docker.io/nikghosh09/transformers:sing_v1 linux/amd64

docker.io/nikghosh09/transformers:sing_v1 - 国内下载镜像源 浏览次数:220
这是docker容器镜像的描述信息：

Transformers

A JAX-based implementation of various transformer models, including BERT, RoBERTa and other variants.

This is a collection of transformer models that can be used as a starting point for your own research or development projects. The models are implemented using the JAX library, which provides a high-performance and flexible framework for building machine learning models.

The transformers in this repository include:

  • BERT (Bidirectional Encoder Representations from Transformers)
  • RoBERTa (Robustly Optimized BERT Pretraining Approach)
  • DistilBERT (Distilled version of BERT)
  • XLNet (Extreme Language Modeling for Text Generation)

This repository provides a convenient way to access and use these transformer models in your own projects, with pre-trained weights available for download. You can also use this as a starting point to experiment with different architectures or modifications.

源镜像 docker.io/nikghosh09/transformers:sing_v1
国内镜像 swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nikghosh09/transformers:sing_v1
镜像ID sha256:255fc450efbcd5f23bcac03ed060be2e21fe62951d268fb0e5f6cf4d06b1e649
镜像TAG sing_v1
大小 19.31GB
镜像源 docker.io
项目信息 Docker-Hub主页 🚀项目TAG 🚀
CMD
启动入口 /opt/nvidia/nvidia_entrypoint.sh
工作目录 /home/aiscuser
OS/平台 linux/amd64
浏览量 220 次
贡献者
镜像创建 2023-08-21T17:56:15.597681526Z
同步时间 2024-10-18 00:53
更新时间 2025-02-18 11:25
环境变量
PATH=/usr/local/mpi/bin:/usr/local/ucx/bin:/opt/conda/envs/ptca/bin:/opt/conda/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>=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 NV_CUDA_CUDART_VERSION=11.7.60-1 NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-7 CUDA_VERSION=11.7.0 LD_LIBRARY_PATH=/opt/hpcx/nccl_rdma_sharp_plugin/lib:/opt/nccl-rdma-sharp-plugins/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64 NVIDIA_VISIBLE_DEVICES=all NVIDIA_DRIVER_CAPABILITIES=compute,utility NV_CUDA_LIB_VERSION=11.7.0-1 NV_NVTX_VERSION=11.7.50-1 NV_LIBNPP_VERSION=11.7.3.21-1 NV_LIBNPP_PACKAGE=libnpp-11-7=11.7.3.21-1 NV_LIBCUSPARSE_VERSION=11.7.3.50-1 NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-7 NV_LIBCUBLAS_VERSION=11.10.1.25-1 NV_LIBCUBLAS_PACKAGE=libcublas-11-7=11.10.1.25-1 NV_LIBNCCL_PACKAGE_NAME=libnccl2 NV_LIBNCCL_PACKAGE_VERSION=2.13.4-1 NCCL_VERSION=2.13.4-1 NV_LIBNCCL_PACKAGE=libnccl2=2.13.4-1+cuda11.7 NVIDIA_PRODUCT_NAME=CUDA NVIDIA_CUDA_END_OF_LIFE=1 NV_CUDA_CUDART_DEV_VERSION=11.7.60-1 NV_NVML_DEV_VERSION=11.7.50-1 NV_LIBCUSPARSE_DEV_VERSION=11.7.3.50-1 NV_LIBNPP_DEV_VERSION=11.7.3.21-1 NV_LIBNPP_DEV_PACKAGE=libnpp-dev-11-7=11.7.3.21-1 NV_LIBCUBLAS_DEV_VERSION=11.10.1.25-1 NV_LIBCUBLAS_DEV_PACKAGE_NAME=libcublas-dev-11-7 NV_LIBCUBLAS_DEV_PACKAGE=libcublas-dev-11-7=11.10.1.25-1 NV_NVPROF_VERSION=11.7.50-1 NV_NVPROF_DEV_PACKAGE=cuda-nvprof-11-7=11.7.50-1 NV_LIBNCCL_DEV_PACKAGE_NAME=libnccl-dev NV_LIBNCCL_DEV_PACKAGE_VERSION=2.13.4-1 NV_LIBNCCL_DEV_PACKAGE=libnccl-dev=2.13.4-1+cuda11.7 LIBRARY_PATH=/usr/local/cuda/lib64/stubs NV_CUDNN_VERSION=8.5.0.96 NV_CUDNN_PACKAGE_NAME=libcudnn8 NV_CUDNN_PACKAGE=libcudnn8=8.5.0.96-1+cuda11.7 NV_CUDNN_PACKAGE_DEV=libcudnn8-dev=8.5.0.96-1+cuda11.7 GPU_TYPE=cu117 PYTHON_VERSION=3.8 PYTORCH_BUILD_VERSION=1.13.0 DISTRIBUTED_BACKEND=sccl INTERNAL_OR_PUBLIC=internal PYTORCH_TYPE=stable DSVM=False LANG=en_US.UTF-8 CONDA_ENVIRONMENT_PATH=/opt/conda/envs/ptca AZUREML_CONDA_ENVIRONMENT_PATH=/opt/conda/envs/ptca CONDA_DEFAULT_ENV=ptca CONDA_PREFIX=/opt/conda/envs/ptca OPAL_PREFIX=/opt/hpcx/ompi SINGULARITY_IMAGE_FRAMEWORK=PYTORCH SINGULARITY_IMAGE_ACCELERATOR=NVIDIA SINGULARITY_IMAGE_ACCELERATOR_SKU=A100 NCCL_ASYNC_ERROR_HANDLING=1 TZ=US/Pacific SINGULARITY_BASE_IMAGE=base/job/pytorch/ptca-1.13.0-cuda11.7:20230414T112529310
镜像标签
biweekly.202304.1: acptTag 2023-04-03T08:05:02Z: buildDate 8.5.0.96: com.nvidia.cudnn.version 592d91bdbe3ba56c8dc90936386028458831a59e: commitSHA Singularity Engineering Team <singularity@microsoft.com>: maintainer Azure Container for Pytorch: name 2023-04-04T03:41:49Z: releaseDate
镜像安全扫描 查看Trivy扫描报告

