Accessing scikit-learn 0.21.3-fosscuda-2019b-Python-3.7.4
To load the module for scikit-learn 0.21.3-fosscuda-2019b-Python-3.7.4 please use this command on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs):
module load scikit-learn/0.21.3-fosscuda-2019b-Python-3.7.4
BEAR Apps Version
EL8-haswell (GPUs: NVIDIA P100)
The listed architectures consist of two part: OS-CPU.
- BlueBEAR: The OS used on BlueBEAR 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.
- BEAR and CaStLeS Cloud VMs: These VMs can have one of two OSes. Those with access to a BEAR Cloud or CaStLeS VM should check that the listed architectures for an application include the OS of VM being used. The VMs, irrespective of OS, will use the haswell CPU type.
For more information visit the scikit-learn website.
This version of scikit-learn is a direct dependent of: keras-tuner/1.0.2-fosscuda-2019b-Python-3.7.4 PyTorch-Geometric/1.4.3-fosscuda-2019b-Python-3.7.4-PyTorch-1.4.0
Last modified on 13th May 2020