pytorch-lightning 1.5.7-foss-2021aThe lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
Accessing pytorch-lightning 1.5.7-foss-2021a
To load the module for pytorch-lightning 1.5.7-foss-2021a please use this command on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs):
module load pytorch-lightning/1.5.7-foss-2021a
There is a GPU enabled version of this module: pytorch-lightning 1.5.7-foss-2021a-CUDA-11.3.1
BEAR Apps Version
EL8-cascadelake — EL8-haswell — EL8-icelake
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.
- fsspec 2021.7.0
- pyDeprecate 0.3.1
- torchmetrics 0.6.2
For more information visit the pytorch-lightning website.
This version of pytorch-lightning has a direct dependency on: foss/2021a Python/3.9.5-GCCcore-10.3.0 PyTorch/1.9.1-foss-2021a-imkl TensorFlow/2.6.0-foss-2021a torchvision/0.11.1-foss-2021a tqdm/4.61.2-GCCcore-10.3.0
This version of pytorch-lightning is a direct dependent of: Kornia/0.6.3-foss-2021a
These versions of pytorch-lightning are available on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.
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Last modified on 25th February 2022