docker.io/iseekyan/verl:app-verl0.5-transformers4.55.4-vllm0.10.0-mcore0.15.0-te2.7 linux/amd64

Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/iseekyan/verl:app-verl0.5-transformers4.55.4-vllm0.10.0-mcore0.15.0-te2.7
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/iseekyan/verl:app-verl0.5-transformers4.55.4-vllm0.10.0-mcore0.15.0-te2.7  docker.io/iseekyan/verl:app-verl0.5-transformers4.55.4-vllm0.10.0-mcore0.15.0-te2.7

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/iseekyan/verl:app-verl0.5-transformers4.55.4-vllm0.10.0-mcore0.15.0-te2.7
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/iseekyan/verl:app-verl0.5-transformers4.55.4-vllm0.10.0-mcore0.15.0-te2.7  docker.io/iseekyan/verl:app-verl0.5-transformers4.55.4-vllm0.10.0-mcore0.15.0-te2.7

Shell快速替换命令

sed -i 's#iseekyan/verl:app-verl0.5-transformers4.55.4-vllm0.10.0-mcore0.15.0-te2.7#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/iseekyan/verl:app-verl0.5-transformers4.55.4-vllm0.10.0-mcore0.15.0-te2.7#' deployment.yaml

Ansible快速分发-Docker

#ansible k8s -m shell -a 'docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/iseekyan/verl:app-verl0.5-transformers4.55.4-vllm0.10.0-mcore0.15.0-te2.7 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/iseekyan/verl:app-verl0.5-transformers4.55.4-vllm0.10.0-mcore0.15.0-te2.7  docker.io/iseekyan/verl:app-verl0.5-transformers4.55.4-vllm0.10.0-mcore0.15.0-te2.7'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/iseekyan/verl:app-verl0.5-transformers4.55.4-vllm0.10.0-mcore0.15.0-te2.7 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/iseekyan/verl:app-verl0.5-transformers4.55.4-vllm0.10.0-mcore0.15.0-te2.7  docker.io/iseekyan/verl:app-verl0.5-transformers4.55.4-vllm0.10.0-mcore0.15.0-te2.7'

镜像构建历史

# 2025-09-19 17:17:43  3.44MB 执行命令并创建新的镜像层
RUN /bin/sh -c pip3 install --no-cache-dir --no-deps trl # buildkit
                        
# 2025-09-19 17:17:41  776.73KB 执行命令并创建新的镜像层
RUN /bin/sh -c pip3 install --no-cache-dir mbridge==v0.15.0 # buildkit
                        
# 2025-09-19 17:17:37  10.21MB 执行命令并创建新的镜像层
RUN /bin/sh -c pip3 install --no-deps --no-cache-dir --no-build-isolation git+https://github.com/NVIDIA/Megatron-LM.git@core_v0.15.0rc4 # buildkit
                        
# 2025-09-19 17:17:21  31.01MB 执行命令并创建新的镜像层
RUN /bin/sh -c pip install onnxscript # buildkit
                        
# 2025-09-19 17:17:16  437.55MB 执行命令并创建新的镜像层
RUN /bin/sh -c export NVTE_FRAMEWORK=pytorch && pip3 install --resume-retries 999 --no-deps --no-cache-dir --no-build-isolation git+https://github.com/NVIDIA/TransformerEngine.git@release_v2.7 # buildkit
                        
# 2025-09-19 17:05:56  1.05GB 执行命令并创建新的镜像层
RUN /bin/sh -c pip install --resume-retries 999 --no-cache-dir nvidia-cudnn-cu12==9.8.0.87 # buildkit
                        
# 2025-09-19 17:05:39  475.68KB 执行命令并创建新的镜像层
RUN /bin/sh -c pip uninstall -y pynvml nvidia-ml-py &&     pip install --resume-retries 999 --no-cache-dir --upgrade "nvidia-ml-py>=12.560.30" "fastapi[standard]>=0.115.0" "optree>=0.13.0" "pydantic>=2.9" "grpcio>=1.62.1" # buildkit
                        
# 2025-09-19 17:05:31  72.12MB 执行命令并创建新的镜像层
RUN /bin/sh -c pip install --no-cache-dir "tensordict==0.6.2" "transformers[hf_xet]>=4.55.4" accelerate datasets peft hf-transfer     "numpy<2.0.0" "pyarrow>=19.0.1" pandas     ray[default] codetiming hydra-core pylatexenc qwen-vl-utils wandb dill pybind11 liger-kernel mathruler blobfile xgrammar     pytest py-spy pyext pre-commit ruff # buildkit
                        
# 2025-09-19 17:05:25  2.09GB 执行命令并创建新的镜像层
RUN /bin/sh -c pip install --resume-retries 999 --no-cache-dir vllm==0.10.0 # buildkit
                        
# 2025-09-19 17:05:25  0.00B 设置环境变量 HF_HUB_ENABLE_HF_TRANSFER
ENV HF_HUB_ENABLE_HF_TRANSFER=1
                        
# 2025-09-19 17:05:25  0.00B 设置环境变量 PIP_ROOT_USER_ACTION
ENV PIP_ROOT_USER_ACTION=ignore
                        
# 2025-09-19 17:05:25  0.00B 设置环境变量 NODE_OPTIONS
ENV NODE_OPTIONS=
                        
# 2025-09-19 17:05:25  0.00B 设置环境变量 DEBIAN_FRONTEND
ENV DEBIAN_FRONTEND=noninteractive
                        
# 2025-09-19 17:05:25  0.00B 设置环境变量 VLLM_WORKER_MULTIPROC_METHOD
ENV VLLM_WORKER_MULTIPROC_METHOD=spawn
                        
# 2025-09-19 17:05:25  0.00B 设置环境变量 MAX_JOBS
ENV MAX_JOBS=32
                        
# 2025-09-19 15:25:49  67.00B 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c pip config unset global.index-url &&     pip config unset global.extra-index-url # buildkit
                        
# 2025-09-19 15:25:48  216.14MB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c cd DeepEP &&     python setup.py install # buildkit
                        
# 2025-09-19 15:24:52  0.00B 设置环境变量 PATH
ENV PATH=/workspace/deepep-nvshmem/install/bin:/usr/local/lib/python3.10/dist-packages/torch_tensorrt/bin:/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/tensorrt/bin
                        
# 2025-09-19 15:24:52  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/workspace/deepep-nvshmem/install/lib:/usr/local/x86_64-linux-gnu:/usr/local/mpi/lib:/usr/local/lib/python3.10/dist-packages/torch/lib:/usr/local/lib/python3.10/dist-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2025-09-19 15:24:52  0.00B 设置环境变量 NVSHMEM_DIR
ENV NVSHMEM_DIR=/workspace/deepep-nvshmem/install
                        
# 2025-09-19 15:24:52  1.77GB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c cd deepep-nvshmem &&     NVSHMEM_SHMEM_SUPPORT=0     NVSHMEM_UCX_SUPPORT=0     NVSHMEM_USE_NCCL=0     NVSHMEM_MPI_SUPPORT=0     NVSHMEM_IBGDA_SUPPORT=1     NVSHMEM_PMIX_SUPPORT=0     NVSHMEM_TIMEOUT_DEVICE_POLLING=0     NVSHMEM_USE_GDRCOPY=1     cmake -G Ninja -S . -B build/ -DCMAKE_INSTALL_PREFIX=/workspace/deepep-nvshmem/install && cmake --build build/ --target install # buildkit
                        
