- I would like to know if the keras layer supports back propgation with while using tf.tensor device and the qulacs device in version 13?
- can we use
parallel=true with tensorflow to compute the gradients of multiple circuits?
- in tensorflow 2.4.0 this error occurs:
but in tf 2.3.1 it works fine.
thanks in advance
- Yes, you should be able to use backpropagation for a KerasLayer consisting of tensorflow tensors for the classical part and qulacs device for the quantum part.
- Depends more specifically what you mean here. How does your question compare to this one for TorchLayer? (which should have similar restrictions as KerasLayer)
- This is hard to debug without further context (e.g., a minimal (non-)working example). The error seems to be thrown by Keras, and you say it doesn’t occur in earlier versions, so on a superficial level I would guess it is a bug in TF/Keras, but hard to know for sure without full code here