Hello, I’ve discussed an Amazon Braket issue on Discord and was directed here. When I make a call into Amazon Braket within Jupyter cell, it works fine. All the code before, between and after the calls into Braket is executed properly. However, any cell that is executed afterwards is stuck.
To reproduce, please put the code below into a Jupyter cell (assuming you have AWS credentials configured in your environment). Run the cell, and then try to run another cell within Jupter, as simple as a print statement and Jupyter will get stuck until you interrupt it and restart the kernel.
Cell 1:
import pennylane as qml
from braket.devices import Devices
dev = qml.device("braket.aws.qubit", device_arn=Devices.Amazon.SV1, wires=1, shots=256)
@qml.qnode(dev)
def flip():
qml.X(wires=0)
return qml.probs(wires=0)
print("1")
res = flip()
print(res)
print(2)
res2 = flip()
print(res2)
print(3)
It will output:
1
[0. 1.]
2
[0. 1.]
3
Cell 2:
print("4")
It will get stuck after cell 1 is done executing.
qml.about() output:
Name: PennyLane
Version: 0.38.0
Summary: PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
Home-page: https://github.com/PennyLaneAI/pennylane
Author:
Author-email:
License: Apache License 2.0
Location: d:\dev\quantotto\quantum\qvenv\lib\site-packages
Requires: appdirs, autograd, autoray, cachetools, networkx, numpy, packaging, pennylane-lightning, requests, rustworkx, scipy, toml, typing-extensions
Required-by: amazon-braket-pennylane-plugin, PennyLane-qiskit, PennyLane_Lightning
Platform info: Windows-10-10.0.22631-SP0
Python version: 3.10.11
Numpy version: 1.26.3
Scipy version: 1.11.4
Installed devices:
- braket.aws.ahs (amazon-braket-pennylane-plugin-1.28.0)
- braket.aws.qubit (amazon-braket-pennylane-plugin-1.28.0)
- braket.local.ahs (amazon-braket-pennylane-plugin-1.28.0)
- braket.local.qubit (amazon-braket-pennylane-plugin-1.28.0)
- default.clifford (PennyLane-0.38.0)
- default.gaussian (PennyLane-0.38.0)
- default.mixed (PennyLane-0.38.0)
- default.qubit (PennyLane-0.38.0)
- default.qubit.autograd (PennyLane-0.38.0)
- default.qubit.jax (PennyLane-0.38.0)
- default.qubit.legacy (PennyLane-0.38.0)
- default.qubit.tf (PennyLane-0.38.0)
- default.qubit.torch (PennyLane-0.38.0)
- default.qutrit (PennyLane-0.38.0)
- default.qutrit.mixed (PennyLane-0.38.0)
- default.tensor (PennyLane-0.38.0)
- null.qubit (PennyLane-0.38.0)
- lightning.qubit (PennyLane_Lightning-0.38.0)
- qiskit.aer (PennyLane-qiskit-0.38.0)
- qiskit.basicaer (PennyLane-qiskit-0.38.0)
- qiskit.basicsim (PennyLane-qiskit-0.38.0)
- qiskit.remote (PennyLane-qiskit-0.38.0)
Could someone please check this use case?
Thank you!
Yev