Improve QNode keyword input validation

Feature details

Any keyword argument can be passed to a QNode or its qnode decorator without errors arising.

This can result in unexpected behaviour if users make a typo when attempting to use a valid option.

E.g., the following example uses the Autograd interface although inteface="jax" is being passed (because inteface is not an accepted kwarg):

import pennylane as qml

dev = qml.device('default.qubit', wires=3)

@qml.qnode(dev, inteface="jax")
def circuit():
    return qml.expval(qml.PauliZ(0))

>>> circuit()
tensor(1., requires_grad=True)

Implementation

No response

How important would you say this feature is?

2: Somewhat important. Needed this quarter.

Additional information

No response

[antalszava]

Hi @nahumsa, great! 😃

I think that sounds good. The main subtlety here is that kwargs passed to qml.qnode would be passed as gradient_kwargs to qml.execute. So it first has to be considered if the possible options for gradient_kwargs can be collected in advance or if not, if we can somehow create patterns and/or query options from the ML framework determined by a specific interface.

[nahumsa]

I have noticed that on pennylane.interfaces.execution.cache_execute:

https://github.com/PennyLaneAI/pennylane/blob/1e3a73107d1a897ba04910492c1c698d41e8787e/pennylane/interfaces/execution.py#L126-L128

The gradient_kwargs variable when running the default interface (which I think is autograd) is modified to an empty dict because of the pennylane.interfaces.autograd._execute

https://github.com/PennyLaneAI/pennylane/blob/1e3a73107d1a897ba04910492c1c698d41e8787e/pennylane/interfaces/autograd.py#L109-L110

Any thoughts about this?

P.S.: I’m trying to understand more about the codebase, sorry if the commentary wasn’t that useful 😃