# 2025-09-19 15:17:31  0.00B 设置环境变量 GDRCOPY_HOME
ENV GDRCOPY_HOME=/workspace/gdrcopy
                        
# 2025-09-19 15:17:31  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/x86_64-linux-gnu:/usr/local/mpi/lib:/usr/local/lib/python3.10/dist-packages/torch/lib:/usr/local/lib/python3.10/dist-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2025-09-19 15:17:31  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/mpi/lib:/usr/local/lib/python3.10/dist-packages/torch/lib:/usr/local/lib/python3.10/dist-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2025-09-19 15:17:31  0.00B 设置环境变量 CPATH
ENV CPATH=/usr/local/mpi/include:
                        
# 2025-09-19 15:17:31  0.00B 设置环境变量 CUDA_HOME
ENV CUDA_HOME=/usr/local/cuda
                        
# 2025-09-19 15:17:31  4.12MB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c wget https://developer.nvidia.com/downloads/assets/secure/nvshmem/nvshmem_src_3.2.5-1.txz &&     tar -xvf nvshmem_src_3.2.5-1.txz && mv nvshmem_src deepep-nvshmem &&     cd deepep-nvshmem && git apply ../DeepEP/third-party/nvshmem.patch # buildkit
                        
# 2025-09-19 15:17:30  5.26MB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c git clone -b v2.3.1 https://github.com/NVIDIA/gdrcopy.git &&     git clone https://github.com/deepseek-ai/DeepEP.git  &&     cd DeepEP && git checkout a84a248 # buildkit
                        
# 2025-09-19 15:17:28  38.00B 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c ln -s /usr/lib/x86_64-linux-gnu/libmlx5.so.1 /usr/lib/x86_64-linux-gnu/libmlx5.so # buildkit
                        
# 2025-09-19 15:17:27  883.52MB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c pip install --resume-retries 999 --no-cache-dir "tensordict==0.6.2" torchdata "transformers[hf_xet]>=4.52.3" accelerate datasets peft hf-transfer     "numpy<2.0.0" "pyarrow>=19.0.1" pandas cuda-bindings     ray[default] codetiming hydra-core pylatexenc qwen-vl-utils wandb dill pybind11 liger-kernel mathruler blobfile xgrammar     pytest py-spy pyext pre-commit ruff # buildkit
                        
# 2025-09-19 15:15:51  1.11GB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c apt-get install -y ./nsight-systems-2025.3.1_2025.3.1.90-1_amd64.deb &&     rm -rf /usr/local/cuda/bin/nsys &&     ln -s /opt/nvidia/nsight-systems/2025.3.1/target-linux-x64/nsys  /usr/local/cuda/bin/nsys &&     rm -rf /usr/local/cuda/bin/nsys-ui &&     ln -s /opt/nvidia/nsight-systems/2025.3.1/target-linux-x64/nsys-ui /usr/local/cuda/bin/nsys-ui &&     rm nsight-systems-2025.3.1_2025.3.1.90-1_amd64.deb # buildkit
                        
# 2025-09-19 15:15:31  432.48MB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c aria2c --always-resume=true --max-tries=99999 https://developer.nvidia.com/downloads/assets/tools/secure/nsight-systems/2025_3/nsight-systems-2025.3.1_2025.3.1.90-1_amd64.deb &&     apt-get update && apt-get install -y libxcb-cursor0 # buildkit
                        
# 2025-09-19 15:15:18  220.83MB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" --resume-retries 999 git+https://github.com/NVIDIA/apex.git # buildkit
                        
# 2025-09-19 14:38:44  3.79GB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c aria2c --max-tries=9999 https://developer.download.nvidia.com/compute/cudnn/9.8.0/local_installers/cudnn-local-repo-ubuntu2204-9.8.0_1.0-1_amd64.deb &&     dpkg -i cudnn-local-repo-ubuntu2204-9.8.0_1.0-1_amd64.deb &&     cp /var/cudnn-local-repo-ubuntu2204-9.8.0/cudnn-*-keyring.gpg /usr/share/keyrings/ &&     apt-get update &&     apt-get -y install cudnn-cuda-12 &&     rm cudnn-local-repo-ubuntu2204-9.8.0_1.0-1_amd64.deb # buildkit
                        
# 2025-09-19 14:37:20  54.42MB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c pip uninstall -y pynvml nvidia-ml-py &&     pip install --no-cache-dir --upgrade "nvidia-ml-py>=12.560.30" "fastapi[standard]>=0.115.0" "optree>=0.13.0" "pydantic>=2.9" "grpcio>=1.62.1" # buildkit
                        
# 2025-09-19 14:36:55  793.06MB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c ABI_FLAG=$(python -c "import torch; print('TRUE' if torch._C._GLIBCXX_USE_CXX11_ABI else 'FALSE')") &&     URL="https://github.com/Dao-AILab/flash-attention/releases/download/v2.7.4.post1/flash_attn-2.7.4.post1+cu12torch2.6cxx11abi${ABI_FLAG}-cp310-cp310-linux_x86_64.whl" &&     FILE="flash_attn-2.7.4.post1+cu12torch2.6cxx11abi${ABI_FLAG}-cp310-cp310-linux_x86_64.whl" &&     wget -nv "${URL}" &&     pip install --no-cache-dir "${FILE}" # buildkit
                        
# 2025-09-19 14:36:44  5.35GB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c pip install --resume-retries 999 --no-cache-dir torch==2.7.1 torchvision==0.22.1 torchaudio==2.7.1 # buildkit
                        
# 2025-09-19 14:30:37  0.00B 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c pip uninstall -y torch torchvision torchaudio     pytorch-quantization pytorch-triton torch-tensorrt     xgboost transformer_engine flash_attn apex megatron-core grpcio # buildkit
                        
# 2025-09-19 14:30:29  9.17MB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c pip config set global.index-url "${PIP_INDEX}" &&     pip config set global.extra-index-url "${PIP_INDEX}" &&     python -m pip install --upgrade pip # buildkit
                        
# 2025-09-19 14:30:22  55.86MB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c apt-get update &&     apt-get install -y tini aria2 libfreeimage3 libfreeimage-dev zlib1g htop &&     apt-get clean # buildkit
                        
# 2025-09-19 14:30:08  89.33MB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c apt-get update &&     apt-get install -y -o Dpkg::Options::="--force-confdef" systemd &&     apt-get clean # buildkit
                        
# 2025-09-19 14:29:47  2.79KB 执行命令并创建新的镜像层
RUN |2 APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple /bin/sh -c cp /etc/apt/sources.list /etc/apt/sources.list.bak &&     {     echo "deb ${APT_SOURCE} jammy main restricted universe multiverse";     echo "deb ${APT_SOURCE} jammy-updates main restricted universe multiverse";     echo "deb ${APT_SOURCE} jammy-backports main restricted universe multiverse";     echo "deb ${APT_SOURCE} jammy-security main restricted universe multiverse";     } > /etc/apt/sources.list # buildkit
                        
