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PyTorch is a python package that provides two high-level features:

  • Tensor computation (like Numpy) with strong GPU acceleration
  • Deep Neural Networks built on a tape-based autograd system

Usually one uses PyTorch either as:

  • A replacement for numpy to use the power of GPUs.
  • a deep learning research platform that provides maximum flexibility and speed

CPU vs. GPU-accelerated computations

All currently installed versions of PyTorch support following methods of computations:

  • CPU-only computations
  • GPU-accelerated computations based on CUDA 8.0 and CuDNN 7.0 libraries


Available modulefiles (PyTorch 0.3.0):

  • pytorch-0.3.0_python-3.6.2_cuda-8.0 (January 2018); version 0.3.0.post4 - with Python 3.6.2, CUDA 8.0 and CuDNN 7.0
  • pytorch-0.3.0_python-2.7.6_cuda-8.0 (January 2018); version 0.3.0.post4 - with Python 2.7.6, CUDA 8.0 and CuDNN 7.0

Available modulefiles (PyTorch 1.1.0):


(JESSIE)mmares@tarkil:~$ module load pytorch-0.3.0_python-3.6.2_cuda-8.0
(JESSIE)mmares@tarkil:~$ python -c 'import torch; print(torch.__version__);'

(JESSIE)leontovyc_roman@tarkil:~$ module add pytorch-1.1.0_python-3.6.2_cuda-10.1
(JESSIE)leontovyc_roman@tarkil:~$ python -c 'import torch; print(torch.__version__);'


You can find documentation at the official website:

Program administrator

Official website