LSTM not outputting sequence

1 view (last 30 days)
John Malik
John Malik on 18 Dec 2019
Edited: John Malik on 26 Dec 2019
I am attempting to do sequence-to-sequence classification.
I haveNtime series of observations each, and each observation collectsp features.
I build a cell array XTrain. I set XTrain{i} to be the i-th time series in my database.
I have two classes. I build a cell array YTrain, where YTrain{i} is a categorical vector telling me which class is at which time.
Now I build the following network:
inputSize = [p, 1, 1];
filterSize = [2 1];
numFilters = 20;
numHiddenUnits = 128;
numClasses = 2;
layers = [ ...
sequenceInputLayer(inputSize,'Name','input')
sequenceFoldingLayer('Name','fold')
convolution2dLayer(filterSize,numFilters,'Name','conv1')
reluLayer('Name','relu1')
convolution2dLayer(filterSize,numFilters,'Name','conv2')
reluLayer('Name','relu2')
flattenLayer('Name','flatten')
sequenceUnfoldingLayer('Name','unfold')
lstmLayer(numHiddenUnits,'OutputMode','sequence','Name','lstm')
fullyConnectedLayer(numClasses,'Name','fc')
softmaxLayer('Name','softmax')
classificationLayer('Name','classification')];
lgraph = layerGraph(layers);
lgraph = connectLayers(lgraph,'fold/miniBatchSize','unfold/miniBatchSize');
maxEpochs = 1;
miniBatchSize = 2;
options = trainingOptions('adam', ...
'ExecutionEnvironment','cpu', ...
'MaxEpochs',maxEpochs, ...
'MiniBatchSize',miniBatchSize, ...
'GradientThreshold',1, ...
'Verbose',false, ...
'Plots','training-progress');
net = trainNetwork(XTrain,YTrain,lgraph,options);
However, if I then run:
YScores = predict(net,XTrain,'MiniBatchSize',1);
the output is a cell array whose i-th entry is a vector of class probabilities.
This is INCORRECT. It should be a vector of class probabilities.
  4 Comments
John Malik
John Malik on 26 Dec 2019
Edited: John Malik on 26 Dec 2019
Thanks, I had that first and changed it to this version.
Neither work.
I ended up coding it myself from scratch.

Sign in to comment.

Answers (0)

Categories

Find more on Image Data Workflows in Help Center and File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!