镜像构建历史
# 2024-07-23 15:17:56 10.75KB 执行命令并创建新的镜像层
RUN |3 WHEEL_PATH=.whl/ray-2.33.0-cp311-cp311-manylinux2014_x86_64.whl FIND_LINKS_PATH=.whl CONSTRAINTS_FILE=requirements_compiled.txt /bin/bash -c $HOME/anaconda3/bin/pip freeze > /home/ray/pip-freeze.txt # buildkit
# 2024-07-23 15:17:55 349.75MB 执行命令并创建新的镜像层
RUN |3 WHEEL_PATH=.whl/ray-2.33.0-cp311-cp311-manylinux2014_x86_64.whl FIND_LINKS_PATH=.whl CONSTRAINTS_FILE=requirements_compiled.txt /bin/bash -c $HOME/anaconda3/bin/pip --no-cache-dir install -c $CONSTRAINTS_FILE `basename $WHEEL_PATH`[all] --find-links $FIND_LINKS_PATH && sudo rm `basename $WHEEL_PATH` # buildkit
# 2024-07-23 15:17:35 92.69MB 复制新文件或目录到容器中
COPY .whl .whl # buildkit
# 2024-07-23 15:17:34 64.96MB 复制新文件或目录到容器中
COPY .whl/ray-2.33.0-cp311-cp311-manylinux2014_x86_64.whl . # buildkit
# 2024-07-23 15:17:33 63.11KB 复制新文件或目录到容器中
COPY requirements_compiled.txt ./ # buildkit
# 2024-07-23 15:17:33 0.00B 定义构建参数
ARG CONSTRAINTS_FILE=requirements_compiled.txt
# 2024-07-23 15:17:33 0.00B 定义构建参数
ARG FIND_LINKS_PATH=.whl
# 2024-07-23 15:17:33 0.00B 定义构建参数
ARG WHEEL_PATH
# 2024-07-22 17:30:41 0.00B 执行命令并创建新的镜像层
RUN /bin/bash -c python -c "import tensorflow_probability" # buildkit
# 2024-07-22 17:30:40 10.60KB 执行命令并创建新的镜像层
RUN /bin/bash -c $HOME/anaconda3/bin/pip freeze > /home/ray/pip-freeze.txt # buildkit
# 2024-07-22 17:30:39 11.41GB 执行命令并创建新的镜像层
RUN /bin/bash -c sudo chmod +x install-ml-docker-requirements.sh && ./install-ml-docker-requirements.sh # buildkit
# 2024-07-22 17:21:33 1.98KB 复制新文件或目录到容器中
COPY *install-ml-docker-requirements.sh docker/ray-ml/*install-ml-docker-requirements.sh ./ # buildkit
# 2024-07-22 17:21:33 63.11KB 复制新文件或目录到容器中
COPY *requirements_compiled.txt python/*requirements_compiled.txt ./ # buildkit
# 2024-07-22 17:21:33 6.68KB 复制新文件或目录到容器中
COPY *requirements.txt python/*requirements.txt python/requirements/ml/*requirements.txt python/requirements/docker/*requirements.txt ./ # buildkit
# 2024-07-22 17:17:19 0.00B 设置工作目录为/home/ray
WORKDIR /home/ray
# 2024-07-22 17:17:19 1.35GB 执行命令并创建新的镜像层
RUN |7 BASE_IMAGE=nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04 AUTOSCALER=autoscaler DEBIAN_FRONTEND=noninteractive PYTHON_VERSION=3.11 HOSTTYPE=x86_64 RAY_UID=1000 RAY_GID=100 /bin/bash -c sudo apt-get update -y && sudo apt-get upgrade -y && sudo apt-get install -y git libjemalloc-dev wget cmake g++ zlib1g-dev $(if [ "$AUTOSCALER" = "autoscaler" ]; then echo tmux screen rsync netbase openssh-client gnupg; fi) && wget --quiet "https://repo.anaconda.com/miniconda/Miniconda3-py311_24.4.0-0-Linux-${HOSTTYPE}.sh" -O /tmp/miniconda.sh && /bin/bash /tmp/miniconda.sh -b -u -p $HOME/anaconda3 && $HOME/anaconda3/bin/conda init && echo 'export PATH=$HOME/anaconda3/bin:$PATH' >> /home/ray/.bashrc && rm /tmp/miniconda.sh && $HOME/anaconda3/bin/conda install -y libgcc-ng python=$PYTHON_VERSION && $HOME/anaconda3/bin/conda install -y -c conda-forge