# 2025-09-19 14:29:47  0.00B 定义构建参数
ARG PIP_INDEX=https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
                        
# 2025-09-19 14:29:47  0.00B 定义构建参数
ARG APT_SOURCE=https://mirrors.tuna.tsinghua.edu.cn/ubuntu/
                        
# 2025-09-19 14:29:47  0.00B 设置环境变量 HF_HUB_ENABLE_HF_TRANSFER
ENV HF_HUB_ENABLE_HF_TRANSFER=1
                        
# 2025-09-19 14:29:47  0.00B 设置环境变量 PIP_ROOT_USER_ACTION
ENV PIP_ROOT_USER_ACTION=ignore
                        
# 2025-09-19 14:29:47  0.00B 设置环境变量 NODE_OPTIONS
ENV NODE_OPTIONS=
                        
# 2025-09-19 14:29:47  0.00B 设置环境变量 DEBIAN_FRONTEND
ENV DEBIAN_FRONTEND=noninteractive
                        
# 2025-09-19 14:29:47  0.00B 设置环境变量 VLLM_WORKER_MULTIPROC_METHOD
ENV VLLM_WORKER_MULTIPROC_METHOD=spawn
                        
# 2025-09-19 14:29:47  0.00B 设置环境变量 MAX_JOBS
ENV MAX_JOBS=16
                        
# 2024-08-19 15:02:13  0.00B 添加元数据标签
LABEL com.nvidia.build.ref=25aae698093a80672c33aac448393478894f210e
                        
# 2024-08-19 15:02:13  0.00B 定义构建参数
ARG NVIDIA_BUILD_REF=25aae698093a80672c33aac448393478894f210e
                        
# 2024-08-19 15:02:13  0.00B 添加元数据标签
LABEL com.nvidia.build.id=107063150
                        
# 2024-08-19 15:02:13  0.00B 设置环境变量 NVIDIA_BUILD_ID
ENV NVIDIA_BUILD_ID=107063150
                        
# 2024-08-19 15:02:13  0.00B 定义构建参数
ARG NVIDIA_BUILD_ID=107063150
                        
# 2024-08-19 15:02:13  719.00B 复制新文件或目录到容器中
COPY entrypoint.d/ /opt/nvidia/entrypoint.d/ # buildkit
                        
# 2024-08-19 15:02:13  84.48KB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 PYVER=3.10 /bin/sh -c ln -sf ${_CUDA_COMPAT_PATH}/lib.real ${_CUDA_COMPAT_PATH}/lib  && echo ${_CUDA_COMPAT_PATH}/lib > /etc/ld.so.conf.d/00-cuda-compat.conf  && ldconfig  && rm -f ${_CUDA_COMPAT_PATH}/lib # buildkit
                        
# 2024-08-19 15:02:13  0.00B 设置环境变量 CUDA_MODULE_LOADING
ENV CUDA_MODULE_LOADING=LAZY
                        
# 2024-08-19 15:02:13  0.00B 设置环境变量 TORCH_CUDNN_V8_API_ENABLED
ENV TORCH_CUDNN_V8_API_ENABLED=1
                        
# 2024-08-19 15:02:13  334.24MB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 PYVER=3.10 /bin/sh -c if [ "${L4T}" = "1" ]; then echo "Not installing Transformer Engine in iGPU container because Version variable is set"; else     pip install --no-cache-dir --no-build-isolation git+https://github.com/NVIDIA/TransformerEngine.git@release_v${TRANSFORMER_ENGINE_VERSION}; fi # buildkit
                        
# 2024-08-19 14:50:45  401.25MB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 PYVER=3.10 /bin/sh -c if [ "${L4T}" = "1" ]; then echo "Not installing Flash Attention in iGPU as it is a requirement for Transformer Engine"; else     env MAX_JOBS=4 pip install flash-attn==2.4.2; fi # buildkit
                        
# 2024-08-19 14:25:14  0.00B 设置环境变量 PATH
ENV PATH=/usr/local/lib/python3.10/dist-packages/torch_tensorrt/bin:/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/tensorrt/bin
                        
# 2024-08-19 14:25:14  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/usr/local/lib/python3.10/dist-packages/torch/lib:/usr/local/lib/python3.10/dist-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2024-08-19 14:25:14  45.42MB 执行命令并创建新的镜像层
RUN |7 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 PYVER=3.10 /bin/sh -c pip install --no-cache-dir /opt/pytorch/torch_tensorrt/dist/*.whl # buildkit
                        
# 2024-08-19 14:22:24  0.00B 定义构建参数
ARG PYVER=3.10
                        
# 2024-08-19 14:22:24  151.65MB 复制新文件或目录到容器中
COPY torch_tensorrt/ /opt/pytorch/torch_tensorrt/ # buildkit
                        
# 2024-08-19 14:22:23  47.88MB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c pip --version && python -c 'import sys; print(sys.platform)'     && pip install --no-cache-dir nvidia-pyindex     && pip install --extra-index-url https://urm.nvidia.com/artifactory/api/pypi/sw-tensorrt-pypi/simple --no-cache-dir polygraphy==0.49.12     && pip install --extra-index-url https://pypi.nvidia.com "nvidia-modelopt[torch]==${MODEL_OPT_VERSION}" # buildkit
                        
# 2024-08-19 14:22:14  0.00B 设置环境变量 PATH
ENV PATH=/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/tensorrt/bin
                        
# 2024-08-19 14:22:14  6.50MB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c set -x  && URL=$(VERIFY=1 /nvidia/build-scripts/installTRT.sh | sed -n "s/^.*\(http.*\)tar.*$/\1/p")tar  && FILE=$(wget -O - $URL | sed -n 's/^.*href="\(TensorRT[^"]*\)".*$/\1/p' | egrep -v "internal|safety")  && wget -q $URL/$FILE -O - | tar -xz  && PY=$(python -c 'import sys; print(str(sys.version_info[0])+str(sys.version_info[1]))')  && pip install TensorRT-*/python/tensorrt-*-cp$PY*.whl  && mv /usr/src/tensorrt /opt  && ln -s /opt/tensorrt /usr/src/tensorrt  && rm -r TensorRT-* # buildkit
                        
# 2024-08-19 14:21:19  51.00MB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c chmod -R a+w . # buildkit
                        
# 2024-08-19 14:21:19  34.89MB 复制新文件或目录到容器中
COPY tutorials tutorials # buildkit
                        
# 2024-08-19 14:21:19  15.96MB 复制新文件或目录到容器中
COPY examples examples # buildkit
                        
# 2024-08-19 14:21:19  2.07KB 复制新文件或目录到容器中
COPY docker-examples docker-examples # buildkit
                        
# 2024-08-19 14:21:19  2.05KB 复制新文件或目录到容器中
COPY NVREADME.md README.md # buildkit
                        
# 2024-08-19 14:21:19  0.00B 设置工作目录为/workspace
WORKDIR /workspace
                        
# 2024-08-19 14:21:19  2.56GB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c if [ "${L4T}" = "1" ]; then     echo "Not installing rapids for L4T build." ; else     find /rapids  -name "*-Linux.tar.gz" -exec     tar -C /usr --exclude="*.a" --exclude="bin/xgboost" --strip-components=1 -xvf {} \;  && find /rapids -name "*.whl"     ! -name "tornado-*"     ! -name "Pillow-*"     ! -name "certifi-*"     ! -name "protobuf-*" -exec     pip install --no-cache-dir {} + ; pip install numpy==1.24.4; fi # buildkit
                        
# 2024-08-19 14:20:53  201.84KB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c pip install --no-cache-dir --disable-pip-version-check tabulate # buildkit
                        
