PyTorch 1.6.0-foss-2019b-Python-3.7.4

There is a newer version of PyTorch

PyTorch provides tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system.

Accessing PyTorch 1.6.0-foss-2019b-Python-3.7.4

To load the module for PyTorch 1.6.0-foss-2019b-Python-3.7.4 please use this command on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs):

module load PyTorch/1.6.0-foss-2019b-Python-3.7.4

BEAR Apps Version

2019b

Architectures

EL8-cascadelake

The listed architectures consist of two part: OS-CPU. The OS used is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.

More Information

For more information visit the PyTorch website.

Dependencies

This version of PyTorch has a direct dependency on: FFmpeg/4.2.1-GCCcore-8.3.0 foss/2019b gflags/2.2.2-GCCcore-8.3.0 glog/0.4.0-GCCcore-8.3.0 GMP/6.1.2-GCCcore-8.3.0 MPFR/4.0.2-GCCcore-8.3.0 Ninja/1.9.0-GCCcore-8.3.0 numactl/2.0.12-GCCcore-8.3.0 Pillow/6.2.1-GCCcore-8.3.0 protobuf/3.10.0-GCCcore-8.3.0 pybind11/2.4.3-GCCcore-8.3.0-Python-3.7.4 Python/3.7.4-GCCcore-8.3.0 PyYAML/5.1.2-GCCcore-8.3.0 SciPy-bundle/2019.10-foss-2019b-Python-3.7.4

Required By

This version of PyTorch is a direct dependent of: Pyro/1.5.0-foss-2019b-Python-3.7.4

Other Versions

These versions of PyTorch are available on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.

Last modified on 6th September 2020