libffi=3.4.2 && $HOME/anaconda3/bin/conda clean -y --all && $HOME/anaconda3/bin/pip install --no-cache-dir flatbuffers cython==0.29.37 numpy\>=1.20 psutil && $HOME/anaconda3/bin/pip uninstall -y dask && sudo apt-get autoremove -y cmake zlib1g-dev $(if [[ "$BASE_IMAGE" == "ubuntu:22.04" && "$HOSTTYPE" == "x86_64" ]]; then echo g++; fi) && sudo rm -rf /var/lib/apt/lists/* && sudo apt-get clean && (if [ "$AUTOSCALER" = "autoscaler" ]; then $HOME/anaconda3/bin/pip --no-cache-dir install "redis>=3.5.0,<4.0.0" "six==1.13.0" "boto3==1.26.76" "pyOpenSSL==22.1.0" "cryptography==38.0.1" "google-api-python-client==1.7.8" "google-oauth" "azure-cli-core==2.40.0" "azure-identity==1.10.0" "azure-mgmt-compute==23.1.0" "azure-mgmt-network==19.0.0" "azure-mgmt-resource==20.0.0" "msrestazure==0.6.4"; fi;) # buildkit
# 2024-07-22 17:15:54 0.00B
SHELL [/bin/bash -c]
# 2024-07-22 17:15:54 0.00B 设置环境变量 HOME
ENV HOME=/home/ray
# 2024-07-22 17:15:54 0.00B 指定运行容器时使用的用户
USER 1000
# 2024-07-22 17:15:54 7.20MB 执行命令并创建新的镜像层
RUN |7 BASE_IMAGE=nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04 AUTOSCALER=autoscaler DEBIAN_FRONTEND=noninteractive PYTHON_VERSION=3.11 HOSTTYPE=x86_64 RAY_UID=1000 RAY_GID=100 /bin/sh -c apt-get update -y && apt-get install -y sudo tzdata && useradd -ms /bin/bash -d /home/ray ray --uid $RAY_UID --gid $RAY_GID && usermod -aG sudo ray && echo 'ray ALL=NOPASSWD: ALL' >> /etc/sudoers && rm -rf /var/lib/apt/lists/* && apt-get clean # buildkit
# 2024-07-22 17:15:54 0.00B 定义构建参数
ARG RAY_GID=100
# 2024-07-22 17:15:54 0.00B 定义构建参数
ARG RAY_UID=1000
# 2024-07-22 17:15:54 0.00B 定义构建参数
ARG HOSTTYPE=x86_64
# 2024-07-22 17:15:54 0.00B 定义构建参数
ARG PYTHON_VERSION=3.8.16
# 2024-07-22 17:15:54 0.00B 定义构建参数
ARG DEBIAN_FRONTEND=noninteractive
# 2024-07-22 17:15:54 0.00B 设置环境变量 PATH
ENV PATH=/home/ray/anaconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# 2024-07-22 17:15:54 0.00B 设置环境变量 LANG
ENV LANG=C.UTF-8
# 2024-07-22 17:15:54 0.00B 设置环境变量 LC_ALL
ENV LC_ALL=C.UTF-8
# 2024-07-22 17:15:54 0.00B 设置环境变量 TZ
ENV TZ=America/Los_Angeles
# 2024-07-22 17:15:54 0.00B 定义构建参数
ARG AUTOSCALER=autoscaler
# 2024-07-22 17:15:54 0.00B 定义构建参数
ARG BASE_IMAGE
# 2023-11-10 15:16:45 2.37GB 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
# 2023-11-10 15:16:45 0.00B 添加元数据标签
LABEL com.nvidia.cudnn.version=8.9.6.50
# 2023-11-10 15:16:45 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2023-11-10 15:16:45 0.00B 定义构建参数
ARG TARGETARCH
# 2023-11-10 15:16:45 0.00B 设置环境变量 NV_CUDNN_PACKAGE_DEV
ENV NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.9.6.50-1+cuda11.8
# 2023-11-10 15:16:45 0.00B 设置环境变量 NV_CUDNN_PACKAGE
ENV NV_CUDNN_PACKAGE=libcudnn8=8.9.6.50-1+cuda11.8
# 2023-11-10 15:16:45 0.00B 设置环境变量 NV_CUDNN_PACKAGE_NAME
ENV NV_CUDNN_PACKAGE_NAME=libcudnn8
# 2023-11-10 15:16:45 0.00B 设置环境变量 NV_CUDNN_VERSION
ENV NV_CUDNN_VERSION=8.9.6.50
