logo
ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1
linux/amd64 ghcr.io

该镜像属于Kubeflow生态系统，是用于PyTorch模型训练的训练器镜像，支持基于TorchTune工具进行模型训练任务，适用于Kubeflow环境中的机器学习训练工作流场景。

10
浏览次数
8.92GB
镜像大小
国内镜像
swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1
源镜像
ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1
镜像ID
sha256:b936475893935d52f10e0c9c00024910762bf1f01e51311508bde58322aefd26
镜像 TAG
v2.2.1
镜像大小
8.92GB
平台架构
linux/amd64
镜像源
ghcr.io
CMD
/bin/bash
启动入口
工作目录
/workspace
OS/平台
linux/amd64
镜像创建
2026-06-17T18:18:31.468627382Z
同步时间
2026-07-14 03:44
浏览量
10 次
贡献者
⚙️ 环境变量 5
KeyValue
PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 0
NVIDIA_VISIBLE_DEVICES=all 1
NVIDIA_DRIVER_CAPABILITIES=compute,utility 2
LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 3
PYTORCH_VERSION=2.9.1 4
🏷️ 镜像标签 3
KeyValue
nvidia_driver com.nvidia.volumes.needed
ubuntu org.opencontainers.image.ref.name
22.04 org.opencontainers.image.version
🛡️ 镜像安全扫描
ubuntu 22.04 Trivy 2026-07-14 03:45 查看完整报告
408
低危 LOW
2831
中危 MEDIUM
260
高危 HIGH
21
严重 CRITICAL
受影响目标 (2)
ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1 (ubuntu 22.04) ubuntu Python python-pkg
无权限下载？点我修复 生成 Docker Run 命令 生成 Kubernetes YAML

Docker拉取命令 

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1  ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1

Containerd拉取命令 

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1  ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1

Shell快速替换命令 

sed -i 's#ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1#' deployment.yaml

Ansible快速分发-Docker 

#ansible k8s -m shell -a 'docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1  ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1'

Ansible快速分发-Containerd 

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1  ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1'

镜像构建历史 


# 2026-06-18 02:18:31  717.85MB 执行命令并创建新的镜像层
RUN /bin/sh -c pip install -r requirements.txt # buildkit
                        
# 2026-06-18 02:18:16  70.00B 复制新文件或目录到容器中
COPY cmd/trainers/torchtune/requirements.txt . # buildkit
                        
# 2026-06-18 02:18:16  235.81MB 执行命令并创建新的镜像层
RUN /bin/sh -c apt update && apt-get install -y --no-install-recommends build-essential     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2026-06-18 02:18:05  0.00B 设置工作目录为/workspace
WORKDIR /workspace
                        
# 2025-11-13 03:30:31  0.00B 设置工作目录为/workspace
WORKDIR /workspace
                        
# 2025-11-13 03:30:31  0.00B 设置环境变量 PYTORCH_VERSION
ENV PYTORCH_VERSION=2.9.1
                        
# 2025-11-13 03:30:31  0.00B 设置环境变量 PATH
ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2025-11-13 03:30:31  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2025-11-13 03:30:31  0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
                        
# 2025-11-13 03:30:31  0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
                        
# 2025-11-13 03:30:31  0.00B 设置环境变量 PATH
ENV PATH=/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2025-11-13 03:30:31  0.00B 执行命令并创建新的镜像层
RUN |4 PYTORCH_VERSION=2.9.1 TRITON_VERSION= TARGETPLATFORM=linux/amd64 CUDA_VERSION=12.8.1 /bin/sh -c if test -n "${TRITON_VERSION}" -a "${TARGETPLATFORM}" != "linux/arm64"; then         DEBIAN_FRONTEND=noninteractive apt install -y --no-install-recommends gcc;         rm -rf /var/lib/apt/lists/*;     fi # buildkit
                        
# 2025-11-13 03:30:31  7.87GB 复制新文件或目录到容器中
COPY /opt/conda /opt/conda # buildkit
                        
# 2025-11-13 03:25:44  25.98MB 执行命令并创建新的镜像层
RUN |4 PYTORCH_VERSION=2.9.1 TRITON_VERSION= TARGETPLATFORM=linux/amd64 CUDA_VERSION=12.8.1 /bin/sh -c apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends         ca-certificates         libjpeg-dev         libpng-dev         && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2025-11-13 03:25:44  0.00B 添加元数据标签
LABEL com.nvidia.volumes.needed=nvidia_driver
                        
# 2025-11-13 03:25:44  0.00B 定义构建参数
ARG CUDA_VERSION=12.8.1
                        
# 2025-11-13 03:25:44  0.00B 定义构建参数
ARG TARGETPLATFORM=linux/amd64
                        
# 2025-11-13 03:25:44  0.00B 定义构建参数
ARG TRITON_VERSION=
                        
# 2025-11-13 03:25:44  0.00B 定义构建参数
ARG PYTORCH_VERSION=2.9.1
                        
# 2025-10-01 15:05:10  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2025-10-01 15:05:09  77.87MB 
/bin/sh -c #(nop) ADD file:32d41b6329e8f89fa4ac92ef97c04b7cfd5e90fb74e1509c3e27d7c91195b7c7 in / 
                        
