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=f7207771a583a8091f425dfdbcaae60bbce7fe76
08/08/2025 5:17 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
NVIDIA_BUILD_REF=f7207771a583a8091f425dfdbcaae60bbce7fe76
08/08/2025 5:17 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
com.nvidia.build.id=197421316
08/08/2025 5:17 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
NVIDIA_BUILD_ID=197421316
08/08/2025 5:17 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
NVIDIA_BUILD_ID=197421316
08/08/2025 5:17 PM UTC
sha256:fbcd7b1d1d2071e474187529d3323e6b8627e996f3f3c2f2c2096839e94e2516RUN
NVIDIA_PYTORCH_VERSION=25.08 PYTORCH_BUILD_VERSION=2.8.0a0+34c6371 NVFUSER_BUILD_VERSION=1a27c18 TARGETARCH=arm64 PYVER=3.12 L4T=1 ENABLE_MITMPROXY=0 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali cd /opt/pytorch/pytorch/ &&
  sed -i "s#    if (props.computeMode != cudaComputeModeDefault) {#    int computeMode = -1;\n    TP_CUDA_CHECK(cudaDeviceGetAttribute(\&computeMode, cudaDevAttrComputeMode, device.index));\n    if (computeMode != cudaComputeModeDefault) {#g" ./third_party/tensorpipe/tensorpipe/channel/cuda_ipc/context_impl.cc &&
  cd -
08/08/2025 5:17 PM UTC
sha256:8e4217eb7c291a3fc09baf8c67fdde24e379fbc1e684e0e6f474d87c341dddd9COPY
entrypoint.d/ /opt/nvidia/entrypoint.d/
08/08/2025 5:17 PM UTC
sha256:52b2bb027b60a15fe699b17dc2e4a41e6adad99b10ec83e8b0e7e6b1fc922542COPY
constraint.txt /etc/pip/original_constraint.txt
08/08/2025 5:17 PM UTC
sha256:7574823d01addc084893eb8190031be3578848f8fd16f67a25ec547336d7538cCOPY
restricted_constraint.txt /etc/pip/constraint.txt
08/08/2025 5:17 PM UTC
sha256:094c01d18088f4afc5dbd0559d9d5e02e4dcd3c50d6a2be91d113586fbfc13d6RUN
NVIDIA_PYTORCH_VERSION=25.08 PYTORCH_BUILD_VERSION=2.8.0a0+34c6371 NVFUSER_BUILD_VERSION=1a27c18 TARGETARCH=arm64 PYVER=3.12 L4T=1 ENABLE_MITMPROXY=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
08/08/2025 5:17 PM UTC
...

NVIDIA uses cookies to improve your experience on our web site. We and our third-party partners also use cookies and other tools to collect and record information you provide as well as information about your interactions with our websites for performance improvement, analytics, and to assist in marketing efforts. By clicking "Accept All", you consent to our use of cookies and other tools as described in our Cookie Policy. You can manage your cookie settings by clicking on "Manage Settings." By continuing to use this site or by clicking one of the buttons below, you agree to our Terms of Service (which contains important waivers). Please see our Privacy Policy for more information on our privacy practices.