Skip to main content
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
    PyTorch
    Container
    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
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
    com.nvidia.build.ref=8d28f2ff75a3f186220e187654c5890a49f8d87a
    		04/15/2025 7:20 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    NVIDIA_BUILD_REF=8d28f2ff75a3f186220e187654c5890a49f8d87a
    		04/15/2025 7:20 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
    com.nvidia.build.id=159049543
    		04/15/2025 7:20 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
    NVIDIA_BUILD_ID=159049543
    		04/15/2025 7:20 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    NVIDIA_BUILD_ID=159049543
    		04/15/2025 7:20 PM UTC
    sha256:3376805493cd509d0df56085f02aad7905f80c380cb316c5ddd13f847e241a17COPY
    entrypoint.d/ /opt/nvidia/entrypoint.d/
    		04/15/2025 7:20 PM UTC
    sha256:68280ef181425716d886f00a016924556eefdeea7344c1021de8255fde0d9dbeRUN
    NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b 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 ${_CUDA_COMPAT_PATH}/lib
    		04/15/2025 7:20 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
    TORCH_NCCL_USE_COMM_NONBLOCKING=0
    		04/15/2025 7:20 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
    CUDA_MODULE_LOADING=LAZY
    		04/15/2025 7:20 PM UTC
    sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1RUN
    NVIDIA_PYTORCH_VERSION=25.04 PYTORCH_BUILD_VERSION=2.7.0a0+79aa174 NVFUSER_BUILD_VERSION=5111d3b TARGETARCH=arm64 PYVER=3.12 PYVER_MAJMIN=312 L4T=1 DALI_EXTRA_INDEX_URL=http://sqrl/nvdl/datasets/dali/pip-dali if [ "${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
    		04/15/2025 7:20 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.