Skip to content

kaust-vislab/pytorch-tutorials

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

60 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Binder

PyTorch tutorials

Collection of Jupyter notebooks demonstrating best-practices for using PyTorch on GPU accelerated hardware.

  • Demonstrate end-to-end GPU accelerated ML workflow using PyTorch to train various DNN achitectures.
  • Demonstrate distributed, GPU accelerated training capable of scaling to clusters of GPUs.

Using Conda

Create the environment...

$ conda env create --prefix ./env --file environment.yml

...then activate the environment...

$ conda activate ./env

...then launch the JupyterLab server.

$ jupyter lab

About

Tutorial materials for GPU accelerated PyTorch

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published