Error in matlab included deep learning example
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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 个评论
Edric Ellis
2019-10-15
Thanks for reporting this - I can reproduce the problem using R2019b here, I shall forward this to the development team...
采纳的回答
Joss Knight
2019-10-15
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 个评论
Javier Bush
2019-10-17
Joss Knight
2019-10-17
That's odd - I'll get back to you on that.
Javier Bush
2019-10-17
Katja Mogalle
2019-10-25
There are some small issues in the example script that will prevent you from setting the miniBatchSize>1. The fix is pretty simple though.
1) Replace the modelGradients function with the following:
function [gradients,loss] = modelGradients(dlX,T,parameters,hyperparameters,numTimeSteps)
dlY = model(dlX,parameters,hyperparameters,true);
dlY = softmax(dlY,'DataFormat','CBT');
dlT = dlarray(T,'CBT');
loss = maskedCrossEntropyLoss(dlY, dlT, numTimeSteps);
gradients = dlgradient(mean(loss),parameters); % this line was changed to compute the mean loss
end
2) Replace the transformSequences function with the following:
function [XTransformed, YTransformed, numTimeSteps] = transformSequences(X,Y)
% Removed line which computed the numTimeSteps. We'll compute this later in the loop
miniBatchSize = numel(X);
numFeatures = size(X{1},1);
sequenceLength = max(cellfun(@(sequence) size(sequence,2),X));
classes = categories(Y{1});
numClasses = numel(classes);
sz = [numFeatures miniBatchSize sequenceLength];
XTransformed = zeros(sz,'single');
sz = [numClasses miniBatchSize sequenceLength];
YTransformed = zeros(sz,'single');
for i = 1:miniBatchSize
predictors = X{i};
% Create dummy labels.
numTimeSteps(i) = size(predictors,2); % This line now sets the time steps for the i-th observation
responses = zeros(numClasses, numTimeSteps(i), 'single'); % This line also uses the i-th observation numTimeSteps
for c = 1:numClasses
responses(c,Y{i}==classes(c)) = 1;
end
% Left pad.
XTransformed(:,i,:) = leftPad(predictors,sequenceLength);
YTransformed(:,i,:) = leftPad(responses,sequenceLength);
end
end
Note, however, that depending on your GPU you might run into out-of-memory issues already with a small miniBatchSize. I have a GeForce GTX 1080 and I already run into this issue with a miniBatchSize of 3.
We will work on updating the example to fix these issues as soon as possible. Apologies for the inconvenience!
Javier Bush
2019-10-26
Zekun
2019-12-29
编辑：Walter Roberson
2019-12-30
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.
更多回答（2 个）
Linda Koletsou Soulti
2019-10-22
0 个投票
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:
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