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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
6e9b2b4df1fbabd2456c6a73a4379b7c7b5c9a68a2a4e28e59e1bf5c337696bdCONFIG
Entrypoint /usr/local/bin/nvidia_entrypoint.sh; WorkingDir /workspace; ExposedPorts 6006/tcp, 8888/tcp
02/21/2020 1:12 AM UTC
570bdc61ea7e12c98e5d6fab6cfba80e34418f27cf8fde07eb2d8b61094be428ARG
NVIDIA_BUILD_REF
02/21/2020 1:12 AM UTC
1bfc3b3aa830f09d0410aea66d740722688104bf3fc430c05d91a6ac68f35518LABEL
com.nvidia.build.id=10315040
02/21/2020 1:12 AM UTC
e6885e8cb5386b938e7156288e2342ee13647a60de4870c5350b50765b65ee2bENV
NVIDIA_BUILD_ID=10315040
02/21/2020 1:12 AM UTC
c608ea0b7813ea0d31dd7786f6b083ed8799da8a0ced930b135026dc523c1cb7ARG
NVIDIA_BUILD_ID
02/21/2020 1:12 AM UTC
933df560e15f6bbc2c7f054ce28dbbad34ec08ea7db673a931f122a5ad9ad766ENV
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
67a701525dc61a1c34edf9a564fc6466188f83ae3f40d8ca04ed386ee8dea664RUN
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
688995008c5aad9024596b572d344f6553a8ad9bd971940ce3da2db37087bb66ENTRYPOINT
/usr/local/bin/nvidia_entrypoint.sh
02/21/2020 1:12 AM UTC
5a64ce7326edc4c9edb89266e563b66717249129741ce1c4dd335ee5cbdc9270COPY
nvidia_entrypoint.sh /usr/local/bin
02/21/2020 1:12 AM UTC
83d294b70662107b01ab575eef60c9b826f610dd75d055a1c27302fc9f4b12b4RUN
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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