# 2024-08-19 14:20:52  757.18MB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c ( cd vision && export PYTORCH_VERSION=$(python -c "import torch; print(torch.__version__)") && CFLAGS="-g0" FORCE_CUDA=1 NVCC_APPEND_FLAGS="--threads 8" pip install --no-cache-dir --no-build-isolation --disable-pip-version-check . )  && ( cd vision && cmake -Bbuild -H. -GNinja -DWITH_CUDA=1 -DCMAKE_PREFIX_PATH=`python -c 'import torch;print(torch.utils.cmake_prefix_path)'` && cmake --build build --target install && rm -rf build )  && ( cd fuser && pip install -r requirements.txt &&  python setup.py -version-tag=a0+${NVFUSER_VERSION} install && python setup.py clean && cp $(find /usr/local/lib/python3.10/dist-packages/ -name libnvfuser_codegen.so)  /usr/local/lib/python3.10/dist-packages/torch/lib/ )  && ( cd lightning-thunder && python setup.py install && rm -rf build)  && BUILD_OPTIONS="--cpp_ext --cuda_ext --bnp --xentropy --deprecated_fused_adam --deprecated_fused_lamb --fast_multihead_attn --distributed_lamb --fast_layer_norm --transducer --distributed_adam --fmha --permutation_search --focal_loss --fused_conv_bias_relu --index_mul_2d --cudnn_gbn --group_norm --gpu_direct_storage"  && if [ "${L4T}" != "1" ]; then BUILD_OPTIONS="--fast_bottleneck --nccl_p2p --peer_memory --nccl_allocator ${BUILD_OPTIONS}"; fi && ( cd apex && CFLAGS="-g0" NVCC_APPEND_FLAGS="--threads 8" pip install -v --no-build-isolation --no-cache-dir --disable-pip-version-check --config-settings "--build-option=${BUILD_OPTIONS}" . && rm -rf build )  && ( cd lightning-thunder && mkdir tmp && cd tmp && git clone -b v${CUDNN_FRONTEND_VERSION} --recursive --single-branch https://github.com/NVIDIA/cudnn-frontend.git cudnn_frontend && cd cudnn_frontend && pip install --no-build-isolation --no-cache-dir --disable-pip-version-check . && cd ../../ && rm -rf tmp )  && ( cd pytorch/third_party/onnx && pip uninstall typing -y && CMAKE_ARGS="-DONNX_USE_PROTOBUF_SHARED_LIBS=ON" pip install --no-build-isolation --no-cache-dir --disable-pip-version-check . ) # buildkit
                        
# 2024-08-19 13:55:55  2.21KB 复制新文件或目录到容器中
COPY singularity/ /.singularity.d/ # buildkit
                        
# 2024-08-19 13:55:55  79.24MB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c export COCOAPI_TAG=$(echo ${COCOAPI_VERSION} | sed 's/^.*+n//')  && pip install --disable-pip-version-check --no-cache-dir git+https://github.com/nvidia/cocoapi.git@${COCOAPI_TAG}#subdirectory=PythonAPI # buildkit
                        
# 2024-08-19 13:55:40  0.00B 设置环境变量 COCOAPI_VERSION
ENV COCOAPI_VERSION=2.0+nv0.8.0
                        
# 2024-08-19 13:55:40  660.39MB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c if [ -z "${DALI_VERSION}" ] ; then   echo "Not Installing DALI for L4T Build." ; else   export DALI_PKG_SUFFIX="cuda${CUDA_VERSION%%.*}0"   && pip install --disable-pip-version-check --no-cache-dir                 --extra-index-url https://developer.download.nvidia.com/compute/redist                 --extra-index-url http://sqrl/dldata/pip-dali${DALI_URL_SUFFIX:-} --trusted-host sqrl         nvidia-dali-${DALI_PKG_SUFFIX}==${DALI_VERSION}; fi # buildkit
                        
# 2024-08-19 13:55:32  570.57MB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c pip install --no-cache-dir /tmp/dist/*.whl # buildkit
                        
# 2024-08-19 13:55:28  11.45MB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c cd pytorch && pip install --no-cache-dir -v -r /opt/pytorch/pytorch/requirements.txt # buildkit
                        
# 2024-08-19 13:55:27  1.90GB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c pip install /opt/transfer/torch*.whl      && patchelf --set-rpath '/usr/local/lib' /usr/local/lib/python3.10/dist-packages/torch/lib/libtorch_global_deps.so # buildkit
                        
# 2024-08-19 13:55:08  0.00B 设置环境变量 USE_EXPERIMENTAL_CUDNN_V8_API
ENV USE_EXPERIMENTAL_CUDNN_V8_API=1
                        
# 2024-08-19 13:55:08  0.00B 设置环境变量 TORCH_ALLOW_TF32_CUBLAS_OVERRIDE
ENV TORCH_ALLOW_TF32_CUBLAS_OVERRIDE=1
                        
# 2024-08-19 13:55:08  0.00B 设置环境变量 CUDA_HOME
ENV CUDA_HOME=/usr/local/cuda
                        
# 2024-08-19 13:55:08  0.00B 设置环境变量 PYTORCH_HOME
ENV PYTORCH_HOME=/opt/pytorch/pytorch
                        
# 2024-08-19 13:55:08  0.00B 设置环境变量 TORCH_CUDA_ARCH_LIST
ENV TORCH_CUDA_ARCH_LIST=5.2 6.0 6.1 7.0 7.2 7.5 8.0 8.6 8.7 9.0+PTX
                        
# 2024-08-19 13:55:08  0.00B 设置环境变量 UCC_CL_BASIC_TLS
ENV UCC_CL_BASIC_TLS=^sharp
                        
# 2024-08-19 13:55:08  53.68MB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c OPENCV_VERSION=4.7.0 &&     cd / &&     wget -q -O - https://github.com/opencv/opencv/archive/${OPENCV_VERSION}.tar.gz | tar -xzf - &&     cd /opencv-${OPENCV_VERSION} &&     cmake -GNinja -Bbuild -H.           -DWITH_CUDA=OFF -DWITH_1394=OFF           -DPYTHON3_PACKAGES_PATH="/usr/local/lib/python${PYVER}/dist-packages"           -DBUILD_opencv_cudalegacy=OFF -DBUILD_opencv_stitching=OFF -DWITH_IPP=OFF -DWITH_PROTOBUF=OFF &&     cmake --build build --target install &&     cd modules/python/package &&     pip install --no-cache-dir --disable-pip-version-check -v . &&     rm -rf /opencv-${OPENCV_VERSION} # buildkit
                        
# 2024-08-19 13:53:25  0.00B 声明容器运行时监听的端口
EXPOSE map[6006/tcp:{}]
                        
# 2024-08-19 13:53:25  0.00B 声明容器运行时监听的端口
EXPOSE map[8888/tcp:{}]
                        
# 2024-08-19 13:53:25  0.00B 设置环境变量 TENSORBOARD_PORT
ENV TENSORBOARD_PORT=6006
                        
# 2024-08-19 13:53:25  0.00B 设置环境变量 JUPYTER_PORT
ENV JUPYTER_PORT=8888
                        
# 2024-08-19 13:53:25  248.00B 复制新文件或目录到容器中
COPY jupyter_config/settings.jupyterlab-settings /root/.jupyter/lab/user-settings/@jupyterlab/completer-extension/ # buildkit
                        
# 2024-08-19 13:53:25  236.00B 复制新文件或目录到容器中
COPY jupyter_config/manager.jupyterlab-settings /root/.jupyter/lab/user-settings/@jupyterlab/completer-extension/ # buildkit
                        
# 2024-08-19 13:53:25  554.00B 复制新文件或目录到容器中
COPY jupyter_config/jupyter_notebook_config.py /usr/local/etc/jupyter/ # buildkit
                        