系统OS: ubuntu 20.04 扫描引擎: Trivy 扫描时间: 2024-10-27 12:06

低危漏洞:876 中危漏洞:9712 高危漏洞:754 严重漏洞:39
docker.io/nikghosh09/transformers:sing_v1 (ubuntu 20.04) (ubuntu) Conda (conda-pkg) Node.js (node-pkg) Python (python-pkg) opt/conda/envs/ptca/lib/python3.8/site-packages/nebulaml/bin/n2e0b2u2la_mars (gobinary) opt/conda/envs/ptca/lib/python3.8/site-packages/nebulaml/bin/n2e0b2u2la_monitor_service (gobinary) opt/conda/envs/ptca/lib/python3.8/site-packages/nebulaml/bin/n2e0b2u2la_nebula-data (gobinary) opt/conda/envs/ptca/lib/python3.8/site-packages/nebulaml/bin/n2e0b2u2la_saturn (gobinary) opt/conda/envs/ptca/lib/python3.8/site-packages/torch_nebula/bin/n2e0b2u2la_mars (gobinary) opt/conda/envs/ptca/lib/python3.8/site-packages/torch_nebula/bin/n2e0b2u2la_monitor_service (gobinary) opt/conda/envs/ptca/lib/python3.8/site-packages/torch_nebula/bin/n2e0b2u2la_nebula-data (gobinary) opt/conda/envs/ptca/lib/python3.8/site-packages/torch_nebula/bin/n2e0b2u2la_saturn (gobinary) usr/local/bin/gosu (gobinary) usr/share/dotnet/shared/Microsoft.NETCore.App/2.1.30/Microsoft.NETCore.App.deps.json (dotnet-core) /etc/ssh/ssh_host_ed25519_key () /etc/ssh/ssh_host_rsa_key () /opt/conda/envs/ptca/lib/python3.8/site-packages/PyJWT-2.6.0.dist-info/METADATA () /opt/conda/envs/ptca/lib/python3.8/site-packages/google/auth/crypt/__pycache__/_python_rsa.cpython-38.pyc () /etc/ssh/ssh_host_ecdsa_key ()

