Hey, Is there a way to pass iterable arguments to the qnode, where the cost and/or ansatz is redefined for each instance of the problem? Ex 1: import pennylane as qml from pennylane import numpy as np N = 2 dev = qml.device(‘forest.numpy_wavefunction’, wires=N) @qml.qnode(dev) def qaoa_one_q…

if you allow me this example demonstrates how to use pytorch and also defines which variable needs to be differentiated I think if i got your question right this answers your problem

Hi Kareem! Thanks for the response. Unfortunately I don’t think so. In the example you posted only differentiable parameters are passed to the qnode. There is a non-differentiable parameter passed to the cost function (step), but this isn’t used in / passed to the qnode. What I would like to do is…

you’re most welcome but I think if you actually set: required_grad=False then the torch backend won’t calculate its gradients it would be like a constant inside your quantum circuit

There is a semi-related problem in the docs https://pennylane.readthedocs.io/en/latest/tutorials/qubit_rotation.html where it states “Keyword arguments may also be used in your custom quantum function. PennyLane does differentiate QNodes with respect to keyword arguments, so they are useful for pa…

With the above bugfix, your optimization example now works: @qml.qnode(dev) def qaoa_one_qubit(param, problem=None): for i in problem: qml.RX(param[0], wires=i) return qml.expval.PauliZ(i) problem = [0] def cost(param): exp = qaoa_one_qubit(param, problem=problem) return e…

Ah thanks! Sorry, didn’t understand first time. I’ll try this out as well.

Unfortunately, I’m still getting an error @josh . Code %reset -f import pennylane as qml from pennylane import numpy as np import os x = os.path.dirname(qml.file) print(x) N = 2 dev = qml.device(‘forest.numpy_wavefunction’, wires=N) @qml.qnode(dev) def qaoa_one_qubit(param, problem=None): …

Hey @kareem is this what you had in mind? Thought we had it working for a second there… I’ve done a bunch of tests, its a Variable, and when I try and access it with .val it thinks it is None. I want to iterate over ‘terms’ in a list of list, perform some operations on the elements of those terms,…

[image] mxn.wls: Unfortunately, I’m still getting an error @josh . Hey @mxn.wls , I played around with your example, and I get the same error message. However, it works if I remove the print statements inside the QNode: import pennylane as qml from pennylane import numpy as np N = 2 dev = qml…

The following bug fix allows the print statement inside the QNode to work :slight_smile: But, there is a caveat. The way PennyLane is coded, the original function is only ever executed once. The QNode compiles the quantum functions after the first execution, and uses the compiled result from then o…

Passing non-differentiable arguments to qnode

PennyLane Help

SreeramV181 June 7, 2019, 7:09pm 14

How do I install this on my command line?

Gradient Not Working Because of Keyword Arguments

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Passing non-differentiable arguments to qnode

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