12,'Stride',1,'Padding','Same')

batchNormalizationLayer

reluLayer

transposedConv3dLayer(3,12,'Stride',1,'Cropping',1)

batchNormalizationLayer

reluLayer

transposedConv3dLayer(3,6,'Stride',1,'Cropping',1)

softmaxLayer

pixelClassificationLayer

]

opts = trainingOptions('sgdm', ...

'InitialLearnRate',1e-3, ...

'ExecutionEnvironment','CPU',...

'MaxEpochs',100);

[net2,info] = trainNetwork(patchds,layers,opts);close

function data = sampleReadeFcn(filename)

data = niftiread(filename)

end