镜像构建历史
# 2024-04-10 15:47:14 0.00B 指定运行容器时使用的用户
USER root
# 2024-04-10 15:47:14 80.82MB 执行命令并创建新的镜像层
RUN |1 DEBIAN_FRONTEND=noninteractive /bin/bash --login -c . /opt/conda/etc/profile.d/conda.sh && echo "source activate musev" >> ~/.bashrc && conda activate musev && conda env list && pip --no-cache-dir install cuid gradio==4.12 spaces # buildkit
# 2024-04-10 15:47:14 0.00B
SHELL [/bin/bash --login -c]
# 2024-04-10 15:47:14 0.00B 指定运行容器时使用的用户
USER root
# 2024-04-10 15:47:14 0.00B 定义构建参数
ARG DEBIAN_FRONTEND=noninteractive
# 2024-04-10 15:47:14 0.00B 添加元数据标签
LABEL Description=musev gpu runtime image, base docker is pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel
# 2024-04-10 15:47:14 0.00B 添加元数据标签
LABEL Email=anchorxia@tencent.com
# 2024-04-10 15:47:14 0.00B 添加元数据标签
LABEL MAINTAINER=anchorxia
# 2024-03-21 23:30:32 0.00B 指定运行容器时使用的用户
USER root
# 2024-03-21 23:30:32 12.66GB 执行命令并创建新的镜像层
RUN |1 DEBIAN_FRONTEND=noninteractive /bin/bash --login -c conda create -n musev python=3.10.6 -y && . /opt/conda/etc/profile.d/conda.sh && echo "source activate musev" >> ~/.bashrc && conda activate musev && pip install tensorflow==2.12.0 tensorboard==2.12.0 && pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cu118 && pip install ninja==1.11.1 && pip install --no-cache-dir transformers==4.33.1 bitsandbytes==0.41.1 decord==0.6.0 accelerate==0.22.0 xformers==0.0.21 omegaconf einops imageio==2.31.1 && pip install --no-cache-dir pandas h5py matplotlib modelcards==0.1.6 pynvml==11.5.0 black pytest moviepy==1.0.3 torch-tb-profiler==0.4.1 scikit-learn librosa ffmpeg easydict webp mediapipe==0.10.3 && pip install --no-cache-dir cython==3.0.2 easydict gdown infomap==2.7.1 insightface==0.7.3 ipython librosa==0.10.1 onnx==1.14.1 onnxruntime==1.15.1 onnxsim==0.4.33 opencv_python Pillow protobuf==3.20.3 pytube==15.0.0 PyYAML && pip install --no-cache-dir requests scipy six tqdm gradio==3.43.2 albumentations==1.3.1 opencv-contrib-python==4.8.0.76 imageio-ffmpeg==0.4.8 pytorch-lightning==2.0.8 test-tube==0.7.5 && pip install --no-cache-dir timm addict yapf prettytable safetensors==0.3.3 basicsr fvcore pycocotools wandb==0.15.10 wget ffmpeg-python && pip install --no-cache-dir streamlit webdataset kornia==0.7.0 open_clip_torch==2.20.0 streamlit-drawable-canvas==0.9.3 torchmetrics==1.1.1 && pip install --no-cache-dir invisible-watermark==0.1.5 gdown==4.5.3 ftfy==6.1.1 modelcards==0.1.6 && pip install ipywidgets==8.0.3 && python -m ipykernel install --user --name projectv --display-name "python(projectv)" && pip install --no-cache-dir matplotlib==3.6.2 redis==4.5.1 pydantic[dotenv]==1.10.2 loguru==0.6.0 IProgress==0.4 && pip install git+https://github.com/tencent-ailab/IP-Adapter.git && pip install -U openmim && mim install mmengine && mim install "mmcv>=2.0.1" && mim install "mmdet>=3.1.0" && mim install "mmpose>=1.1.0" && pip install --no-cache-dir markupsafe==2.0.1 # buildkit
# 2024-03-21 22:58:32 0.00B
SHELL [/bin/bash --login -c]
# 2024-03-21 22:58:32 524.57MB 执行命令并创建新的镜像层
RUN |1 DEBIAN_FRONTEND=noninteractive /bin/sh -c apt install -y wget git curl tmux cmake htop iotop git-lfs zip && apt install -y autojump && apt install -y libasound-dev portaudio19-dev libportaudio2 libportaudiocpp0 ffmpeg && apt clean # buildkit
# 2024-03-21 20:21:45 1.45GB 执行命令并创建新的镜像层
RUN |1 DEBIAN_FRONTEND=noninteractive /bin/sh -c apt -y update && apt -y upgrade # buildkit
# 2024-03-21 20:21:45 0.00B 指定运行容器时使用的用户
USER root
# 2024-03-21 20:21:45 0.00B 定义构建参数
ARG DEBIAN_FRONTEND=noninteractive
# 2024-03-21 20:21:45 0.00B 添加元数据标签
LABEL Description=gpu development image, from docker pull pytorch/pytorch:2.0.1-cuda11.7-cudnn8-devel
# 2024-03-21 20:21:45 0.00B 添加元数据标签
LABEL Email=anchorxia@tencent.com
# 2024-03-21 20:21:45 0.00B 添加元数据标签
LABEL MAINTAINER=anchorxia
# 2023-05-13 07:31:56 0.00B 设置工作目录为/workspace
WORKDIR /workspace
# 2023-05-13 07:31:56 0.00B 设置环境变量 PYTORCH_VERSION
ENV PYTORCH_VERSION=2.0.1
# 2023-05-13 07:31:56 0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
# 2023-05-13 07:31:56 0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
# 2023-05-13 07:31:56 0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
# 2023-05-13 07:31:56 0.00B 设置环境变量 PATH
ENV PATH=/opt/conda/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# 2023-05-13 07:31:56 0.00B 执行命令并创建新的镜像层