# 2023-11-10 14:55:21 0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs
# 2023-11-10 14:55:21 383.52KB 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} ${NV_LIBNCCL_DEV_PACKAGE_NAME} # buildkit
# 2023-11-10 14:55:17 4.72GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-cudart-dev-11-8=${NV_CUDA_CUDART_DEV_VERSION} cuda-command-line-tools-11-8=${NV_CUDA_LIB_VERSION} cuda-minimal-build-11-8=${NV_CUDA_LIB_VERSION} cuda-libraries-dev-11-8=${NV_CUDA_LIB_VERSION} cuda-nvml-dev-11-8=${NV_NVML_DEV_VERSION} ${NV_NVPROF_DEV_PACKAGE} ${NV_LIBNPP_DEV_PACKAGE} libcusparse-dev-11-8=${NV_LIBCUSPARSE_DEV_VERSION} ${NV_LIBCUBLAS_DEV_PACKAGE} ${NV_LIBNCCL_DEV_PACKAGE} ${NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
# 2023-11-10 14:55:17 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2023-11-10 14:55:17 0.00B 定义构建参数
ARG TARGETARCH
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE
ENV NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.15.5-1+cuda11.8
# 2023-11-10 14:55:17 0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.15.5-1
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_VERSION
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION=2.15.5-1
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_LIBNCCL_DEV_PACKAGE_NAME
ENV NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_NVPROF_DEV_PACKAGE
ENV NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-8=11.8.87-1
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_NVPROF_VERSION
ENV NV_NVPROF_VERSION=11.8.87-1
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE
ENV NV_CUDA_NSIGHT_COMPUTE_DEV_PACKAGE=cuda-nsight-compute-11-8=11.8.0-1
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_CUDA_NSIGHT_COMPUTE_VERSION
ENV NV_CUDA_NSIGHT_COMPUTE_VERSION=11.8.0-1
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE
ENV NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-8=11.11.3.6-1
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_LIBCUBLAS_DEV_PACKAGE_NAME
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-8
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_LIBCUBLAS_DEV_VERSION
ENV NV_LIBCUBLAS_DEV_VERSION=11.11.3.6-1
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_LIBNPP_DEV_PACKAGE
ENV NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-8=11.8.0.86-1
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_LIBNPP_DEV_VERSION
ENV NV_LIBNPP_DEV_VERSION=11.8.0.86-1
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_LIBCUSPARSE_DEV_VERSION
ENV NV_LIBCUSPARSE_DEV_VERSION=11.7.5.86-1
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_NVML_DEV_VERSION
ENV NV_NVML_DEV_VERSION=11.8.86-1
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_CUDA_CUDART_DEV_VERSION
ENV NV_CUDA_CUDART_DEV_VERSION=11.8.89-1
# 2023-11-10 14:55:17 0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.8.0-1
# 2023-11-10 14:42:37 0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
# 2023-11-10 14:42:37 0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
# 2023-11-10 14:42:37 2.53KB 复制新文件或目录到容器中
COPY nvidia_entrypoint.sh /opt/nvidia/ # buildkit
