remove docs references to cuvs-bench-datasets, install a C compiler in pre-commit env (#1736)

## Updates docs

RAPIDS used to publish a `rapidsai/cuvs-bench-datasets` container image, essentially `rapidsai/cuvs-bench` with some benchmarking datasets pre-downloaded.

`rapidsai/cuvs-bench-datasets` was last published over a year ago (rapidsai/docker#725) and is set to be abandoned.

This removes references to it in documentation.

## Installs a C compiler for `pre-commit`

Looks like the `cargo-fmt` hook was relying on the C compilers removed from the `rapidsai/ci-conda` images in rapidsai/ci-imgs#353

This fixes that by explicitly declaring that dependency in the conda environment used for `pre-commit` in CI.

Authors:
  - James Lamb (https://github.com/jameslamb)

Approvers:
  - Dante Gama Dessavre (https://github.com/dantegd)
  - Corey J. Nolet (https://github.com/cjnolet)
  - Bradley Dice (https://github.com/bdice)

URL: #1736

Author: jameslamb

ci/check_style.sh

@@ -1,5 +1,5 @@
 #!/bin/bash
-# SPDX-FileCopyrightText: Copyright (c) 2020-2025, NVIDIA CORPORATION.
+# SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
 # SPDX-License-Identifier: Apache-2.0
 
 set -euo pipefail
@@ -15,8 +15,11 @@ rapids-dependency-file-generator \
   --file-key checks \
   --matrix "cuda=${RAPIDS_CUDA_VERSION%.*};arch=$(arch);py=${RAPIDS_PY_VERSION}" | tee env.yaml
 
+# temporarily allow unbound variables for conda activation scripts
+set +u
 rapids-mamba-retry env create --yes -f env.yaml -n checks
 conda activate checks
+set -u
 
 # get config for cmake-format checks
 RAPIDS_BRANCH="$(cat "$(dirname "$(realpath "${BASH_SOURCE[0]}")")"/../RAPIDS_BRANCH)"

dependencies.yaml

@@ -275,6 +275,10 @@ dependencies:
       - output_types: [conda, requirements]
         packages:
           - pre-commit
+      # cargo-fmt pre-commit hook requires a C compiler
+      - output_types: [conda]
+        packages:
+          - c-compiler
   clang:
     common:
       - output_types: conda

docs/source/cuvs_bench/index.rst

@@ -80,7 +80,6 @@ Docker
 We provide images for GPU enabled systems, as well as systems without a GPU. The following images are available:
 
 - `cuvs-bench`: Contains GPU and CPU benchmarks, can run all algorithms supported. Will download million-scale datasets as required. Best suited for users that prefer a smaller container size for GPU based systems. Requires the NVIDIA Container Toolkit to run GPU algorithms, can run CPU algorithms without it.
-- `cuvs-bench-datasets`: Contains the GPU and CPU benchmarks with million-scale datasets already included in the container. Best suited for users that want to run multiple million scale datasets already included in the image.
 - `cuvs-bench-cpu`: Contains only CPU benchmarks with minimal size. Best suited for users that want the smallest containers to reproduce benchmarks on systems without a GPU.
 
 Nightly images are located in `dockerhub <https://hub.docker.com/r/rapidsai/cuvs-bench/tags>`_.
@@ -97,8 +96,7 @@ The CUDA and python versions can be changed for the supported values:
 
 You can see the exact versions as well in the dockerhub site:
 - `cuVS bench images <https://hub.docker.com/r/rapidsai/cuvs-bench/tags>`_
-- `cuVS bench with pre-loaded million-scale datasets images <https://hub.docker.com/r/rapidsai/cuvs-bench-cpu/tags>`_
-- `cuVS bench CPU only images <https://hub.docker.com/r/rapidsai/cuvs-bench-datasets/tags>`_
+- `cuVS bench CPU only images <https://hub.docker.com/r/rapidsai/cuvs-bench-cpu/tags>`_
 
 **Note:** GPU containers use the CUDA toolkit from inside the container, the only requirement is a driver installed on the host machine that supports that version. So, for example, CUDA 11.8 containers can run in systems with a CUDA 12.x capable driver. Please also note that the Nvidia-Docker runtime from the `Nvidia Container Toolkit <https://github.com/NVIDIA/nvidia-docker>`_ is required to use GPUs inside docker containers.
 
@@ -251,7 +249,7 @@ Usage of the above command is as follows:
    - Description
 
  * - `rapidsai/cuvs-bench:26.04-cuda12.9-py3.13`
-   - Image to use. Can be either `cuvs-bench` or `cuvs-bench-datasets`
+   - Image to use. See "Docker" section for links to lists of available tags.
 
  * - `"--dataset deep-image-96-angular"`
    - Dataset name