RUN |4 PYTORCH_VERSION=2.0.1 TRITON_VERSION= TARGETPLATFORM=linux/amd64 CUDA_VERSION=11.7.0 /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
# 2023-05-13 07:31:56 6.38GB 复制新文件或目录到容器中
COPY /opt/conda /opt/conda # buildkit
# 2023-05-13 07:25:22 3.25MB 执行命令并创建新的镜像层
RUN |4 PYTORCH_VERSION=2.0.1 TRITON_VERSION= TARGETPLATFORM=linux/amd64 CUDA_VERSION=11.7.0 /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
# 2023-05-13 07:25:22 0.00B 添加元数据标签
LABEL com.nvidia.volumes.needed=nvidia_driver
# 2023-05-13 07:25:22 0.00B 定义构建参数
ARG CUDA_VERSION
# 2023-05-13 07:25:22 0.00B 定义构建参数
ARG TARGETPLATFORM
# 2023-05-13 07:25:22 0.00B 定义构建参数
ARG TRITON_VERSION
# 2023-05-13 07:25:22 0.00B 定义构建参数
ARG PYTORCH_VERSION
# 2022-12-17 09:09:24 1.94GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends ${NV_CUDNN_PACKAGE} ${NV_CUDNN_PACKAGE_DEV} && apt-mark hold ${NV_CUDNN_PACKAGE_NAME} && rm -rf /var/lib/apt/lists/* # buildkit
# 2022-12-17 09:09:24 0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.5.0.96
# 2022-12-17 09:09:24 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2022-12-17 09:09:24 0.00B 定义构建参数
ARG TARGETARCH
# 2022-12-17 09:09:24 0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.5.0.96-1+cuda11.7
# 2022-12-17 09:09:24 0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.5.0.96-1+cuda11.7
# 2022-12-17 09:09:24 0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
# 2022-12-17 09:09:24 0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.5.0.96
# 2022-12-15 04:13:58 0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
# 2022-12-15 04:13:58 374.63KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_DEV_PACKAGE_NAME} ${NV_LIBNCCL_DEV_PACKAGE_NAME} # buildkit
# 2022-12-15 04:13:57 2.82GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends libtinfo5 libncursesw5 cuda-cudart-dev-11-7=${NV_CUDA_CUDART_DEV_VERSION} cuda-command-line-tools-11-7=${NV_CUDA_LIB_VERSION} cuda-minimal-build-11-7=${NV_CUDA_LIB_VERSION} cuda-libraries-dev-11-7=${NV_CUDA_LIB_VERSION} cuda-nvml-dev-11-7=${NV_NVML_DEV_VERSION} ${NV_NVPROF_DEV_PACKAGE} ${NV_LIBNPP_DEV_PACKAGE} libcusparse-dev-11-7=${NV_LIBCUSPARSE_DEV_VERSION} ${NV_LIBCUBLAS_DEV_PACKAGE} ${NV_LIBNCCL_DEV_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
# 2022-12-15 04:13:57 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2022-12-15 04:13:57 0.00B 定义构建参数
ARG TARGETARCH
# 2022-12-15 04:13:57 0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.13.4-1+cuda11.7
# 2022-12-15 04:13:57 0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.13.4-1
# 2022-12-15 04:13:57 0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.13.4-1
# 2022-12-15 04:13:57 0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
# 2022-12-15 04:13:57 0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-7=11.7.50-1
# 2022-12-15 04:13:57 0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=11.7.50-1
# 2022-12-15 04:13:57 0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-7=11.10.1.25-1
# 2022-12-15 04:13:57 0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-7
# 2022-12-15 04:13:57 0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=11.10.1.25-1
# 2022-12-15 04:13:57 0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-7=11.7.3.21-1
# 2022-12-15 04:13:57 0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=11.7.3.21-1
# 2022-12-15 04:13:57 0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=11.7.3.50-1
# 2022-12-15 04:13:57 0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=11.7.50-1
# 2022-12-15 04:13:57 0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=11.7.60-1
# 2022-12-15 04:13:57 0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.7.0-1
# 2022-12-15 04:03:03 0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
# 2022-12-15 04:03:03 0.00B 设置环境变量 NVIDIA_CUDA_END_OF_LIFE
ENV NVIDIA_CUDA_END_OF_LIFE=1
# 2022-12-15 04:03:03 0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
# 2022-12-15 04:03:03 2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
# 2022-12-15 04:03:03 3.04KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
# 2022-12-15 04:03:03 258.24KB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-mark hold ${NV_LIBCUBLAS_PACKAGE_NAME} ${NV_LIBNCCL_PACKAGE_NAME} # buildkit
# 2022-12-15 04:03:02 1.82GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-libraries-11-7=${NV_CUDA_LIB_VERSION} ${NV_LIBNPP_PACKAGE} cuda-nvtx-11-7=${NV_NVTX_VERSION} libcusparse-11-7=${NV_LIBCUSPARSE_VERSION} ${NV_LIBCUBLAS_PACKAGE} ${NV_LIBNCCL_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
# 2022-12-15 04:03:02 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2022-12-15 04:03:02 0.00B 定义构建参数
ARG TARGETARCH