Docker拉取命令 无权限下载?点我修复 

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nikghosh09/transformers:sing_v1
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nikghosh09/transformers:sing_v1  docker.io/nikghosh09/transformers:sing_v1

Containerd拉取命令 

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nikghosh09/transformers:sing_v1
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nikghosh09/transformers:sing_v1  docker.io/nikghosh09/transformers:sing_v1

Shell快速替换命令 

sed -i 's#nikghosh09/transformers:sing_v1#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nikghosh09/transformers:sing_v1#' 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/nikghosh09/transformers:sing_v1 && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nikghosh09/transformers:sing_v1  docker.io/nikghosh09/transformers:sing_v1'

Ansible快速分发-Containerd 

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nikghosh09/transformers:sing_v1 && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nikghosh09/transformers:sing_v1  docker.io/nikghosh09/transformers:sing_v1'

镜像构建历史 


# 2023-08-22 01:56:15  2.80KB 执行命令并创建新的镜像层
RUN /bin/bash --login -c /opt/microsoft/_singularity/validations/validator.sh # buildkit
                        
# 2023-08-22 01:56:15  0.00B 设置环境变量 SINGULARITY_IMAGE_ACCELERATOR
ENV SINGULARITY_IMAGE_ACCELERATOR=NVIDIA
                        
# 2023-08-22 01:56:12  107.64KB 复制新文件或目录到容器中
COPY /validations /opt/microsoft/_singularity/validations/ # buildkit
                        
# 2023-08-22 01:56:11  466.41MB 执行命令并创建新的镜像层
RUN /bin/bash --login -c pip install --no-cache-dir -r requirements.txt # buildkit
                        
# 2023-08-22 01:55:19  11.52MB 执行命令并创建新的镜像层
RUN /bin/bash --login -c pip install --no-cache-dir --upgrade pip # buildkit
                        
# 2023-08-22 01:55:15  231.00B 复制新文件或目录到容器中
COPY requirements.txt . # buildkit
                        
# 2023-08-22 01:55:15  67.93MB 执行命令并创建新的镜像层
RUN /bin/bash --login -c apt-get update &&     apt-get install --no-install-recommends --no-install-suggests -yq         git vim &&     rm -rf /var/lib/apt/lists/* &&     apt-get purge --auto-remove &&     apt-get clean # buildkit
                        
# 2023-05-10 10:15:12  0.00B 设置环境变量 SINGULARITY_BASE_IMAGE
ENV SINGULARITY_BASE_IMAGE=base/job/pytorch/ptca-1.13.0-cuda11.7:20230414T112529310
                        
# 2023-05-10 10:15:12  0.00B 添加元数据标签
LABEL maintainer=Singularity Engineering Team <singularity@microsoft.com>
                        
# 2023-05-10 10:15:12  0.00B 设置工作目录为/home/aiscuser
WORKDIR /home/aiscuser
                        
# 2023-05-10 10:15:12  0.00B 指定运行容器时使用的用户
USER root
                        
# 2023-05-10 10:15:12  0.00B 设置环境变量 SINGULARITY_IMAGE_ACCELERATOR_SKU
ENV SINGULARITY_IMAGE_ACCELERATOR_SKU=A100
                        
# 2023-05-10 10:15:12  0.00B 设置环境变量 SINGULARITY_IMAGE_ACCELERATOR
ENV SINGULARITY_IMAGE_ACCELERATOR=NVIDIA
                        
# 2023-05-10 10:15:12  0.00B 设置环境变量 SINGULARITY_IMAGE_FRAMEWORK
ENV SINGULARITY_IMAGE_FRAMEWORK=PYTORCH
                        
# 2023-05-10 10:14:33  197.56KB 执行命令并创建新的镜像层
RUN /bin/bash --login -c CC=mpicc MPICC=mpicc pip install mpi4py --no-binary mpi4py # buildkit
                        
