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PyTorch
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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=36e6c838d631e94a47406a4e952221247afcabc0
    12/05/2024 11:07 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    NVIDIA_BUILD_REF=36e6c838d631e94a47406a4e952221247afcabc0
    12/05/2024 11:07 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
    com.nvidia.build.id=126674149
    12/05/2024 11:07 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
    NVIDIA_BUILD_ID=126674149
    12/05/2024 11:07 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    NVIDIA_BUILD_ID=126674149
    12/05/2024 11:07 PM UTC
    sha256:2354e6c00efee30bf5189a140dfd52d68ccf3b383b16a8a9020e474d3854a06aCOPY
    entrypoint.d/ /opt/nvidia/entrypoint.d/
    12/05/2024 11:07 PM UTC
    sha256:5adbc2a743d644e7c3ea8e62835fc82f19b4d684f4d49b083a9c65ae0fde399eRUN
    NVIDIA_PYTORCH_VERSION=24.12 PYTORCH_BUILD_VERSION=2.6.0a0+df5bbc0 NVFUSER_BUILD_VERSION=0d33366 TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 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 ${_CUDA_COMPAT_PATH}/lib
    12/05/2024 11:07 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
    CUDA_MODULE_LOADING=LAZY
    12/05/2024 11:07 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
    TORCH_CUDNN_V8_API_ENABLED=1
    12/05/2024 11:07 PM UTC
    sha256:07e03c2f107504c4802a890d7c0dae0d4a5a9f63d42cd8dd58eddc03b7e27f10RUN
    NVIDIA_PYTORCH_VERSION=24.12 PYTORCH_BUILD_VERSION=2.6.0a0+df5bbc0 NVFUSER_BUILD_VERSION=0d33366 TARGETARCH=amd64 PYVER=3.12 PYVER_MAJMIN=312 L4T=0 if [ "${L4T}" = "1" ]; then echo "Not installing Transformer Engine in iGPU container until Version variable is set"; else NVTE_BUILD_THREADS_PER_JOB=8 pip install --no-cache-dir --no-build-isolation git+https://github.com/NVIDIA/TransformerEngine.git@release_v${TRANSFORMER_ENGINE_VERSION}; fi
    12/05/2024 11:07 PM UTC
    ...

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