# 2024-08-19 13:53:25  17.26MB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c pip install --no-cache-dir jupyterlab-tensorboard-pro jupytext     black isort  && mkdir -p /root/.jupyter/lab/user-settings/@jupyterlab/completer-extension/  && jupyter lab clean # buildkit
                        
# 2024-08-19 13:53:23  27.81KB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c PATCHED_FILE=$(python -c "from tensorboard.plugins.core import core_plugin as _; print(_.__file__)") &&     sed -i 's/^\( *"--bind_all",\)$/\1 default=True,/' "$PATCHED_FILE" &&     test $(grep '^ *"--bind_all", default=True,$' "$PATCHED_FILE" | wc -l) -eq 1 # buildkit
                        
# 2024-08-19 13:53:23  184.00MB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c git config --global url."https://github".insteadOf git://github &&     pip install --no-cache-dir 'jupyterlab>=4.1.0,<5.0.0a0' notebook tensorboard==2.16.2     jupyterlab_code_formatter python-hostlist # buildkit
                        
# 2024-08-19 13:53:13  2.16GB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c pip install --no-cache-dir         numpy==1.24.4         scipy==1.11.3         "PyYAML>=5.4.1"         astunparse         typing_extensions         cffi         spacy         mock         tqdm         librosa==0.10.1         expecttest==0.1.3         hypothesis==5.35.1         xdoctest==1.0.2         pytest==8.1.1         pytest-xdist         pytest-rerunfailures         pytest-shard         pytest-flakefinder         pybind11         Cython         "regex>=2020.1.8"         protobuf==4.24.4 &&     if [[ $TARGETARCH = "amd64" ]] ; then pip install --no-cache-dir mkl==2021.1.1 mkl-include==2021.1.1 mkl-devel==2021.1.1 ;     find /usr/local/lib -maxdepth 1 -type f -regex '.*\/lib\(tbb\|mkl\).*\.so\($\|\.[0-9]*\.[0-9]*\)' -exec rm -v {} + ; fi # buildkit
                        
# 2024-08-19 13:52:40  0.00B 设置环境变量 PIP_DEFAULT_TIMEOUT
ENV PIP_DEFAULT_TIMEOUT=100
                        
# 2024-08-19 13:52:40  0.00B 设置环境变量 LC_ALL
ENV LC_ALL=C.UTF-8
                        
# 2024-08-19 13:52:40  0.00B 设置环境变量 PYTHONIOENCODING
ENV PYTHONIOENCODING=utf-8
                        
# 2024-08-19 13:52:40  1.39GB 复制新文件或目录到容器中
COPY . . # buildkit
                        
# 2024-08-17 15:43:12  0.00B 设置工作目录为/opt/pytorch
WORKDIR /opt/pytorch
                        
# 2024-08-19 01:33:25  0.00B 设置环境变量 NVPL_LAPACK_MATH_MODE
ENV NVPL_LAPACK_MATH_MODE=PEDANTIC
                        
# 2024-08-19 01:33:25  0.00B 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c if [ $TARGETARCH = "arm64" ]; then cd /opt &&     curl "https://gitlab-master.nvidia.com/api/v4/projects/105799/packages/generic/nvpl_slim_24.04/sbsa/nvpl_slim_24.04.tar" --output nvpl_slim_24.04.tar &&     tar -xf nvpl_slim_24.04.tar &&     cp -r nvpl_slim_24.04/lib/* /usr/local/lib &&     cp -r nvpl_slim_24.04/include/* /usr/local/include &&     rm -rf nvpl_slim_24.04.tar nvpl_slim_24.04 ; fi # buildkit
                        
# 2024-08-17 15:43:12  46.71MB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c curl "https://gitlab-master.nvidia.com/api/v4/projects/105799/packages/generic/OpenBLAS/0.3.24-$(uname -m)/OpenBLAS-0.3.24-$(uname -m).tar.gz" --output OpenBLAS.tar.gz &&     tar -xf OpenBLAS.tar.gz -C /usr/local/ &&     rm OpenBLAS.tar.gz # buildkit
                        
# 2024-08-17 15:43:12  71.45MB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c pip install --no-cache-dir pip 'setuptools<71' &&     pip install --no-cache-dir cmake # buildkit
                        
# 2024-08-17 15:43:08  24.34MB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c curl -O https://bootstrap.pypa.io/get-pip.py &&     python get-pip.py &&     rm get-pip.py # buildkit
                        
# 2024-08-17 15:43:03  0.00B 设置环境变量 PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION
ENV PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
                        
# 2024-08-17 15:43:03  198.72MB 执行命令并创建新的镜像层
RUN |6 NVIDIA_PYTORCH_VERSION=24.08 PYTORCH_BUILD_VERSION=2.5.0a0+872d972 NVFUSER_BUILD_VERSION=1d02b13 TARGETARCH=amd64 PYVER=3.10 L4T=0 /bin/sh -c export PYSFX=`echo "$PYVER" | cut -c1-1` &&     export DEBIAN_FRONTEND=noninteractive &&     apt-get update &&     apt-get install -y --no-install-recommends         python$PYVER-dev         python$PYSFX         python$PYSFX-dev         python$PYSFX-distutils         python-is-python$PYSFX         autoconf         automake         libatlas-base-dev         libgoogle-glog-dev         libbz2-dev         libc-ares2         libre2-9         libleveldb-dev         liblmdb-dev         libprotobuf-dev         libsnappy-dev         libtool         nasm         protobuf-compiler         pkg-config         unzip         sox         libsndfile1         libpng-dev         libhdf5-103         libhdf5-dev         gfortran         rapidjson-dev         ninja-build         libedit-dev         build-essential         patchelf      && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2024-08-17 15:43:03  0.00B 定义构建参数
ARG L4T=0
                        
# 2024-08-17 15:43:03  0.00B 定义构建参数
ARG PYVER=3.10
                        
# 2024-08-17 15:43:03  0.00B 定义构建参数
ARG TARGETARCH=amd64
                        
# 2024-08-17 15:43:03  0.00B 添加元数据标签
LABEL com.nvidia.pytorch.version=2.5.0a0+872d972
                        
# 2024-08-17 15:43:03  0.00B 设置环境变量 NVFUSER_BUILD_VERSION NVFUSER_VERSION
ENV NVFUSER_BUILD_VERSION=1d02b13 NVFUSER_VERSION=1d02b13
                        
# 2024-08-17 15:43:03  0.00B 设置环境变量 PYTORCH_BUILD_VERSION PYTORCH_VERSION PYTORCH_BUILD_NUMBER NVIDIA_PYTORCH_VERSION
ENV PYTORCH_BUILD_VERSION=2.5.0a0+872d972 PYTORCH_VERSION=2.5.0a0+872d972 PYTORCH_BUILD_NUMBER=0 NVIDIA_PYTORCH_VERSION=24.08
                        