# 2023-05-10 10:14:28  41.00B 执行命令并创建新的镜像层
RUN /bin/bash --login -c ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone # buildkit
                        
# 2023-05-10 10:14:28  0.00B 设置环境变量 TZ
ENV TZ=US/Pacific
                        
# 2023-05-10 10:14:28  0.00B 设置环境变量 NCCL_ASYNC_ERROR_HANDLING
ENV NCCL_ASYNC_ERROR_HANDLING=1
                        
# 2023-05-10 10:14:28  0.00B 设置环境变量 LD_LIBRARY_PATH
ENV LD_LIBRARY_PATH=/opt/hpcx/nccl_rdma_sharp_plugin/lib:/opt/nccl-rdma-sharp-plugins/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2023-04-04 11:42:00  0.00B 
/bin/bash --login -c #(nop)  LABEL releaseDate=2023-04-04T03:41:49Z
                        
# 2023-04-04 11:41:55  0.00B 
/bin/bash --login -c #(nop)  LABEL acptTag=biweekly.202304.1
                        
# 2023-04-03 17:18:35  76.82KB 
|2 BUILD_COMMIT_SHA=592d91bdbe3ba56c8dc90936386028458831a59e BUILD_DATE=2023-04-03T08:05:02Z /bin/bash --login -c echo "PTCA build finished."
                        
# 2023-04-03 17:18:23  0.00B 
/bin/bash --login -c #(nop)  LABEL name=Azure Container for Pytorch maintainer=Microsoft ACPT team buildDate=2023-04-03T08:05:02Z commitSHA=592d91bdbe3ba56c8dc90936386028458831a59e
                        
# 2023-04-03 17:18:17  13.47KB 
/bin/bash --login -c #(nop) COPY file:36bc6bd760ec7aaac0060afe157e1605403554b563a002d6a2618bfa09fb5b5c in /getting_started.md 
                        
# 2023-04-03 17:18:12  597.41KB 
/bin/bash --login -c #(nop) COPY file:fa28425ba2408bcf007a93b6c96327bf8b9e0bbf4df22d513c7b388eda3df9d6 in /NOTICE.txt 
                        
# 2023-04-03 17:18:07  78.29KB 
|2 BUILD_COMMIT_SHA=592d91bdbe3ba56c8dc90936386028458831a59e BUILD_DATE=2023-04-03T08:05:02Z /bin/bash --login -c wget https://raw.githubusercontent.com/microsoft/containerregistry/main/legal/Container-Images-Legal-Notice.md -P /
                        
# 2023-04-03 17:17:55  77.98KB 
|2 BUILD_COMMIT_SHA=592d91bdbe3ba56c8dc90936386028458831a59e BUILD_DATE=2023-04-03T08:05:02Z /bin/bash --login -c wget https://raw.githubusercontent.com/microsoft/onnxruntime/master/dockerfiles/LICENSE-IMAGE.txt -P /
                        
# 2023-04-03 17:17:42  376.84KB 
|2 BUILD_COMMIT_SHA=592d91bdbe3ba56c8dc90936386028458831a59e BUILD_DATE=2023-04-03T08:05:02Z /bin/bash --login -c wget https://raw.githubusercontent.com/microsoft/onnxruntime/master/ThirdPartyNotices.txt -P /
                        
# 2023-04-03 17:17:29  1.19KB 
/bin/bash --login -c #(nop) COPY file:89a5e72c44a0a2e2530811b95265c47c371ed04140ba8e2504cd65e515479332 in /nccl_bandwidth_test.sh 
                        
# 2023-04-03 17:17:24  0.00B 
/bin/bash --login -c #(nop)  ENV LD_LIBRARY_PATH=/opt/nccl-rdma-sharp-plugins/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
                        
# 2023-04-03 17:17:19  7.23MB 
|2 BUILD_COMMIT_SHA=592d91bdbe3ba56c8dc90936386028458831a59e BUILD_DATE=2023-04-03T08:05:02Z /bin/bash --login -c bash get_package_versions.sh     && rm /get_package_versions.sh
                        