# 2023-11-10 14:42:37 3.06KB 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
# 2023-11-10 14:42:37 260.16KB 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} ${NV_LIBNCCL_PACKAGE_NAME} # buildkit
# 2023-11-10 14:42:36 2.41GB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends cuda-libraries-11-8=${NV_CUDA_LIB_VERSION} ${NV_LIBNPP_PACKAGE} cuda-nvtx-11-8=${NV_NVTX_VERSION} libcusparse-11-8=${NV_LIBCUSPARSE_VERSION} ${NV_LIBCUBLAS_PACKAGE} ${NV_LIBNCCL_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
# 2023-11-10 14:42:36 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2023-11-10 14:42:36 0.00B 定义构建参数
ARG TARGETARCH
# 2023-11-10 14:42:36 0.00B 设置环境变量 NV_LIBNCCL_PACKAGE
ENV NV_LIBNCCL_PACKAGE=libnccl2=2.15.5-1+cuda11.8
# 2023-11-10 14:42:36 0.00B 设置环境变量 NCCL_VERSION
ENV NCCL_VERSION=2.15.5-1
# 2023-11-10 14:42:36 0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_VERSION
ENV NV_LIBNCCL_PACKAGE_VERSION=2.15.5-1
# 2023-11-10 14:42:36 0.00B 设置环境变量 NV_LIBNCCL_PACKAGE_NAME
ENV NV_LIBNCCL_PACKAGE_NAME=libnccl2
# 2023-11-10 14:42:36 0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE
ENV NV_LIBCUBLAS_PACKAGE=libcublas-11-8=11.11.3.6-1
# 2023-11-10 14:42:36 0.00B 设置环境变量 NV_LIBCUBLAS_VERSION
ENV NV_LIBCUBLAS_VERSION=11.11.3.6-1
# 2023-11-10 14:42:36 0.00B 设置环境变量 NV_LIBCUBLAS_PACKAGE_NAME
ENV NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-8
# 2023-11-10 14:42:36 0.00B 设置环境变量 NV_LIBCUSPARSE_VERSION
ENV NV_LIBCUSPARSE_VERSION=11.7.5.86-1
# 2023-11-10 14:42:36 0.00B 设置环境变量 NV_LIBNPP_PACKAGE
ENV NV_LIBNPP_PACKAGE=libnpp-11-8=11.8.0.86-1
# 2023-11-10 14:42:36 0.00B 设置环境变量 NV_LIBNPP_VERSION
ENV NV_LIBNPP_VERSION=11.8.0.86-1
# 2023-11-10 14:42:36 0.00B 设置环境变量 NV_NVTX_VERSION
ENV NV_NVTX_VERSION=11.8.86-1
# 2023-11-10 14:42:36 0.00B 设置环境变量 NV_CUDA_LIB_VERSION
ENV NV_CUDA_LIB_VERSION=11.8.0-1
# 2023-11-10 14:37:16 0.00B 设置环境变量 NVIDIA_DRIVER_CAPABILITIES
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
# 2023-11-10 14:37:16 0.00B 设置环境变量 NVIDIA_VISIBLE_DEVICES
ENV NVIDIA_VISIBLE_DEVICES=all
# 2023-11-10 14:37:16 17.29KB 复制新文件或目录到容器中
COPY NGC-DL-CONTAINER-LICENSE / # buildkit
# 2023-11-10 14:37:16 0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
# 2023-11-10 14:37:16 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
# 2023-11-10 14:37:16 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
# 2023-11-10 14:37:16 150.67MB 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-11-8=${NV_CUDA_CUDART_VERSION} ${NV_CUDA_COMPAT_PACKAGE} && rm -rf /var/lib/apt/lists/* # buildkit
# 2023-11-10 14:37:01 0.00B 设置环境变量 CUDA_VERSION
ENV CUDA_VERSION=11.8.0
