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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
e0ae64dfa453cd1f8e9d1b718e7090435c68639719955d874002f01f7cc10fd1CONFIG
Entrypoint /usr/local/bin/nvidia_entrypoint.sh; WorkingDir /workspace; ExposedPorts 6006/tcp, 8888/tcp
10/21/2020 10:42 PM UTC
b77c28d8842d18a89bef5164d360270476752c3757fe44709cc0538482e43da1ARG
NVIDIA_BUILD_REF
10/21/2020 10:42 PM UTC
d06b74ecfabe579458f6d02db09f384dad811997572db4e837a27d57364d86edLABEL
com.nvidia.build.id=16972326
10/21/2020 10:42 PM UTC
012bbd79e70e64db433b09c6e3fe5b569f73e78175ac63cc8423447910ac408aENV
NVIDIA_BUILD_ID=16972326
10/21/2020 10:42 PM UTC
58fff8e657a399a1f15e19564aca51ecacc6fab9b4cbce11f4fd1c3b43e35b35ARG
NVIDIA_BUILD_ID
10/21/2020 10:42 PM UTC
d536776ca50958578bc54408897aef900f1ca6a4b5adcfaf211803161a174651ENV
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
a10b7e1987acc315e4a6fbafda0fd71b76559b83e5ba3fb8a033a8adc92761eeRUN
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
acb91564d75b5ada32d6500ac231acbc2471bb697e57899afb476a5b94273c81ENTRYPOINT
/usr/local/bin/nvidia_entrypoint.sh
10/21/2020 10:42 PM UTC
6bbf2d533bb5ea307c3ec4d29eed926325546d90820016fdf6e7c722bc7c2f26COPY
nvidia_entrypoint.sh /usr/local/bin
10/21/2020 10:42 PM UTC
7c216b2f7e636b2326ee631c54315fe8ee2441fe388321be93a5c4e8fced4a88RUN
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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