MATLAB: Error in matlab included deep learning example

deep learningMATLAB

I am trying to run the matlab example
openExample('nnet/SeqToSeqClassificationUsing1DConvAndModelFunctionExample')
In 2019b but, when i change to train the network on gpu the example show me this error. Please help me to run it or give me a workaround to train using gpu.
Error using gpuArray/subsasgn
Attempt to grow array along ambiguous dimension.
Error in deep.internal.recording.operations.ParenAssignOp/forward (line 45)
            x(op.Index{:}) = rhs;
Error in deep.internal.recording.RecordingArray/parenAssign (line 29)
    x = recordBinary(x,rhs,op);
Error in dlarray/parenAssign (line 39)
    objdata(varargin{:}) = rhsdata;
Error in SeqToSeqClassificationUsing1DConvAndModelFunctionExample>maskedCrossEntropyLoss (line 484)
    loss(i) = crossentropy(dlY(:,i,idx),dlT(:,i,idx),'DataFormat','CBT');
Error in SeqToSeqClassificationUsing1DConvAndModelFunctionExample>modelGradients (line 469)
loss = maskedCrossEntropyLoss(dlY, dlT, numTimeSteps);
Error in deep.internal.dlfeval (line 18)
[varargout{1:nout}] = fun(x{:});
Error in dlfeval (line 40)
[varargout{1:nout}] = deep.internal.dlfeval(fun,varargin{:});
Error in SeqToSeqClassificationUsing1DConvAndModelFunctionExample (line 284)
        [gradients, loss] = dlfeval(@modelGradients,dlX,Y,parameters,hyperparameters,numTimeSteps);
Thanks!

Best Answer

There is a bug in this Example which will be rectified. Thanks for reporting. To workaround, initialize the loss variable in the maskedCrossEntropyLoss function:
function loss = maskedCrossEntropyLoss(dlY, dlT, numTimeSteps)
numObservations = size(dlY,2);
loss = zeros([1,1],'like',dlY); % Add this line
for i = 1:numObservations
    idx = 1:numTimeSteps(i);
    loss(i) = crossentropy(dlY(:,i,idx),dlT(:,i,idx),'DataFormat','CBT');
end
end
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