# 2025-10-01 15:05:07  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=22.04
                        
# 2025-10-01 15:05:07  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2025-10-01 15:05:07  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2025-10-01 15:05:07  0.00B 
/bin/sh -c #(nop)  ARG RELEASE

镜像信息 

{
    "Id": "sha256:b936475893935d52f10e0c9c00024910762bf1f01e51311508bde58322aefd26",
    "RepoTags": [
        "ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1"
    ],
    "RepoDigests": [
        "ghcr.io/kubeflow/trainer/torchtune-trainer@sha256:aef64824d274a79d87e91c39a0d1b042a52576dfb3980ecd99f174d892855a71",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/kubeflow/trainer/torchtune-trainer@sha256:8982b453eee19a890e8db41e295b2466f66835be54e334b5b993de0d47406b43"
    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2026-06-17T18:18:31.468627382Z",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "PYTORCH_VERSION=2.9.1"
        ],
        "Cmd": [
            "/bin/bash"
        ],
        "Image": "",
        "Volumes": null,
        "WorkingDir": "/workspace",
        "Entrypoint": null,
        "OnBuild": null,
        "Labels": {
            "com.nvidia.volumes.needed": "nvidia_driver",
            "org.opencontainers.image.ref.name": "ubuntu",
            "org.opencontainers.image.version": "22.04"
        }
    },
    "Architecture": "amd64",
    "Os": "linux",
    "Size": 8924621770,
    "GraphDriver": {
        "Data": {
            "LowerDir": "/var/lib/docker/overlay2/5d11d770783ed4d6d56782e3f1c873d40a53e557efe3bb1ffc09c217193ca1c1/diff:/var/lib/docker/overlay2/8fbde2cfe3774f13eb548423e14a24294e5ebfea64e09f6ec1a4a4ffd7562619/diff:/var/lib/docker/overlay2/4f59f349945c56864b5c2db186c4efc865cc61454c85b8fb5a8a2b207e176178/diff:/var/lib/docker/overlay2/d837c3a9594f4dfe9ab60d65b383b4a4c86b30512fd311c46db7ab18045f7cb6/diff:/var/lib/docker/overlay2/787dc0abfea5d795724bb8369e8594a137576a9b7bc443b8e475e18c674ce990/diff:/var/lib/docker/overlay2/90ad0d942dda8732b6bf754cc8c6fe3db7b0c9d0484eac7c6c627e10946a98fa/diff:/var/lib/docker/overlay2/8eefc52093ebcb7f775d5fe61d4b3aaeb8920b03db210595f4d1a6ede3510359/diff:/var/lib/docker/overlay2/1e2fafcbf1d27fe7b8fff75c3690185a7d400c10defc1d41a920b65ab101414f/diff",
            "MergedDir": "/var/lib/docker/overlay2/9026f54d8f577434811c0ce4f511b8ddf8af04bed891cd6855eb60c3e7633de8/merged",
            "UpperDir": "/var/lib/docker/overlay2/9026f54d8f577434811c0ce4f511b8ddf8af04bed891cd6855eb60c3e7633de8/diff",
            "WorkDir": "/var/lib/docker/overlay2/9026f54d8f577434811c0ce4f511b8ddf8af04bed891cd6855eb60c3e7633de8/work"
        },
        "Name": "overlay2"
    },
    "RootFS": {
        "Type": "layers",
        "Layers": [
            "sha256:767e56ba346ae714b6e6b816baa839051145ed78cfa0e4524a86cc287b0c4b00",
            "sha256:96bd405616abf736648a20f6d2df39dc78f7d9dff8e92dbaa3dbda4c2544826b",
            "sha256:64e10de232400a391cfa6739cd39b6bb6713369801858537a7f9d1e2ee8f878b",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:e86808397b1b613c1513884ea92b79b8711a1ec5e9ea92caebcac7a2bd0fa997",
            "sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
            "sha256:d91244b80e88fdca8587dc5aa2d7b6b030f9c6d621536ddc75ef7985a48643e4",
            "sha256:2ebca93059e4abc4cbde6a72d8018864117b209e8dce6f7a7ab0b36a95bac983",
            "sha256:83bed357e803a557226567d36914824a6690f741af3d48666572980945476576"
        ]
    },
    "Metadata": {
        "LastTagTime": "2026-07-14T03:43:45.858682275+08:00"
    }
}

更多版本

ghcr.io/kubeflow/trainer/torchtune-trainer:v2.2.1

linux/amd64 ghcr.io8.92GB2026-07-14 03:44
9
0 点赞 0 收藏镜像 Run 生成 Docker Run 命令 K8s 生成 Kubernetes YAML 回到顶部
检测到您正在使用广告拦截插件，本站为公益站点，依赖广告维持运转 🙏 查看如何关闭 ×