uis-rnn
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Add a `online_predict()` API for streaming input
UIS-RNN is an online algorithm, but the current predict() API of this library is not.
If people want to deploy this library to a production environment for online use cases, an online_predict() API is going to be necessary.
Its usage should be like this:
# Feed the first sequence, and continuously make use of the label.
label = model.online_predict(X1)
label = model.online_predict(X2)
label = model.online_predict(X3)
model.online_predict(reset=True)
# Feed the second sequence, and continuously make use of the label.
label = model.online_predict(Y1)
label = model.online_predict(Y2)
label = model.online_predict(Y3)
label = model.online_predict(Y4)
model.online_predict(reset=True)
However, we may not have the bandwidth to work on this any time soon.
Unfortunately, as several core members have left the team, we won't be able to work on this ourselves.
But if someone wants to work on this, he/she can create a subclass of UISRNN under the contrib directory. We would welcome that.
UIS-RNN is an online algorithm, but the current
predict()API of this library is not.If people want to deploy this library to a production environment for online use cases, an
online_predict()API is going to be necessary.Its usage should be like this:
# Feed the first sequence, and continuously make use of the label. label = model.online_predict(X1) label = model.online_predict(X2) label = model.online_predict(X3) model.online_predict(reset=True) # Feed the second sequence, and continuously make use of the label. label = model.online_predict(Y1) label = model.online_predict(Y2) label = model.online_predict(Y3) label = model.online_predict(Y4) model.online_predict(reset=True)However, we may not have the bandwidth to work on this any time soon.
can you give some ideas?
