I am unable to find the errror.....

%------------------------Data STores--------------------------------------%
dataSetDir = 'C:\Users\idree\Desktop\Main\ultimate\'
imageDir = fullfile(dataSetDir,'o_binary');
labelDir = fullfile(dataSetDir,'l_binary');
imds = imageDatastore(imageDir);
%-------------------------------------------------------------------------%
classNames = ["shirorekha" "character" "background"];
labelIDs = [1 2 3];
pxds = pixelLabelDatastore(labelDir, classNames, labelIDs);
layers = [
    imageInputLayer([256 256 1])
    convolution2dLayer(3,32,'Padding',1)
    reluLayer
    maxPooling2dLayer(2,'Stride',2)
    convolution2dLayer(3,32,'Padding',1)
    reluLayer
    transposedConv2dLayer(4,32,'Stride',2,'Cropping',1)
    reluLayer
    transposedConv2dLayer(4,32,'Stride',2,'Cropping',1)
    reluLayer
    convolution2dLayer(1,3)
    softmaxLayer
    dicePixelClassificationLayer('dice')
    ]

ds = pixelLabelImageDatastore(imds,pxds);
options = trainingOptions('sgdm', ...
    'InitialLearnRate',1e-3, ...
    'MaxEpochs',100, ...
    'LearnRateDropFactor',0.1, ...
    'LearnRateDropPeriod',50, ...
    'LearnRateSchedule','piecewise', ...
    'MiniBatchSize',32);

net = trainNetwork(ds,layers,options);

-------------------------------------------------------------------------------------------------------

Error using trainNetwork (line 165)
Invalid training data. The output size ([512 512 3]) of the last layer does not match the response size ([256 256 3]).

Error in dice_try_data (line 35)
net = trainNetwork(ds,layers,options);

[Guillaume]

The error message seems clear to me, your neural net expects 256x256 image but is getting 512x512 images.

I know nothing about the neural net toolbox so can't help any further.

[Mohammad Bhat]

I solved by adding maxpooling layer at the end....

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layers = [
    imageInputLayer([256 256 1])
    convolution2dLayer(3,32,'Padding',1)
    reluLayer
    maxPooling2dLayer(2,'Stride',2)
    convolution2dLayer(3,32,'Padding',1)
    reluLayer
    transposedConv2dLayer(4,32,'Stride',2,'Cropping',1)
    reluLayer
    transposedConv2dLayer(4,32,'Stride',2,'Cropping',1)
    reluLayer
    maxPooling2dLayer(2,'Stride',2)
    convolution2dLayer(1,3)
    softmaxLayer
    dicePixelClassificationLayer('dice')
    ]