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NVIDIA
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
43b74e36f97d1ef8edb598d89d12a492079eded3f33ba663e86764344687d5c8CONFIG
Entrypoint /usr/local/bin/nvidia_entrypoint.sh; WorkingDir /workspace; ExposedPorts 6006/tcp, 8888/tcp
08/19/2020 12:45 AM UTC
4228dcce0d0ba2600cfe3267a1aa0d8f3347ae4bf5f6544f67793d1e33ece97eARG
NVIDIA_BUILD_REF
08/19/2020 12:45 AM UTC
8a5f9fcede42607c4b187a65fd0893d5df6a355e9f68b0e6e5b61dbb3b2d0d8dLABEL
com.nvidia.build.id=15516749
08/19/2020 12:45 AM UTC
e01a46357372801647a62e662c4067f1c1e8bfbdaf7762aa5edbf638c126e84aENV
NVIDIA_BUILD_ID=15516749
08/19/2020 12:45 AM UTC
c931897857036ae33a0947727ff2a90b7bfa7ae777eca0378b821ebac27a1f02ARG
NVIDIA_BUILD_ID
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5d07c87efcac0e13f18dfedc52dd7cdd5d47f71c99f31e59c4cc59dd06fa396dENV
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
08/19/2020 12:45 AM UTC
d4150123843a787e1f17fb3dfc0051feb216dd6deace5c0a06120669509d18f0RUN
NVIDIA_PYTORCH_VERSION=20.08 PYTORCH_BUILD_VERSION=1.7.0a0+8deb4fe 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
08/19/2020 12:45 AM UTC
5dabe0ae29aa439b7b9d3978775d00988eae2d55d76f21f232c5706361c783c9ENTRYPOINT
/usr/local/bin/nvidia_entrypoint.sh
08/19/2020 12:45 AM UTC
acc9189c8ee17a6e738c13a6fb4e0f3f11518f0905211281ae437e59d71c1d2eCOPY
nvidia_entrypoint.sh /usr/local/bin
08/19/2020 12:45 AM UTC
543b489111fbe984123090645ceb8931246c95fa2383a53cc81606fccbe1c637RUN
NVIDIA_PYTORCH_VERSION=20.08 PYTORCH_BUILD_VERSION=1.7.0a0+8deb4fe 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
08/19/2020 12:45 AM UTC
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