# 2023-04-03 17:17:04  198.00B 
/bin/bash --login -c #(nop) COPY file:e4f2e038f00586aee06a9fa9253a57693cc879cffed4caaf986b3227499b08b6 in /get_package_versions.sh 
                        
# 2023-04-03 17:16:59  76.82KB 
|2 BUILD_COMMIT_SHA=592d91bdbe3ba56c8dc90936386028458831a59e BUILD_DATE=2023-04-03T08:05:02Z /bin/bash --login -c bash clean_up_ptca.sh     && rm /clean_up_ptca.sh
                        
# 2023-04-03 17:16:33  457.00B 
/bin/bash --login -c #(nop) COPY file:6db288eecc9fddb982df0bbed2e2cadd7e7507a1812abcd248a97668d00d3303 in /clean_up_ptca.sh 
                        
# 2023-04-03 17:16:26  76.82KB 
|2 BUILD_COMMIT_SHA=592d91bdbe3ba56c8dc90936386028458831a59e BUILD_DATE=2023-04-03T08:05:02Z /bin/bash --login -c bash call_patch_files.sh && rm -r /patches && rm /call_patch_files.sh
                        
# 2023-04-03 17:16:13  261.00B 
/bin/bash --login -c #(nop) COPY file:eac3d38ac4124491d33082583e16e4ff1ecb1cac27ccd05a4b7c28c9d933431e in /call_patch_files.sh 
                        
# 2023-04-03 17:16:06  0.00B 
/bin/bash --login -c #(nop) COPY dir:30c16d6156e04534063183ea624e44b999fd75ef95de52018dcc70adc98b9406 in /patches 
                        
# 2023-04-03 17:15:58  6.48GB 
/bin/bash --login -c #(nop) COPY dir:82eefb3036e1bb9986cbf0117cd200dedf5286b714b4e9837e3d7f29cf43c079 in /opt/conda/envs/ 
                        
# 2023-04-03 17:13:32  76.82KB 
|2 BUILD_COMMIT_SHA=592d91bdbe3ba56c8dc90936386028458831a59e BUILD_DATE=2023-04-03T08:05:02Z /bin/bash --login -c rm -rf /opt/conda/envs/
                        
# 2023-04-03 17:13:19  0.00B 
/bin/bash --login -c #(nop)  ARG BUILD_COMMIT_SHA
                        
# 2023-04-03 17:13:14  0.00B 
/bin/bash --login -c #(nop)  ARG BUILD_DATE
                        
# 2023-04-03 16:28:23  76.82KB 
/bin/bash --login -c echo "Verified Singularity installation."
                        
# 2023-04-03 16:28:11  79.62KB 
/bin/bash --login -c /opt/microsoft/_singularity/validations/validator.sh
                        
# 2023-04-03 16:27:45  0.00B 
/bin/bash --login -c #(nop)  ENV SINGULARITY_IMAGE_ACCELERATOR_SKU=
                        
# 2023-04-03 16:27:40  0.00B 
/bin/bash --login -c #(nop)  ENV SINGULARITY_IMAGE_ACCELERATOR=NVIDIA
                        
# 2023-04-03 16:27:35  0.00B 
/bin/bash --login -c #(nop)  ENV SINGULARITY_IMAGE_FRAMEWORK=PyTorch
                        
# 2023-04-03 16:27:30  109.02KB 
/bin/bash --login -c #(nop) COPY dir:303046c532bc3060e414863596cfd1e47eb4380cce34afceca3281b4fc2e965c in /opt/microsoft/_singularity/validations/ 
                        
# 2023-04-03 16:27:25  541.66MB 
/bin/bash --login -c /opt/microsoft/_singularity/installations/singularity/installer.sh
                        
# 2023-04-03 16:25:14  67.24KB 
/bin/bash --login -c #(nop) COPY dir:cfedefbde912d9ae5142ddd7f97b6579ac1b93abc5fcac6afcfe3c55a41618e9 in /opt/microsoft/_singularity/installations/ 
                        