# 2024-08-17 15:43:03  0.00B 定义构建参数
ARG NVFUSER_BUILD_VERSION=1d02b13
                        
# 2024-08-17 15:43:03  0.00B 定义构建参数
ARG PYTORCH_BUILD_VERSION=2.5.0a0+872d972
                        
# 2024-08-17 15:43:03  0.00B 定义构建参数
ARG NVIDIA_PYTORCH_VERSION=24.08
                        
# 2024-08-17 15:43:03  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=PyTorch
                        
# 2024-08-17 13:26:56  0.00B 设置环境变量 LIBRARY_PATH
ENV LIBRARY_PATH=/usr/local/cuda/lib64/stubs:
                        
# 2024-08-17 13:26:56  984.03MB 执行命令并创建新的镜像层
RUN |7 GDRCOPY_VERSION=2.3.1-1 HPCX_VERSION=2.19 RDMACORE_VERSION=39.0 MOFED_VERSION=5.4-rdmacore39.0 OPENUCX_VERSION=1.17.0 OPENMPI_VERSION=4.1.7 TARGETARCH=amd64 /bin/sh -c export DEVEL=1 BASE=0  && /nvidia/build-scripts/installNCU.sh  && /nvidia/build-scripts/installCUDA.sh  && /nvidia/build-scripts/installLIBS.sh  && if [ ! -f /etc/ld.so.conf.d/nvidia-tegra.conf ]; then /nvidia/build-scripts/installNCCL.sh; fi  && /nvidia/build-scripts/installCUDNN.sh  && /nvidia/build-scripts/installCUTENSOR.sh  && /nvidia/build-scripts/installTRT.sh  && /nvidia/build-scripts/installNSYS.sh  && /nvidia/build-scripts/installCUSPARSELT.sh  && if [ -f "/tmp/cuda-${_CUDA_VERSION_MAJMIN}.patch" ]; then patch -p0 < /tmp/cuda-${_CUDA_VERSION_MAJMIN}.patch; fi  && rm -f /tmp/cuda-*.patch # buildkit
                        
# 2024-08-17 13:20:04  1.49KB 复制新文件或目录到容器中
COPY cuda-*.patch /tmp # buildkit
                        
# 2024-08-17 13:20:04  0.00B 设置环境变量 OMPI_MCA_coll_hcoll_enable
ENV OMPI_MCA_coll_hcoll_enable=0
                        
# 2024-08-17 13:20:04  0.00B 设置环境变量 OPAL_PREFIX PATH
ENV OPAL_PREFIX=/opt/hpcx/ompi PATH=/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin
                        
# 2024-08-17 13:20:04  229.15MB 执行命令并创建新的镜像层
RUN |7 GDRCOPY_VERSION=2.3.1-1 HPCX_VERSION=2.19 RDMACORE_VERSION=39.0 MOFED_VERSION=5.4-rdmacore39.0 OPENUCX_VERSION=1.17.0 OPENMPI_VERSION=4.1.7 TARGETARCH=amd64 /bin/sh -c cd /nvidia  && ( export DEBIAN_FRONTEND=noninteractive        && apt-get update                            && apt-get install -y --no-install-recommends              libibverbs1                                  libibverbs-dev                               librdmacm1                                   librdmacm-dev                                libibumad3                                   libibumad-dev                                ibverbs-utils                                ibverbs-providers                     && rm -rf /var/lib/apt/lists/*               && rm $(dpkg-query -L                                    libibverbs-dev                               librdmacm-dev                                libibumad-dev                            | grep "\(\.so\|\.a\)$")          )                                            && ( cd opt/gdrcopy/                              && dpkg -i libgdrapi_*.deb                   )                                         && ( cp -r opt/hpcx /opt/                                         && cp etc/ld.so.conf.d/hpcx.conf /etc/ld.so.conf.d/          && ln -sf /opt/hpcx/ompi /usr/local/mpi                      && ln -sf /opt/hpcx/ucx  /usr/local/ucx                      && sed -i 's/^\(hwloc_base_binding_policy\) = core$/\1 = none/' /opt/hpcx/ompi/etc/openmpi-mca-params.conf         && sed -i 's/^\(btl = self\)$/#\1/'                             /opt/hpcx/ompi/etc/openmpi-mca-params.conf       )                                                         && ldconfig # buildkit
                        
# 2024-08-17 13:20:04  0.00B 定义构建参数
ARG TARGETARCH=amd64
                        
# 2024-08-17 13:20:04  0.00B 设置环境变量 GDRCOPY_VERSION HPCX_VERSION MOFED_VERSION OPENUCX_VERSION OPENMPI_VERSION RDMACORE_VERSION
ENV GDRCOPY_VERSION=2.3.1-1 HPCX_VERSION=2.19 MOFED_VERSION=5.4-rdmacore39.0 OPENUCX_VERSION=1.17.0 OPENMPI_VERSION=4.1.7 RDMACORE_VERSION=39.0
                        
# 2024-08-17 13:20:04  0.00B 定义构建参数
ARG OPENMPI_VERSION=4.1.7
                        
# 2024-08-17 13:20:04  0.00B 定义构建参数
ARG OPENUCX_VERSION=1.17.0
                        
# 2024-08-17 13:20:04  0.00B 定义构建参数
ARG MOFED_VERSION=5.4-rdmacore39.0
                        
# 2024-08-17 13:20:04  0.00B 定义构建参数
ARG RDMACORE_VERSION=39.0
                        
# 2024-08-17 13:20:04  0.00B 定义构建参数
ARG HPCX_VERSION=2.19
                        
# 2024-08-17 13:20:04  0.00B 定义构建参数
ARG GDRCOPY_VERSION=2.3.1-1
                        
# 2024-08-17 13:19:54  84.90MB 执行命令并创建新的镜像层
RUN /bin/sh -c export DEBIAN_FRONTEND=noninteractive  && apt-get update  && apt-get install -y --no-install-recommends         build-essential         git         libglib2.0-0         less         libnl-route-3-200         libnl-3-dev         libnl-route-3-dev         libnuma-dev         libnuma1         libpmi2-0-dev         nano         numactl         openssh-client         vim         wget  && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2024-08-17 12:59:28  148.72KB 复制新文件或目录到容器中
COPY NVIDIA_Deep_Learning_Container_License.pdf /workspace/ # buildkit
                        
# 2024-08-17 12:59:28  0.00B 配置容器启动时运行的命令
ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
                        
# 2024-08-17 12:59:28  0.00B 设置环境变量 NVIDIA_PRODUCT_NAME
ENV NVIDIA_PRODUCT_NAME=CUDA
                        
# 2024-08-17 12:59:28  14.85KB 复制新文件或目录到容器中
COPY entrypoint/ /opt/nvidia/ # buildkit
                        
# 2024-08-17 12:59:28  0.00B 设置环境变量 PATH LD_LIBRARY_PATH NVIDIA_VISIBLE_DEVICES NVIDIA_DRIVER_CAPABILITIES
ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin LD_LIBRARY_PATH=/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility,video
                        
# 2024-08-17 12:59:28  0.00B 定义构建参数
ARG _LIBPATH_SUFFIX=
                        
# 2024-08-17 12:59:28  46.00B 执行命令并创建新的镜像层
RUN |24 CUDA_VERSION=12.6.0.022 CUDA_DRIVER_VERSION=560.35.03 JETPACK_HOST_MOUNTS= NCCL_VERSION=2.22.3 CUBLAS_VERSION=12.6.0.22 CUFFT_VERSION=11.2.6.28 CURAND_VERSION=10.3.7.37 CUSPARSE_VERSION=12.5.2.23 CUSOLVER_VERSION=11.6.4.38 CUTENSOR_VERSION=2.0.2.5 NPP_VERSION=12.3.1.23 NVJPEG_VERSION=12.3.3.23 CUDNN_VERSION=9.3.0.75 CUDNN_FRONTEND_VERSION=1.5.2 TRT_VERSION=10.3.0.26+cuda12.5.1.007 TRTOSS_VERSION=24.08 NSIGHT_SYSTEMS_VERSION=2024.4.2.133 NSIGHT_COMPUTE_VERSION=2024.3.0.15 CUSPARSELT_VERSION=0.6.2.3 DALI_VERSION=1.40.0 DALI_BUILD=16741769 POLYGRAPHY_VERSION=0.49.13 TRANSFORMER_ENGINE_VERSION=1.9 MODEL_OPT_VERSION=0.15.0 /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
                        
