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Error in matlab included deep learning example

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Javier Bush
Javier Bush on 15 Oct 2019
Edited: Walter Roberson on 30 Dec 2019
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!
  1 Comment
Edric Ellis
Edric Ellis on 15 Oct 2019
Thanks for reporting this - I can reproduce the problem using R2019b here, I shall forward this to the development team...

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Accepted Answer

Joss Knight
Joss Knight on 15 Oct 2019
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
  6 Comments
Zekun
Zekun on 29 Dec 2019
I found another solution for
"Error using gpuArray/subsasgn
Attempt to grow array along ambiguous dimension."
In dlarray/parenAssign.m, at this location:"\R2019b\toolbox\nnet\deep\@dlarray\parenAssign.m"
Line 15:
obj = zeros(0, 0, 'like', rhs);
Replace line 15 with the following 2 lines:
szrhs = size(rhs);
obj = zeros(szrhs(1), szrhs(2), 'like', rhs);
Users cannot directly edit this file, so I backed it up and replace it with a new file.

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More Answers (2)


Linda Koletsou Soulti
Linda Koletsou Soulti on 22 Oct 2019
Thank you for reporting the issue. The error you are getting is related to an attempt to grow a gpuArray using linear indexing assignment.
For more information please refer to the following bug report:
  1 Comment
Javier Bush
Javier Bush on 23 Oct 2019
Linda,
I just changed the miniBatchSize to 2, in the same example and I get the following error, could you please help me with that? I think this is a bug because that is offered as a parameter in the example but you cannot change it.
Index exceeds the number of array elements (1).
Error in SeqToSeqClassificationUsing1DConvAndModelFunctionExample>maskedCrossEntropyLoss (line 486)
idx = 1:numTimeSteps(i);
Error in SeqToSeqClassificationUsing1DConvAndModelFunctionExample>modelGradients (line 472)
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 287)
[gradients, loss] = dlfeval(@modelGradients,dlX,Y,parameters,hyperparameters,numTimeSteps);

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