Skip to main content

docker-build

Build a CUDA 13.0 or CUDA 12.8 LMDeploy Docker image and push it to the inner registry.

Informations de source

Dépôt
InternLM/lmdeploy
Dernière activité de la source
10 août 2026 à 10:47
Langue détectée de SKILL.md
anglais
Étoiles
8 106
Forks
768

Options d'installation

Le prompt qui vérifie d'abord la source est sélectionné par défaut. Vous pouvez passer à une commande directe ou télécharger une copie locale.

Vérifiez les fichiers source

Lisez SKILL.md et les fichiers associés affichés par SkillsMP avant de décider de l'installer.

Affichage de SKILL.md

SKILL.md
Instructions source · Aperçu en lecture seule
name
docker-build
description
Build a CUDA 13.0 or CUDA 12.8 LMDeploy Docker image and push it to the inner registry.
disable-model-invocation
true
# Docker Build & Push Build an LMDeploy Docker image and push it to the inner registry. ## Prerequisites Before starting, verify all three environment variables are set: ```bash echo $LMDEPLOY_REGISTRY # inner registry server address echo $REGISTRY_USER # registry login username test -n "$REGISTRY_PASSWORD" && echo "<set>" || echo "<missing>" # registry login password ``` If any are missing, stop and tell the user to set them before proceeding. ## 1. Select CUDA version Ask the user which public CUDA image variant to build: - `cu13.0` (default) — builds from the canonical `cu130` Docker stages - `cu12.8` — builds from the canonical `cu128` Docker stages Set the public tag suffix and corresponding Docker build target: ```bash CUDA_TAG_SUFFIX=${CUDA_TAG_SUFFIX:-cu13.0} case "${CUDA_TAG_SUFFIX}" in cu13.0) CUDA_BUILD_TARGET=cu130 ;; cu12.8) CUDA_BUILD_TARGET=cu128 ;; *) echo "Unsupported CUDA image variant: ${CUDA_TAG_SUFFIX}" >&2; exit 1 ;; esac ``` Do not pass `cu13.0` or `cu12.8` directly to `docker/Dockerfile`. Its canonical stage names are `cu130` and `cu128`. ## 2. Determine image tag ```bash BRANCH=$(git branch --show-current | sed 's/[^a-zA-Z0-9._-]/-/g') SHA=$(git rev-parse --short=7 HEAD) TAG="${BRANCH}-${SHA}-${CUDA_TAG_SUFFIX}" IMAGE="${LMDEPLOY_REGISTRY}/ailab-puyu-puyu_gpu/lmdeploy-dev:${TAG}" ``` Print the computed image name so the user can confirm. ## 3. Build Ask the user which build mode: - **patch** (default) — uses `docker/Dockerfile_patch`, fast overlay on existing image - **full** — uses `docker/Dockerfile`, full multi-stage build from scratch ### Patch build (default) ```bash BASE_IMAGE=${BASE_IMAGE:-openmmlab/lmdeploy:latest-${CUDA_TAG_SUFFIX}} docker build -f docker/Dockerfile_patch \ --build-arg BASE_IMAGE="${BASE_IMAGE}" \ --build-arg BACKEND=pytorch \ --build-arg http_proxy=${http_proxy:-} \ --build-arg https_proxy=${https_proxy:-} \ --build-arg no_proxy=${no_proxy:-} \ -t "${IMAGE}" \ . ``` User can override: - `BASE_IMAGE` — defaults to `openmmlab/lmdeploy:latest-${CUDA_TAG_SUFFIX}` - `BACKEND` — default `pytorch`; set to `turbomind` to include TurboMind C++ extension ### Full build ```bash docker build -f docker/Dockerfile \ --build-arg CUDA_VERSION="${CUDA_BUILD_TARGET}" \ --build-arg http_proxy=${http_proxy:-} \ --build-arg https_proxy=${https_proxy:-} \ --build-arg no_proxy=${no_proxy:-} \ -t "${IMAGE}" \ . ``` `CUDA_BUILD_TARGET` must be the canonical target mapped from the selected public CUDA variant. ### Verify ```bash docker images "${IMAGE}" ``` ## 4. Push Skip this step if the user only wants a local build. ### Login ```bash echo "${REGISTRY_PASSWORD}" | docker login "${LMDEPLOY_REGISTRY}" -u "${REGISTRY_USER}" --password-stdin ``` ### Push ```bash docker push "${IMAGE}" ``` Confirm success via exit code.
Voir sur GitHub