[BUG] JSONDecodeError when running cuVS Bench
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Description
Describe the bug
When running cuVS Bench in Docker, I encountered the following errors:
Steps/Code to reproduce bug
Follow this guide https://docs.rapids.ai/api/cuvs/nightly/cuvs_bench/ to install cuVS Bench with Docker, then execute the following commands to run:
export DATA_FOLDER=./datasets
docker run --gpus all --rm -it -u $(id -u) \
-v $DATA_FOLDER:/data/benchmarks \
rapidsai/cuvs-bench:24.12a-cuda12.5-py3.10 \
"--dataset gist-960-euclidean" \
"--normalize" \
"--algorithms cuvs_cagra,cuvs_ivf_pq --batch-size 1 -k 10" \
""
Expected behavior
The benchmark results should be exported without errors.
Environment details (please complete the following information):
- Environment location: Docker
- Method of RAFT install: Docker
- If method of install is [Docker], provide
docker pull&docker runcommands used: docker pull rapidsai/cuvs-bench:24.12a-cuda12.5-py3.10
- If method of install is [Docker], provide
Additional context
The ANN search process in the benchmark seems to be running normally, but the result export process failed. I tried to switch to the conda environment, install cuVS in conda, and run the benchmark, but the error persisted.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Follow the cuVS Bench Docker guide and reproduce the JSONDecodeError with the provided docker pull and docker run commands. Start at the benchmark result-export process, since ANN search appears to complete normally. Done means the benchmark results export successfully without the reported error.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- docker
- Domain
- devops, testing-qa
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100