[Draft] Add a standard way of creating QNN models

[smitchaudhary]

Meant to fix pasqal-io/qadence#396

It is not meant as a replacement of the current workflow but a more of a standardised alternative.

• Main motivation is to have a standard manner of defining QNNs.
• Good for quick prototyping and benchmarking different parts (Rydberg Hamiltonian based ansatz vs a fully digital ansatz etc)
• Much easier to store this
• Reduces a bunch of boilerplate code that you need to write.

[dominikandreasseitz]

hi @smitchaudhary , i responded in pasqal-io/qadence#396 regarding this, but i think @jpmoutinho is the best person to consult about this

[jpmoutinho]

Thanks @dominikandreasseitz, yes I am aware of these changes and will review it.

[smitchaudhary]

Thanks @dominikandreasseitz and @jpmoutinho

Still a draft. Once I incorporate more changes, will request a proper review. Open for feedback already though.

[n-toscano]

Watchout @smitchaudhary, there's still a reference to the eic_aero package in the quantum_models file

[RolandMacDoland]

Hey @smitchaudhary will you have time to work on this ?

[smitchaudhary]

@Roland-djee Yes I will pick it up soon. Gathering some more feedback from some users and incorporating that.

[dominikandreasseitz]

hey @smitchaudhary , lets add the logic for output transformation here

[smitchaudhary]

Yeah! It can already do a scaling operation for each qubit. Will expand that to include shifting too. Also I need to make the names a bit more clear.

[dominikandreasseitz]

@smitchaudhary should we merge pasqal-io/qadence#385 and this together?

[smitchaudhary]

@dominikandreasseitz I assume the transformed module needs to be refactored for qadence at large but does this new config workflow also go directly into qadence, in contrast to just qadence-libs for now?

[dominikandreasseitz]

@dominikandreasseitz I assume the transformed module needs to be refactored for qadence at large but does this new config workflow also go directly into qadence, in contrast to just qadence-libs for now?

imo, i would have all of this in qadence for now and then move the full ml_tools module once its ready @Roland-djee @jpmoutinho @Doomsk @smitchaudhary

[jpmoutinho]

@dominikandreasseitz I assume the transformed module needs to be refactored for qadence at large but does this new config workflow also go directly into qadence, in contrast to just qadence-libs for now?

imo, i would have all of this in qadence for now and then move the full ml_tools module once its ready @Roland-djee @jpmoutinho @Doomsk @smitchaudhary

I would first try to converge on the goal for the QNN interface before deciding how to handle the code here and the changes being made in your MR @dominikandreasseitz.

Some thoughts:

• In the current state, the code here is a convenience layer on top of QNN which culminates in build_qnn function. Is that desired? Another option is to have the configs be part of the input of the QNN class itself.
• In this MR the scaling parameters affect how the feature map constructor is built, while in the QNN MR the scaling affects the parameters of the QNN itself. These are functionalities with an overlapping goal but different implementation. What is the plan on combining those?
• Same thing for the output scaling and observable config.

[smitchaudhary]

@jpmoutinho

In the current state, the code here is a convenience layer on top of QNN which culminates in build_qnn function. Is that desired? Another option is to have the configs be part of the input of the QNN class itself.

This was developed independent of the QNN/TransformedModule logic (and is just a draft at that), so if the plan is to open up QNN and change the definition/signature altogether, then we could do that. However, the current QuantumCircuit class is a lot more general than what is created inside build_qnn_model. For starters, in general, a circuit is not required to have a feature map, or ansatz. It can have any block. All this to say that if this is the route taken, then the current logic with the configs here will need to be changed accordingly.

These are functionalities with an overlapping goal but different implementation. What is the plan on combining those?

I think @dominikandreasseitz 's impetus behind merging the two is exactly this. Do away with the wrapper TransformedModule.

[jpmoutinho]

In the current state, the code here is a convenience layer on top of QNN which culminates in build_qnn function. Is that desired? Another option is to have the configs be part of the input of the QNN class itself.

This was developed independent of the QNN/TransformedModule logic (and is just a draft at that), so if the plan is to open up QNN and change the definition/signature altogether, then we could do that. However, the current QuantumCircuit class is a lot more general than what is created inside build_qnn_model. For starters, in general, a circuit is not required to have a feature map, or ansatz. It can have any block. All this to say that if this is the route taken, then the current logic with the configs here will need to be changed accordingly.

Yes indeed! I just meant that it is an opportunity to think about the best option and work towards that. We already have the QuantumModel for general circuits, and we could allow the QNN to be initialized with your workflow directly, letting your code take care of the circuit initialization. It could still accept custom circuits of course. I understand it is currently designed as a layer on top, and that is also fine by me if you prefer that as a user.

[dominikandreasseitz]

@awennersteen @Roland-djee , @smitchaudhary @jpmoutinho and I propose to combine https://github.com/pasqal-io/qadence/pull/385/files and this MR together, meaning:

1. Removal of the TranformedModule
2. Achieving scaling/shifting of inputs and outputs of QNNs through featuremap and observable configs

However some libraries which use qadence rely on the TransfomedModule for classical NNs, we think its best to fully separate the quantum and classical parts which would be achieved by doing the above. wdyt?

[smitchaudhary]

Moved this PR to the main qadence repo here