# 2023-04-03 16:24:54  0.00B 
/bin/bash --login -c #(nop)  ENV OPAL_PREFIX=/opt/hpcx/ompi PATH=/usr/local/mpi/bin:/usr/local/ucx/bin:/opt/conda/envs/ptca/bin:/opt/conda/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2023-04-03 16:24:49  2.45GB 
|1 PTEBIC_STORAGE_HPCX_SAS_TOKEN=si=read_policy&spr=https&sv=2021-06-08&sr=c&sig=kpQKbmNEORCCELcYAIMDag5CccWbS6H%2F8TkN4e1RaJY%3D /bin/bash --login -c bash install_system_packages.sh $PTEBIC_STORAGE_HPCX_SAS_TOKEN     && rm /install_system_packages.sh     && rm -rf /training
                        
# 2023-04-03 16:21:06  11.24KB 
/bin/bash --login -c #(nop) COPY dir:f092ea73db3661090acc4cc59650f351294c32336a2de1613d956430ec1ff6bd in /training/install/system_packages 
                        
# 2023-04-03 16:21:02  51.42KB 
|1 PTEBIC_STORAGE_HPCX_SAS_TOKEN=si=read_policy&spr=https&sv=2021-06-08&sr=c&sig=kpQKbmNEORCCELcYAIMDag5CccWbS6H%2F8TkN4e1RaJY%3D /bin/bash --login -c echo "sudo() { command sudo env PATH="\$PATH" "\$@"; }"  >> /root/.bashrc
                        
# 2023-04-03 16:20:52  386.38MB 
/bin/bash --login -c #(nop) COPY dir:4f7f639b8a96783a638b073262c781b9279334e6d2daa7117a6694c886be84aa in /training/install/internal_packages/download_internal_packages/msccl_package 
                        
# 2023-04-03 16:20:41  1.69KB 
/bin/bash --login -c #(nop) COPY file:025cf7ebd5b079ce6e5403b5fe5ebac75813dbad6e5b89c35112e6168ffcd3e6 in /install_system_packages.sh 
                        
# 2023-04-03 16:20:37  0.00B 
/bin/bash --login -c #(nop)  ARG PTEBIC_STORAGE_HPCX_SAS_TOKEN
                        
# 2023-04-03 16:20:34  0.00B 
/bin/bash --login -c #(nop)  ENV CONDA_DEFAULT_ENV=ptca CONDA_PREFIX=/opt/conda/envs/ptca
                        
# 2023-04-03 16:20:30  0.00B 
/bin/bash --login -c #(nop)  ENV PATH=/opt/conda/envs/ptca/bin:/opt/conda/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2023-04-03 16:20:26  205.43MB 
/bin/bash --login -c conda create -y -p $CONDA_ENVIRONMENT_PATH python=$PYTHON_VERSION     && conda clean --all --yes
                        
# 2023-04-03 16:19:42  0.00B 
/bin/bash --login -c #(nop)  ENV AZUREML_CONDA_ENVIRONMENT_PATH=/opt/conda/envs/ptca
                        
# 2023-04-03 16:19:39  0.00B 
/bin/bash --login -c #(nop)  ENV CONDA_ENVIRONMENT_PATH=/opt/conda/envs/ptca
                        
# 2023-04-03 16:19:35  261.56MB 
|5 BUILD_DISTRIBUTED_BACKEND=sccl BUILD_INTERNAL_OR_PUBLIC=internal BUILD_PYTHON_VERSION=3.8 BUILD_PYTORCH_TYPE=stable BUILD_PYTORCH_VERSION=1.13.0 /bin/bash --login -c curl -fsSL -o install_conda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh     && bash install_conda.sh -b -p /opt/conda     && conda init bash     && conda config --set auto_activate_base false     && conda update --all     && echo "if [ -z "\${CONDA_PREFIX+x}" ]; then :; else conda activate "\$CONDA_PREFIX"; fi" >> /root/.bashrc     && rm install_conda.sh && /opt/conda/bin/conda clean -ya
                        
