LSTM architecture for a sequence-to-sequence model

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Brita Linnestad
Brita Linnestad 2022-9-28
回答： Sivylla Paraskevopoulou 2022-10-14
I have build a LSTM sequence-to-sequence model which I would like to convert to onnx and use in a python script-
My input data is as follows, 11307 sequences of 24 times steps and 6 features:
XTrain = 11307x1 cell array
{ 6x24 double}
YTrain = 11307x1 cell array
{1x24 catgorical}
The layer is :
numFeatures = 6
NumHiddenUnis = 50
numClasses = 2
layers = [ ...
sequenceInputLayer(numFeatures)
lstmLayer(numHiddenUnits,'OutputMode','sequence')
fullyConnectedLayer(numClasses)
softmaxLayer
classificationLayer];
netlstm=trainNetwork(XTrain,YTrain,layers,options)
Whe I run the model on test data with numFeatures = 6, sequence_length = 24 in matlab, the results are good.
Exporting netlstm to onnx using
exportONNXNetwork(netlstm, 'file.onnx')
Viewing the file.onnx in a model checker show that the initial_h is 1x1x50, not 1x24x50 as expected.
Loading the onnx.model in python, I can run the model with input 1x1x6, but not he full sequence of 24 time steps.
Why is the sequnce length missing from initial_h after exporting to onnx?
The example: Sequence-to-Sequence Classification Using Deep Learning - MATLAB & Simulink - MathWorks Nordic
gives the same issue when exporting the network after running the example.

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回答（1 个）

Sivylla Paraskevopoulou
You can try specifying the BatchSize name-value argument of the exportONNXNetwork function.

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