setHardware: A hardware setter to run the model
In ff98li/scRGNet: Perform scRNA-seq Analysis using Single-cell Graphical Neural Network (scGNN) Framework

Setting up your hardware to train the model faster and get a better result (if you have a powerful one)

1	setHardware(coresUsage = 1L, CUDA = FALSE)

`coresUsage`	The number of CPU cores you would like to use to train the model. For Mac user, please do not change the default value of 1. This is a special case for Mac OS (sorry)
`CUDA`	Whther to use Nvidia GPU to train the model via CUDA. Make sure you have CUDA 10.0 or 11.1 version installed. Higher version of CUDA is currently not supported by torch. If CUDA is set to TRUE, coresUsage will not be used. Default FALSE.

A list of parameters to set up hardware

\insertRef

scGNNscRGNet

ff98li/scRGNet documentation built on Jan. 14, 2022, 4:58 a.m.

ff98li/scRGNet index

README.md

Note that we can't provide technical support on individual packages. You should contact the package authors for that.

Description