# 2024-08-17 12:59:27  13.39KB 复制文件或目录到容器中
ADD docs.tgz / # buildkit
                        
# 2024-08-17 12:59:27  0.00B 设置环境变量 DALI_VERSION DALI_BUILD POLYGRAPHY_VERSION TRANSFORMER_ENGINE_VERSION MODEL_OPT_VERSION
ENV DALI_VERSION=1.40.0 DALI_BUILD=16741769 POLYGRAPHY_VERSION=0.49.13 TRANSFORMER_ENGINE_VERSION=1.9 MODEL_OPT_VERSION=0.15.0
                        
# 2024-08-17 12:59:27  0.00B 定义构建参数
ARG MODEL_OPT_VERSION=0.15.0
                        
# 2024-08-17 12:59:27  0.00B 定义构建参数
ARG TRANSFORMER_ENGINE_VERSION=1.9
                        
# 2024-08-17 12:59:27  0.00B 定义构建参数
ARG POLYGRAPHY_VERSION=0.49.13
                        
# 2024-08-17 12:59:27  0.00B 定义构建参数
ARG DALI_BUILD=16741769
                        
# 2024-08-17 12:59:27  0.00B 定义构建参数
ARG DALI_VERSION=1.40.0
                        
# 2024-08-17 12:59:27  0.00B 添加元数据标签
LABEL com.nvidia.nccl.version=2.22.3 com.nvidia.cublas.version=12.6.0.22 com.nvidia.cufft.version=11.2.6.28 com.nvidia.curand.version=10.3.7.37 com.nvidia.cusparse.version=12.5.2.23 com.nvidia.cusparselt.version=0.6.2.3 com.nvidia.cusolver.version=11.6.4.38 com.nvidia.cutensor.version=2.0.2.5 com.nvidia.npp.version=12.3.1.23 com.nvidia.nvjpeg.version=12.3.3.23 com.nvidia.cudnn.version=9.3.0.75 com.nvidia.tensorrt.version=10.3.0.26+cuda12.5.1.007 com.nvidia.tensorrtoss.version=24.08 com.nvidia.nsightsystems.version=2024.4.2.133 com.nvidia.nsightcompute.version=2024.3.0.15
                        
# 2024-08-17 12:59:27  6.43GB 执行命令并创建新的镜像层
RUN |19 CUDA_VERSION=12.6.0.022 CUDA_DRIVER_VERSION=560.35.03 JETPACK_HOST_MOUNTS= NCCL_VERSION=2.22.3 CUBLAS_VERSION=12.6.0.22 CUFFT_VERSION=11.2.6.28 CURAND_VERSION=10.3.7.37 CUSPARSE_VERSION=12.5.2.23 CUSOLVER_VERSION=11.6.4.38 CUTENSOR_VERSION=2.0.2.5 NPP_VERSION=12.3.1.23 NVJPEG_VERSION=12.3.3.23 CUDNN_VERSION=9.3.0.75 CUDNN_FRONTEND_VERSION=1.5.2 TRT_VERSION=10.3.0.26+cuda12.5.1.007 TRTOSS_VERSION=24.08 NSIGHT_SYSTEMS_VERSION=2024.4.2.133 NSIGHT_COMPUTE_VERSION=2024.3.0.15 CUSPARSELT_VERSION=0.6.2.3 /bin/sh -c /nvidia/build-scripts/installLIBS.sh  && /nvidia/build-scripts/installCUDNN.sh  && /nvidia/build-scripts/installTRT.sh  && /nvidia/build-scripts/installNSYS.sh  && /nvidia/build-scripts/installNCU.sh  && /nvidia/build-scripts/installCUTENSOR.sh  && /nvidia/build-scripts/installCUSPARSELT.sh  && if [ -z "${JETPACK_HOST_MOUNTS}" ]; then       /nvidia/build-scripts/installNCCL.sh;     fi; # buildkit
                        
# 2024-08-17 12:54:52  0.00B 设置环境变量 NCCL_VERSION CUBLAS_VERSION CUFFT_VERSION CURAND_VERSION CUSPARSE_VERSION CUSPARSELT_VERSION CUSOLVER_VERSION CUTENSOR_VERSION NPP_VERSION NVJPEG_VERSION CUDNN_VERSION CUDNN_FRONTEND_VERSION TRT_VERSION TRTOSS_VERSION NSIGHT_SYSTEMS_VERSION NSIGHT_COMPUTE_VERSION
ENV NCCL_VERSION=2.22.3 CUBLAS_VERSION=12.6.0.22 CUFFT_VERSION=11.2.6.28 CURAND_VERSION=10.3.7.37 CUSPARSE_VERSION=12.5.2.23 CUSPARSELT_VERSION=0.6.2.3 CUSOLVER_VERSION=11.6.4.38 CUTENSOR_VERSION=2.0.2.5 NPP_VERSION=12.3.1.23 NVJPEG_VERSION=12.3.3.23 CUDNN_VERSION=9.3.0.75 CUDNN_FRONTEND_VERSION=1.5.2 TRT_VERSION=10.3.0.26+cuda12.5.1.007 TRTOSS_VERSION=24.08 NSIGHT_SYSTEMS_VERSION=2024.4.2.133 NSIGHT_COMPUTE_VERSION=2024.3.0.15
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG CUSPARSELT_VERSION=0.6.2.3
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG NSIGHT_COMPUTE_VERSION=2024.3.0.15
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG NSIGHT_SYSTEMS_VERSION=2024.4.2.133
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG TRTOSS_VERSION=24.08
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG TRT_VERSION=10.3.0.26+cuda12.5.1.007
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG CUDNN_FRONTEND_VERSION=1.5.2
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG CUDNN_VERSION=9.3.0.75
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG NVJPEG_VERSION=12.3.3.23
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG NPP_VERSION=12.3.1.23
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG CUTENSOR_VERSION=2.0.2.5
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG CUSOLVER_VERSION=11.6.4.38
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG CUSPARSE_VERSION=12.5.2.23
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG CURAND_VERSION=10.3.7.37
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG CUFFT_VERSION=11.2.6.28
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG CUBLAS_VERSION=12.6.0.22
                        
# 2024-08-17 12:54:52  0.00B 定义构建参数
ARG NCCL_VERSION=2.22.3
                        
# 2024-08-17 12:54:52  0.00B 添加元数据标签
LABEL com.nvidia.volumes.needed=nvidia_driver com.nvidia.cuda.version=9.0
                        
# 2024-08-17 12:54:52  0.00B 设置环境变量 _CUDA_COMPAT_PATH ENV BASH_ENV SHELL NVIDIA_REQUIRE_CUDA
ENV _CUDA_COMPAT_PATH=/usr/local/cuda/compat ENV=/etc/shinit_v2 BASH_ENV=/etc/bash.bashrc SHELL=/bin/bash NVIDIA_REQUIRE_CUDA=cuda>=9.0
                        
# 2024-08-17 12:54:52  58.91KB 执行命令并创建新的镜像层
RUN |3 CUDA_VERSION=12.6.0.022 CUDA_DRIVER_VERSION=560.35.03 JETPACK_HOST_MOUNTS= /bin/sh -c cp -vprd /nvidia/. /  &&  patch -p0 < /etc/startup_scripts.patch  &&  rm -f /etc/startup_scripts.patch # buildkit
                        
