From 1fe3bf95e4f306f6b5a8faddcf0790cb3ea1a13a Mon Sep 17 00:00:00 2001 From: James Bourbeau Date: Thu, 9 Apr 2026 11:17:35 -0500 Subject: [PATCH] Fix cuvs-bench docker images in docs Signed-off-by: James Bourbeau --- docs/source/cuvs_bench/index.rst | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/source/cuvs_bench/index.rst b/docs/source/cuvs_bench/index.rst index c80b461aa4..2efa9ff86b 100644 --- a/docs/source/cuvs_bench/index.rst +++ b/docs/source/cuvs_bench/index.rst @@ -84,7 +84,7 @@ We provide images for GPU enabled systems, as well as systems without a GPU. The Nightly images are located in `dockerhub `_. -The following command pulls the nightly container for Python version 3.13, CUDA version 12.9, and cuVS version 26.04: +The following command pulls the nightly container for Python version 3.13, CUDA version 12.9, and cuVS version 26.06: .. code-block:: bash @@ -289,7 +289,7 @@ For GPU-enabled systems, the `DATA_FOLDER` variable should be a local folder whe export DATA_FOLDER=path/to/store/datasets/and/results docker run --gpus all --rm -it -u $(id -u) \ -v $DATA_FOLDER:/data/benchmarks \ - rapidsai/cuvs-bench:26.06-cuda12.9-py3.13 \ + rapidsai/cuvs-bench:26.06a-cuda12-py3.13 \ "--dataset deep-image-96-angular" \ "--normalize" \ "--algorithms cuvs_cagra,cuvs_ivf_pq --batch-size 10 -k 10" \ @@ -302,7 +302,7 @@ Usage of the above command is as follows: * - Argument - Description - * - `rapidsai/cuvs-bench:26.06-cuda12.9-py3.13` + * - `rapidsai/cuvs-bench:26.06a-cuda12-py3.13` - Image to use. See "Docker" section for links to lists of available tags. * - `"--dataset deep-image-96-angular"` @@ -331,7 +331,7 @@ The container arguments in the above section also be used for the CPU-only conta export DATA_FOLDER=path/to/store/datasets/and/results docker run --rm -it -u $(id -u) \ -v $DATA_FOLDER:/data/benchmarks \ - rapidsai/cuvs-bench-cpu:26.04a-py3.13 \ + rapidsai/cuvs-bench-cpu:26.06a-py3.13 \ "--dataset deep-image-96-angular" \ "--normalize" \ "--algorithms hnswlib --batch-size 10 -k 10" \ @@ -349,7 +349,7 @@ All of the `cuvs-bench` images contain the Conda packages, so they can be used d --entrypoint /bin/bash \ --workdir /data/benchmarks \ -v $DATA_FOLDER:/data/benchmarks \ - rapidsai/cuvs-bench:26.06-cuda12.9-py3.13 + rapidsai/cuvs-bench:26.06a-cuda12-py3.13 This will drop you into a command line in the container, with the `cuvs-bench` python package ready to use, as described in the `Running the benchmarks`_ section above: