Math used for BiLSTMLayer in predict function
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I am trying to convert a trained Bi-LSTM network to use on another platform, and wish to know the exact math used for the BiLSTM layer in Matlab predict function, just like the equations used in the LSTM layer Architecture section on this page.
The reason I am asking is that, the output given by the "predict" function is different from the output I calculate using my own code.
So I am trying to figure out the problem.
(pretty sure that I got the parameters like the input weights, recurrectweight, and bias correctly.)
The way I was calculating is as follows:
% forward
ft = sigmoid(wf*xt + uf*ht +bf);
it = sigmoid(wi*xt + ui*ht +bi);
ot = sigmoid(wo*xt + uo*ht +bo);
ctb = tanh(wc*xt + uc*ht +bc);
ct = ft.*ct + it.*ctb;
ht = ot.*tanh(ct);
% backward
xtb = flip(xt);
ftb = sigmoid(wfb*xtb + ufb*htb +bfb);
itb = sigmoid(wib*xtb + uib*htb +bib);
otb = sigmoid(wob*xtb + uob*htb +bob);
ctbb = tanh(wcb*xtb + ucb*htb +bcb);
ctb = ftb.*ctb + itb.*ctbb;
htb = otb.*tanh(ctb);
% output hidden states
Ht = [ht;htb];
Can anyone help? Thank you very much!
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採用された回答
David Willingham
2022 年 1 月 27 日
Hi James,
One option for exporting is to export the network to onnx format using exportONNXnetwork. Once exported you could either import the onnx version into the other framework as well as look at how the network wax exported.
3 件のコメント
David Willingham
2022 年 1 月 28 日
I checked with our developers and what you have looks correct. Without having both your full MATLAB code and python? code it may be difficult for us to find the reason why they maybe different.
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