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NVIDIA
NVIDIA
PyTorch
Container
NVIDIA
NVIDIA
PyTorch

PyTorch is a GPU accelerated tensor computational framework. Functionality can be extended with common Python libraries such as NumPy and SciPy. Automatic differentiation is done with a tape-based system at the functional and neural network layer levels.

NVIDIA AI Enterprise Supported
LayerLabelCreated
f80e3da6b43f8a8ee5383c07d7e5e62a8bf75646a552d0dd2df0cd19f93fcba1CONFIG
Entrypoint /opt/nvidia/nvidia_entrypoint.sh; WorkingDir /workspace; ExposedPorts 6006/tcp, 8888/tcp
05/22/2025 5:31 AM UTC
1e4305a6294c3b43c4b887fbf144dab2c2ff2b5ebe3a7c4f1b0a676db24cf618ARG
NVIDIA_BUILD_REF=0f499560921269b0135bf88c85232c1f26bcecfb
05/22/2025 5:31 AM UTC
951ae22717f8e428eff6c95f021cb3247acb183871bbea82783b117e69cc60b7LABEL
com.nvidia.build.id=170559088
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6cf524257195330cabb6a68364b26459f3be016959edf9cdd01c1727daabc545ENV
NVIDIA_BUILD_ID=170559088
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016f992109ea04cd5cd43e796bf85b5ffc44c9f8741ca57da74f6635dc7ae900ARG
NVIDIA_BUILD_ID=170559088
05/22/2025 5:31 AM UTC
c1498a16750acc830b173c057e7420be86c45a5cd9d8838574661ca6173d3fa0COPY
entrypoint.d/ /opt/nvidia/entrypoint.d/
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a20acb5857e0051c0c78e1b768cf0e5c9cfc13aa01fe7d40d6d7482e0d830ee6RUN
NVIDIA_PYTORCH_VERSION=25.05 PYTORCH_BUILD_VERSION=2.8.0a0+5228986 NVFUSER_BUILD_VERSION=9bf5aca TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali 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 ${_CUDA_COMPAT_PATH}/lib
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b67279c6f9de7255fadb91176682c208ccaf7712075d4b5c76c5268ae7c50af4ENV
TORCH_NCCL_USE_COMM_NONBLOCKING=0
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82dcab69474289eadca2cd16bb1ea71b46e5962b7f49bac71c441d99350e5f66ENV
CUDA_MODULE_LOADING=LAZY
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15211124ea767b762ead88663566cd621393a798394c5dce3457124eacc719b1RUN
NVIDIA_PYTORCH_VERSION=25.05 PYTORCH_BUILD_VERSION=2.8.0a0+5228986 NVFUSER_BUILD_VERSION=9bf5aca TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali if [ "${L4T}" = "1" ]; then echo "Not installing Transformer Engine in iGPU container until Version variable is set"; else /nvidia/build-scripts/installCAL.sh &&
  /nvidia/build-scripts/installCUBLASMP.sh &&
  /nvidia/build-scripts/installNVSHMEM.sh &&
  git clone -b release_v${TRANSFORMER_ENGINE_VERSION} --single-branch --recursive https://github.com/NVIDIA/TransformerEngine.git &&
  env NVTE_CUDA_ARCHS="70;80;89;90;100;120" NVTE_BUILD_THREADS_PER_JOB=8 pip install --no-cache-dir --no-build-isolation ./TransformerEngine &&
  rm -rf TransformerEngine; fi
05/22/2025 5:31 AM UTC
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