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Description
System and Environment Information
Running on mac os 15.6.1, python version 3.13.0 and mqt-predictor version 2.3.0
Bug Description
I'm following the framework setup section in the documentation. I was able to run Step 2 (RL training) in about 4 hours on my M4 Pro, using 50k timesteps for IBM Falcon 27.
For Step 3, I've been running the code for several hours but am not able to tell the progress in the ML training phase. Is there a way to assess the progress? Is there an estimate of how long it should take?
You can look at this log for output from my run before I killed the process. It looks like a call to bqskit is timing out, and then later on, it looks like some subprocesses may not be handling signals properly and lingering.
Steps to Reproduce
- Setup environment with
uv initanduv add mqt.predictor - Follow the steps in https://mqt.readthedocs.io/projects/predictor/en/latest/setup.html
- For step 3, run:
from mqt.predictor.ml import setup_device_predictor
from mqt.bench.targets import get_device
devices = [get_device("ibm_falcon_27")]
setup_device_predictor(
devices=devices,
figure_of_merit="expected_fidelity",
)Reactions are currently unavailable
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