# 2024-08-17 12:54:52  459.75MB 执行命令并创建新的镜像层
RUN |3 CUDA_VERSION=12.6.0.022 CUDA_DRIVER_VERSION=560.35.03 JETPACK_HOST_MOUNTS= /bin/sh -c /nvidia/build-scripts/installCUDA.sh # buildkit
                        
# 2024-08-17 12:54:33  0.00B 执行命令并创建新的镜像层
RUN |3 CUDA_VERSION=12.6.0.022 CUDA_DRIVER_VERSION=560.35.03 JETPACK_HOST_MOUNTS= /bin/sh -c if [ -n "${JETPACK_HOST_MOUNTS}" ]; then        echo "/usr/lib/aarch64-linux-gnu/tegra" > /etc/ld.so.conf.d/nvidia-tegra.conf     && echo "/usr/lib/aarch64-linux-gnu/tegra-egl" >> /etc/ld.so.conf.d/nvidia-tegra.conf;     fi # buildkit
                        
# 2024-08-17 12:54:33  0.00B 设置环境变量 CUDA_VERSION CUDA_DRIVER_VERSION CUDA_CACHE_DISABLE NVIDIA_REQUIRE_JETPACK_HOST_MOUNTS
ENV CUDA_VERSION=12.6.0.022 CUDA_DRIVER_VERSION=560.35.03 CUDA_CACHE_DISABLE=1 NVIDIA_REQUIRE_JETPACK_HOST_MOUNTS=
                        
# 2024-08-17 12:54:33  0.00B 定义构建参数
ARG JETPACK_HOST_MOUNTS=
                        
# 2024-08-17 12:54:33  0.00B 定义构建参数
ARG CUDA_DRIVER_VERSION=560.35.03
                        
# 2024-08-17 12:54:33  0.00B 定义构建参数
ARG CUDA_VERSION=12.6.0.022
                        
# 2024-08-17 12:54:33  324.29MB 执行命令并创建新的镜像层
RUN /bin/sh -c export DEBIAN_FRONTEND=noninteractive  && apt-get update  && apt-get install -y --no-install-recommends         apt-utils         build-essential         ca-certificates         curl         libncurses5         libncursesw5         patch         wget         rsync         unzip         jq         gnupg         libtcmalloc-minimal4 # buildkit
                        
# 2024-08-13 17:27:24  0.00B 
/bin/sh -c #(nop)  CMD ["/bin/bash"]
                        
# 2024-08-13 17:27:24  77.86MB 
/bin/sh -c #(nop) ADD file:2f8a54a5efd080fb81efea702b4e3e07d946eec7563fb2281bd28950c10ec462 in / 
                        
# 2024-08-13 17:27:22  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.version=22.04
                        
# 2024-08-13 17:27:22  0.00B 
/bin/sh -c #(nop)  LABEL org.opencontainers.image.ref.name=ubuntu
                        
# 2024-08-13 17:27:22  0.00B 
/bin/sh -c #(nop)  ARG LAUNCHPAD_BUILD_ARCH
                        
# 2024-08-13 17:27:22  0.00B 
/bin/sh -c #(nop)  ARG RELEASE
                        
                    

镜像信息

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    "RepoDigests": [
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    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2025-09-19T02:17:43.812267942-07:00",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "ExposedPorts": {
            "6006/tcp": {},
            "8888/tcp": {}
        },
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "PATH=/workspace/deepep-nvshmem/install/bin:/usr/local/lib/python3.10/dist-packages/torch_tensorrt/bin:/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/tensorrt/bin",
            "CUDA_VERSION=12.6.0.022",
            "CUDA_DRIVER_VERSION=560.35.03",
            "CUDA_CACHE_DISABLE=1",
            "NVIDIA_REQUIRE_JETPACK_HOST_MOUNTS=",
            "_CUDA_COMPAT_PATH=/usr/local/cuda/compat",
            "ENV=/etc/shinit_v2",
            "BASH_ENV=/etc/bash.bashrc",
            "SHELL=/bin/bash",
            "NVIDIA_REQUIRE_CUDA=cuda\u003e=9.0",
            "NCCL_VERSION=2.22.3",
            "CUBLAS_VERSION=12.6.0.22",
            "CUFFT_VERSION=11.2.6.28",
            "CURAND_VERSION=10.3.7.37",
            "CUSPARSE_VERSION=12.5.2.23",
            "CUSPARSELT_VERSION=0.6.2.3",
            "CUSOLVER_VERSION=11.6.4.38",
            "CUTENSOR_VERSION=2.0.2.5",
            "NPP_VERSION=12.3.1.23",
            "NVJPEG_VERSION=12.3.3.23",
            "CUDNN_VERSION=9.3.0.75",
            "CUDNN_FRONTEND_VERSION=1.5.2",
            "TRT_VERSION=10.3.0.26+cuda12.5.1.007",
            "TRTOSS_VERSION=24.08",
            "NSIGHT_SYSTEMS_VERSION=2024.4.2.133",
            "NSIGHT_COMPUTE_VERSION=2024.3.0.15",
            "DALI_VERSION=1.40.0",
            "DALI_BUILD=16741769",
            "POLYGRAPHY_VERSION=0.49.13",
            "TRANSFORMER_ENGINE_VERSION=1.9",
            "MODEL_OPT_VERSION=0.15.0",
            "LD_LIBRARY_PATH=/workspace/deepep-nvshmem/install/lib:/usr/local/x86_64-linux-gnu:/usr/local/mpi/lib:/usr/local/lib/python3.10/dist-packages/torch/lib:/usr/local/lib/python3.10/dist-packages/torch_tensorrt/lib:/usr/local/cuda/compat/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility,video",
            "NVIDIA_PRODUCT_NAME=PyTorch",
            "GDRCOPY_VERSION=2.3.1-1",
            "HPCX_VERSION=2.19",
            "MOFED_VERSION=5.4-rdmacore39.0",
            "OPENUCX_VERSION=1.17.0",
            "OPENMPI_VERSION=4.1.7",
            "RDMACORE_VERSION=39.0",
            "OPAL_PREFIX=/opt/hpcx/ompi",
            "OMPI_MCA_coll_hcoll_enable=0",
            "LIBRARY_PATH=/usr/local/cuda/lib64/stubs:",
            "PYTORCH_BUILD_VERSION=2.5.0a0+872d972",
            "PYTORCH_VERSION=2.5.0a0+872d972",
            "PYTORCH_BUILD_NUMBER=0",
            "NVIDIA_PYTORCH_VERSION=24.08",
            "NVFUSER_BUILD_VERSION=1d02b13",
            "NVFUSER_VERSION=1d02b13",
            "PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python",
            "NVPL_LAPACK_MATH_MODE=PEDANTIC",
            "PYTHONIOENCODING=utf-8",
            "LC_ALL=C.UTF-8",
            "PIP_DEFAULT_TIMEOUT=100",
            "JUPYTER_PORT=8888",
            "TENSORBOARD_PORT=6006",
            "UCC_CL_BASIC_TLS=^sharp",
            "TORCH_CUDA_ARCH_LIST=5.2 6.0 6.1 7.0 7.2 7.5 8.0 8.6 8.7 9.0+PTX",
            "PYTORCH_HOME=/opt/pytorch/pytorch",
            "CUDA_HOME=/usr/local/cuda",
            "TORCH_ALLOW_TF32_CUBLAS_OVERRIDE=1",
            "USE_EXPERIMENTAL_CUDNN_V8_API=1",
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