# 2022-12-15 04:03:02 0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.13.4-1+cuda11.7
# 2022-12-15 04:03:02 0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.13.4-1
# 2022-12-15 04:03:02 0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.13.4-1
# 2022-12-15 04:03:02 0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
# 2022-12-15 04:03:02 0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-11-7=11.10.1.25-1
# 2022-12-15 04:03:02 0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=11.10.1.25-1
# 2022-12-15 04:03:02 0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-7
# 2022-12-15 04:03:02 0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=11.7.3.50-1
# 2022-12-15 04:03:02 0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-11-7=11.7.3.21-1
# 2022-12-15 04:03:02 0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=11.7.3.21-1
# 2022-12-15 04:03:02 0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=11.7.50-1
# 2022-12-15 04:03:02 0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.7.0-1
# 2022-12-15 03:58:37 0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
# 2022-12-15 03:58:37 0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
# 2022-12-15 03:58:37 16.05KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
# 2022-12-15 03:58:37 0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
# 2022-12-15 03:58:37 0.00B 设置环境变量 PATH
ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# 2022-12-15 03:58:37 46.00B 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf && echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf # buildkit
# 2022-12-15 03:58:37 119.68MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-cudart-11-7=${NV_CUDA_CUDART_VERSION} ${NV_CUDA_COMPAT_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
# 2022-12-15 03:58:22 0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=11.7.0
# 2022-12-15 03:58:22 18.28MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends gnupg2 curl ca-certificates && curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/${NVARCH}/3bf863cc.pub | apt-key add - && echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/${NVARCH} /" > /etc/apt/sources.list.d/cuda.list && apt-get purge --autoremove -y curl && rm -rf /var/lib/apt/lists/* # buildkit
# 2022-12-15 03:58:22 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2022-12-15 03:58:22 0.00B 定义构建参数
ARG TARGETARCH
# 2022-12-15 03:58:22 0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-7
# 2022-12-15 03:58:22 0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=11.7.60-1
# 2022-12-15 03:58:22 0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=11.7 brand=tesla,driver>=450,driver<451 brand=tesla,driver>=470,driver<471 brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471 brand=tesla,driver>=510,driver<511 brand=unknown,driver>=510,driver<511 brand=nvidia,driver>=510,driver<511 brand=nvidiartx,driver>=510,driver<511 brand=quadro,driver>=510,driver<511 brand=quadrortx,driver>=510,driver<511 brand=titan,driver>=510,driver<511 brand=titanrtx,driver>=510,driver<511 brand=geforce,driver>=510,driver<511 brand=geforcertx,driver>=510,driver<511
# 2022-12-15 03:58:22 0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
# 2022-12-09 09:20:21 0.00B
/bin/sh -c #(nop) CMD ["bash"]
# 2022-12-09 09:20:21 72.79MB
/bin/sh -c #(nop) ADD file:9d282119af0c42bc823c95b4192a3350cf2cad670622017356dd2e637762e425 in /
镜像信息
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"RepoTags": [
"anchorxia/musev:latest",
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],
"RepoDigests": [
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],
"Parent": "",
"Comment": "buildkit.dockerfile.v0",
"Created": "2024-04-10T15:47:14.90153929+08:00",
"Container": "",
"ContainerConfig": null,
"DockerVersion": "",
"Author": "",
"Config": {
"Hostname": "",
"Domainname": "",
"User": "root",
"AttachStdin": false,
"AttachStdout": false,
"AttachStderr": false,
"Tty": false,
"OpenStdin": false,
"StdinOnce": false,
"Env": [
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