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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=2f15053fc9da046228c5e45db0b145a68033ddf3
02/21/2020 1:12 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
NVIDIA_BUILD_REF
02/21/2020 1:12 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4LABEL
com.nvidia.build.id=10315040
02/21/2020 1:12 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
NVIDIA_BUILD_ID=10315040
02/21/2020 1:12 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
NVIDIA_BUILD_ID
02/21/2020 1:12 AM 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:/opt/tensorrt/bin
02/21/2020 1:12 AM UTC
sha256:28c44c82ed9aed25f4c8465aba376ecfff58c3dcdbaab848f35684bd473c70e9RUN
NVIDIA_PYTORCH_VERSION=20.02 PYTORCH_BUILD_VERSION=1.5.0a0+3bbb36e 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
02/21/2020 1:12 AM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENTRYPOINT
/usr/local/bin/nvidia_entrypoint.sh
02/21/2020 1:12 AM UTC
sha256:9c7bab99491ca679e0f00d40c1342134efb25918191518f44f7e254825f08753COPY
nvidia_entrypoint.sh /usr/local/bin
02/21/2020 1:12 AM UTC
sha256:299f3d8fedc3f7e8a4c5c3d4ff35642320eae3d281ee494b9109fe97979f6e66RUN
NVIDIA_PYTORCH_VERSION=20.02 PYTORCH_BUILD_VERSION=1.5.0a0+3bbb36e 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
02/21/2020 1:12 AM UTC
...

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