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.

LayerLabelCreated
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com.nvidia.build.ref=0f499560921269b0135bf88c85232c1f26bcecfb
05/22/2025 2:30 AM UTC
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05/22/2025 2:30 AM UTC
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com.nvidia.build.id=170559090
05/22/2025 2:30 AM UTC
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NVIDIA_BUILD_ID=170559090
05/22/2025 2:30 AM UTC
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NVIDIA_BUILD_ID=170559090
05/22/2025 2:30 AM UTC
sha256:2f074dc76c5da961ce13817b02fa1e3c3070ad4b94970aa7f52f6c0d63b07696COPY
entrypoint.d/ /opt/nvidia/entrypoint.d/
05/22/2025 2:30 AM UTC
sha256:a152112837e81c884fcadd924cd34cc4664ee1441c5ede7611db336e9f177645RUN
NVIDIA_PYTORCH_VERSION=25.05 PYTORCH_BUILD_VERSION=2.8.0a0+5228986 NVFUSER_BUILD_VERSION=9bf5aca TARGETARCH=arm64 PYVER=3.12 PYVER_MAJMIN=312 L4T=1 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 ${_CUDA_COMPAT_PATH}/lib
05/22/2025 2:30 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
TORCH_NCCL_USE_COMM_NONBLOCKING=0
05/22/2025 2:30 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
CUDA_MODULE_LOADING=LAZY
05/22/2025 2:30 AM UTC
sha256:172c5454ee0da01d12cafaef9e4e31874370248d88c99b759a3543133c7cb335RUN
NVIDIA_PYTORCH_VERSION=25.05 PYTORCH_BUILD_VERSION=2.8.0a0+5228986 NVFUSER_BUILD_VERSION=9bf5aca TARGETARCH=arm64 PYVER=3.12 PYVER_MAJMIN=312 L4T=1 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali if [ "${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 2:30 AM UTC
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