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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.

NVIDIA AI Enterprise Supported
LayerLabelCreated
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
com.nvidia.build.ref=25072f77d16075934e5548f85208971a3b7ce708
10/21/2020 10:42 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
NVIDIA_BUILD_REF
10/21/2020 10:42 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
com.nvidia.build.id=16972326
10/21/2020 10:42 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
NVIDIA_BUILD_ID=16972326
10/21/2020 10:42 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
NVIDIA_BUILD_ID
10/21/2020 10:42 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
PATH=/opt/conda/bin:/opt/cmake-3.14.6-Linux-x86_64/bin/:/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin:/opt/tensorrt/bin
10/21/2020 10:42 PM UTC
sha256:b3f0de31ee0f985cdd7339f2a9cbaed9980d6e0d75f7be213ad065c611361c11RUN
NVIDIA_PYTORCH_VERSION=20.10 PYTORCH_BUILD_VERSION=1.7.0a0+7036e91 PYVER=3.6 BASE=0 DEVEL=0 SAMPLES=0 PYTHON=1 /nvidia/build-scripts/installTRT.sh &&
  mv /usr/src/tensorrt /opt &&
  ln -s /opt/tensorrt /usr/src/tensorrt
10/21/2020 10:42 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENTRYPOINT
/usr/local/bin/nvidia_entrypoint.sh
10/21/2020 10:42 PM UTC
sha256:7542506f8d1bbdd4841a1d0d2d10e410e44c0b21f4aa0c4295be4812370a7e5aCOPY
nvidia_entrypoint.sh /usr/local/bin
10/21/2020 10:42 PM UTC
sha256:9299d68426e138461154dd2e810b107027ab897d53d5ef8415e753f25fbde64dRUN
NVIDIA_PYTORCH_VERSION=20.10 PYTORCH_BUILD_VERSION=1.7.0a0+7036e91 PYVER=3.6 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
10/21/2020 10:42 PM UTC
...

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