# 2023-04-03 16:18:52  0.00B 
/bin/bash --login -c #(nop)  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
                        
# 2023-04-03 16:18:50  0.00B 
/bin/bash --login -c #(nop)  ENV LANG=en_US.UTF-8
                        
# 2023-04-03 16:18:48  4.90MB 
|5 BUILD_DISTRIBUTED_BACKEND=sccl BUILD_INTERNAL_OR_PUBLIC=internal BUILD_PYTHON_VERSION=3.8 BUILD_PYTORCH_TYPE=stable BUILD_PYTORCH_VERSION=1.13.0 /bin/bash --login -c sed -i -e 's/# en_US.UTF-8 UTF-8/en_US.UTF-8 UTF-8/' /etc/locale.gen &&     dpkg-reconfigure --frontend=noninteractive locales &&     update-locale LANG=en_US.UTF-8
                        
# 2023-04-03 16:18:34  459.18MB 
|5 BUILD_DISTRIBUTED_BACKEND=sccl BUILD_INTERNAL_OR_PUBLIC=internal BUILD_PYTHON_VERSION=3.8 BUILD_PYTORCH_TYPE=stable BUILD_PYTORCH_VERSION=1.13.0 /bin/bash --login -c bash install_essential_packages.sh     && rm /install_essential_packages.sh
                        
# 2023-04-03 16:10:04  467.00B 
/bin/bash --login -c #(nop) COPY file:17c450ba615149f9ac5bbc9b2fc627bd23269c1b38d8ab5e7efa1d1acb1112c4 in /install_cmake.sh 
                        
# 2023-04-03 16:10:03  608.00B 
/bin/bash --login -c #(nop) COPY file:2fcdfe3b21b65418eb505e7a67e9f88fd8301ca2814d5cfe950da6a5a2e36749 in /install_essential_packages.sh 
                        
# 2023-04-03 16:10:02  1.17GB 
|5 BUILD_DISTRIBUTED_BACKEND=sccl BUILD_INTERNAL_OR_PUBLIC=internal BUILD_PYTHON_VERSION=3.8 BUILD_PYTORCH_TYPE=stable BUILD_PYTORCH_VERSION=1.13.0 /bin/bash --login -c apt update && apt upgrade -y
                        
