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Can you share the script you are using to check if we can reproduce the error on our end?
Thank You!
Hello, Thank you for using Braket!
Have you tried submitting the circuit again? I believe this is a boto api transient error. In order for us to reproduce the issue on our end can you provide us with the following information:
- This error was received immediately or after a certain period of time after submitting the circuit?
- Are you using any of the Braket example notebooks or a different script for this?
Thank you for your response.
-
The error appeared after a certain period of time after submitting the circuit, I actually received some solutions without any errors, but after approx. one hour, the error message was shown.
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I did not use one of the example notebooks, I am using my own script within my local Python IDE (PyCharm).
Hello, you could use the following to configure the read timeouts:
from botocore.config import Config
from braket.aws import AwsSession
config = Config(read_timeout=300)
session = AwsSession(config=config)
and then supply this session to the BraketDWaveSampler as:
system = BraketDWaveSampler(s3_destination_folder=s3_folder,
device_arn='arn:aws:braket:::device/qpu/d-wave/Advantage_system4',
aws_session=session)
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I cannot share everything, since it is part of an ongoing research project, but here are the main parts. The error occurred during the execution of "QBSolv().sample_qubo(...)".
choose a D-Wave Advantage system
system = BraketDWaveSampler(s3_folder, device_arn='arn:aws:braket:::device/qpu/d-wave/Advantage_system4')
use the FixedEmbeddingComposite() method with a fixed embedding
solver_QA = FixedEmbeddingComposite(system, embedding)
Initialize the QUBO matrix
QUBO = defaultdict(int)
Update the QUBO matrix based on the problem at hand
for k in qubo_matrix_quadratic_dict: QUBO[(k[0], k[1])] += qubo_matrix_quadratic_dict[k]
sampler = solver_QA response = QBSolv().sample_qubo(QUBO, solver=sampler, num_repeats=config_dict["num_repeats"], solver_limit=config_dict["solver_limit"], num_reads=config_dict["number_of_reads"], verbosity=1)