# 2023-11-10 14:37:01 10.56MB 执行命令并创建新的镜像层
RUN |1 TARGETARCH=amd64 /bin/sh -c apt-get update && apt-get install -y --no-install-recommends gnupg2 curl ca-certificates && curl -fsSLO https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/${NVARCH}/cuda-keyring_1.0-1_all.deb && dpkg -i cuda-keyring_1.0-1_all.deb && apt-get purge --autoremove -y curl && rm -rf /var/lib/apt/lists/* # buildkit
# 2023-11-10 14:37:01 0.00B 添加元数据标签
LABEL maintainer=NVIDIA CORPORATION <cudatools@nvidia.com>
# 2023-11-10 14:37:01 0.00B 定义构建参数
ARG TARGETARCH
# 2023-11-10 14:37:01 0.00B 设置环境变量 NV_CUDA_COMPAT_PACKAGE
ENV NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-8
# 2023-11-10 14:37:01 0.00B 设置环境变量 NV_CUDA_CUDART_VERSION
ENV NV_CUDA_CUDART_VERSION=11.8.89-1
# 2023-11-10 14:37:01 0.00B 设置环境变量 NVIDIA_REQUIRE_CUDA brand brand brand brand brand brand brand brand brand brand
ENV NVIDIA_REQUIRE_CUDA=cuda>=11.8 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
# 2023-11-10 14:37:01 0.00B 设置环境变量 NVARCH
ENV NVARCH=x86_64
# 2023-10-05 15:33:32 0.00B
/bin/sh -c #(nop) CMD ["/bin/bash"]
# 2023-10-05 15:33:32 77.82MB
/bin/sh -c #(nop) ADD file:63d5ab3ef0aab308c0e71cb67292c5467f60deafa9b0418cbb220affcd078444 in /
# 2023-10-05 15:33:30 0.00B
/bin/sh -c #(nop) LABEL org.opencontainers.image.version=22.04
# 2023-10-05 15:33:30 0.00B
/bin/sh -c #(nop) LABEL org.opencontainers.image.ref.name=ubuntu
# 2023-10-05 15:33:30 0.00B
/bin/sh -c #(nop) ARG LAUNCHPAD_BUILD_ARCH
# 2023-10-05 15:33:30 0.00B
/bin/sh -c #(nop) ARG RELEASE
镜像信息
{
"Id": "sha256:61feeac8814edc3f406d9a29a2ee0c3ed71ea2f3c60d3bace48950c1ff588742",
"RepoTags": [
"rayproject/ray-ml:2.33.0.914af0-py311",
"swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray-ml:2.33.0.914af0-py311"
],
"RepoDigests": [
"rayproject/ray-ml@sha256:b58d530020601ae694bfb87b6fa9a479e9bdbbdae4d0e605cb36d2608600041f",
"swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/rayproject/ray-ml@sha256:b58d530020601ae694bfb87b6fa9a479e9bdbbdae4d0e605cb36d2608600041f"
],
"Parent": "",
"Comment": "buildkit.dockerfile.v0",
"Created": "2024-07-23T07:17:56.910532179Z",
"Container": "",
"ContainerConfig": null,
"DockerVersion": "",
"Author": "",
"Config": {
"Hostname": "",
"Domainname": "",
"User": "1000",
"AttachStdin": false,
"AttachStdout": false,
"AttachStderr": false,
"Tty": false,
"OpenStdin": false,
"StdinOnce": false,
"Env": [
"PATH=/home/ray/anaconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin",
"NVARCH=x86_64",
"NVIDIA_REQUIRE_CUDA=cuda\u003e=11.8 brand=tesla,driver\u003e=470,driver\u003c471 brand=unknown,driver\u003e=470,driver\u003c471 brand=nvidia,driver\u003e=470,driver\u003c471 brand=nvidiartx,driver\u003e=470,driver\u003c471 brand=geforce,driver\u003e=470,driver\u003c471 brand=geforcertx,driver\u003e=470,driver\u003c471 brand=quadro,driver\u003e=470,driver\u003c471 brand=quadrortx,driver\u003e=470,driver\u003c471 brand=titan,driver\u003e=470,driver\u003c471 brand=titanrtx,driver\u003e=470,driver\u003c471",
"NV_CUDA_CUDART_VERSION=11.8.89-1",
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