# 2023-04-03 16:08:32  0.00B 
/bin/bash --login -c #(nop)  ENV DSVM=False
                        
# 2023-04-03 16:08:31  0.00B 
/bin/bash --login -c #(nop)  ARG DSVM
                        
# 2023-04-03 16:08:30  0.00B 
/bin/bash --login -c #(nop)  ENV PYTORCH_TYPE=stable
                        
# 2023-04-03 16:08:29  0.00B 
/bin/bash --login -c #(nop)  ARG BUILD_PYTORCH_TYPE
                        
# 2023-04-03 16:08:28  0.00B 
/bin/bash --login -c #(nop)  ENV INTERNAL_OR_PUBLIC=internal
                        
# 2023-04-03 16:08:27  0.00B 
/bin/bash --login -c #(nop)  ARG BUILD_INTERNAL_OR_PUBLIC
                        
# 2023-04-03 16:08:26  0.00B 
/bin/bash --login -c #(nop)  ENV DISTRIBUTED_BACKEND=sccl
                        
# 2023-04-03 16:08:25  0.00B 
/bin/bash --login -c #(nop)  ARG BUILD_DISTRIBUTED_BACKEND
                        
# 2023-04-03 16:08:24  0.00B 
/bin/bash --login -c #(nop)  ENV PYTORCH_BUILD_VERSION=1.13.0
                        
# 2023-04-03 16:08:23  0.00B 
/bin/bash --login -c #(nop)  ARG BUILD_PYTORCH_VERSION
                        
# 2023-04-03 16:08:22  0.00B 
/bin/bash --login -c #(nop)  ENV PYTHON_VERSION=3.8
                        
# 2023-04-03 16:08:21  0.00B 
/bin/bash --login -c #(nop)  ARG BUILD_PYTHON_VERSION
                        
# 2023-04-03 16:08:20  0.00B 
/bin/bash --login -c #(nop)  SHELL [/bin/bash --login -c]
                        
# 2023-04-03 16:08:19  0.00B 
/bin/sh -c #(nop)  ENV GPU_TYPE=cu117
                        
# 2023-04-03 16:08:19  0.00B 
/bin/sh -c #(nop)  ARG BUILD_GPU_TYPE
                        
# 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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    "Id": "sha256:255fc450efbcd5f23bcac03ed060be2e21fe62951d268fb0e5f6cf4d06b1e649",
    "RepoTags": [
        "nikghosh09/transformers:sing_v1",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nikghosh09/transformers:sing_v1"
    ],
    "RepoDigests": [
        "nikghosh09/transformers@sha256:d942d9d397760b0ab7800ca17aa7925b9f472f0f1296563e647b578a4118d23f",
        "swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/nikghosh09/transformers@sha256:d942d9d397760b0ab7800ca17aa7925b9f472f0f1296563e647b578a4118d23f"
    ],
    "Parent": "",
    "Comment": "buildkit.dockerfile.v0",
    "Created": "2023-08-21T17:56:15.597681526Z",
    "Container": "",
    "ContainerConfig": null,
    "DockerVersion": "",
    "Author": "",
    "Config": {
        "Hostname": "",
        "Domainname": "",
        "User": "root",
        "AttachStdin": false,
        "AttachStdout": false,
        "AttachStderr": false,
        "Tty": false,
        "OpenStdin": false,
        "StdinOnce": false,
        "Env": [
            "PATH=/usr/local/mpi/bin:/usr/local/ucx/bin:/opt/conda/envs/ptca/bin:/opt/conda/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=11.7 brand=tesla,driver\u003e=450,driver\u003c451 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 brand=tesla,driver\u003e=510,driver\u003c511 brand=unknown,driver\u003e=510,driver\u003c511 brand=nvidia,driver\u003e=510,driver\u003c511 brand=nvidiartx,driver\u003e=510,driver\u003c511 brand=quadro,driver\u003e=510,driver\u003c511 brand=quadrortx,driver\u003e=510,driver\u003c511 brand=titan,driver\u003e=510,driver\u003c511 brand=titanrtx,driver\u003e=510,driver\u003c511 brand=geforce,driver\u003e=510,driver\u003c511 brand=geforcertx,driver\u003e=510,driver\u003c511",
            "NV_CUDA_CUDART_VERSION=11.7.60-1",
            "NV_CUDA_COMPAT_PACKAGE=cuda-compat-11-7",
            "CUDA_VERSION=11.7.0",
            "LD_LIBRARY_PATH=/opt/hpcx/nccl_rdma_sharp_plugin/lib:/opt/nccl-rdma-sharp-plugins/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64",
            "NVIDIA_VISIBLE_DEVICES=all",
            "NVIDIA_DRIVER_CAPABILITIES=compute,utility",
            "NV_CUDA_LIB_VERSION=11.7.0-1",
            "NV_NVTX_VERSION=11.7.50-1",
            "NV_LIBNPP_VERSION=11.7.3.21-1",
            "NV_LIBNPP_PACKAGE=libnpp-11-7=11.7.3.21-1",
            "NV_LIBCUSPARSE_VERSION=11.7.3.50-1",
            "NV_LIBCUBLAS_PACKAGE_NAME=libcublas-11-7",
            "NV_LIBCUBLAS_VERSION=11.10.1.25-1",
            "NV_LIBCUBLAS_PACKAGE=libcublas-11-7=11.10.1.25-1",
            "NV_LIBNCCL_PACKAGE_NAME=libnccl2",
            "NV_LIBNCCL_PACKAGE_VERSION=2.13.4-1",
            "NCCL_VERSION=2.13.4-1",
            "NV_LIBNCCL_PACKAGE=libnccl2=2.13.4-1+cuda11.7",
            "NVIDIA_PRODUCT_NAME=CUDA",
            "NVIDIA_CUDA_END_OF_LIFE=1",
            "NV_CUDA_CUDART_DEV_VERSION=11.7.60-1",
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更多版本

docker.io/nikghosh09/transformers:sing_v1

linux/amd64 docker.io19.31GB2024-10-18 00:53
219