Random shuffling (with shuffle() command) does not work in combination with randomPatc​hExtractio​nDatastore​-Objects and/or multi-gpu training

I want to shuffle my partitioned randomPatchExtractionDatastore objects in "workerImds" randomly by using the "shuffle()" command like shown in the following lines:

iteration = 0;

    spmd
        % partition datastore
        workerImds = partition(dsTrain,numWorkers,labindex);
        workerImds.MiniBatchSize = workerMiniBatchSize(labindex);

        % loop over epochs
        for epoch = 1:options.MaxEpochs
            
            % shuffle data every epoch
            reset(workerImds)
            workerImds = shuffle(workerImds);
            
            % loop over mini-batches
            while gop(@and,hasdata(workerImds))
                
                iteration = iteration + 1;
                
                % read mini-batch of data
                [workerXYBatch,workerImdsInfo] = read(workerImds);
                
                ...
                    
            end  
        end
    end

This is done according to the related documentation: https://de.mathworks.com/help/parallel-computing/train-network-in-parallel-with-custom-training-loop.html

But everytime starting a new training loop the shuffling results in the same order of indices, which can be seen when adding the following line to my while-loop and starting the training over and over again.

if iteration == 1 || mod(iteration-1,numIterationsPerEpoch) == 0
    if labindex == 1
        fprintf("\nEpoch: %2.0f Iteration: %4.0f WorkerIndices: %s",epoch,iteration,mat2str(workerImdsInfo.ImageIndices.'))
    end
end

Lab 1: 

Epoch:  1 Iteration:    1 WorkerIndices: [16 23 15 21 49]
Epoch:  2 Iteration:   11 WorkerIndices: [40 17 38 24 15]
Epoch:  3 Iteration:   21 WorkerIndices: [49 21 18 11 12]
Epoch:  4 Iteration:   31 WorkerIndices: [24 6 48 42 40]
Epoch:  5 Iteration:   41 WorkerIndices: [18 36 22 20 23]

This order of indices ([16 23 15 21 49] ...) is what I get, everytime doing the training. This is not what I would call random shuffling. This is more like a "static shuffling algorithm".

The same problem also occurs without multi-GPU training (without spmd block) when trying to randomly shuffle the normal (non-partitioned) randomPatchExtractionDatastore-Object "dsTrain".

However, the problem does not occur when shuffling an ImageDatastore object. In this case, as well as in the case of shuffling a minibatchqueue by using the shuffle() command, the random shuffling works very well. But unfortunately in this multi-GPU case I can neither use a minibatchqueue nor a normal imageDatastore object in my regression use case.

Looking forward to help and advice on this subject! Thank you!