ContainersNVIDIADeepSeek-R1NVIDIALlama-3.1-Nemotron-70B-InstructNVIDIAPyTorch
CollectionsNVIDIAOmniverse Kit (FB)NVIDIADeepStream SDKNVIDIAOmniverse Kit App Streaming
ModelsNVIDIAStyleGAN3 pretrained modelsNVIDIAPeopleNetNVIDIATrafficCamNet
ResourcesNVIDIARiva Skills Quick Start
Helm ChartsNVIDIAGPU OperatorNVIDIANVIDIA NIM Operator
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
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
com.nvidia.build.ref=8d28f2ff75a3f186220e187654c5890a49f8d87a
04/15/2025 8:00 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
NVIDIA_BUILD_REF=8d28f2ff75a3f186220e187654c5890a49f8d87a
04/15/2025 8:00 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
com.nvidia.build.id=159049541
04/15/2025 8:00 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
NVIDIA_BUILD_ID=159049541
04/15/2025 8:00 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
NVIDIA_BUILD_ID=159049541
04/15/2025 8:00 PM UTC
sha256:656e5b24ffa0f8f319a7aac1dda4a64083a944598316754c994514d91b4374baCOPY
entrypoint.d/ /opt/nvidia/entrypoint.d/
04/15/2025 8:00 PM UTC
sha256:874f48802855247c151a18faa9bd509c1df25a705e8e731ec8eef4f57ccacfb6RUN
NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b 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 ${_CUDA_COMPAT_PATH}/lib
04/15/2025 8:00 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
TORCH_NCCL_USE_COMM_NONBLOCKING=0
04/15/2025 8:00 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
CUDA_MODULE_LOADING=LAZY
04/15/2025 8:00 PM UTC
sha256:081df790f1347b8b43246452ba88444bcce745d5188a0848ff557b97f8e10ceeRUN
NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali if [ "${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
04/15/2025 8:00 PM UTC
...