README.md

dataloader-demo

This repository demonstrates how you can build a performant cloud-native Pytorch dataloader using Zarr, Dask, Xarray, and Xbatcher.

Demo

The demo can be run by executing the following command line script:

# cli help
python main.py --help

# example 1
python main.py \
    --batch-size 4 \
    --num-epochs 3 \
    --num-batches 500 \
    --shuffle \
    --source arraylake > logs-blog/fig2-log.txt

# example 2
python main.py \
    --batch-size 4 \
    --num-epochs 3 \
    --num-batches 500 \
    --num-workers 32 \
    --persistent-workers \
    --dask-threads 4 \
    --shuffle \
    --prefetch-factor 3 \
    --source arraylake > logs-blog/fig3-log.txt

The output of this script is a log file (logs-blog/fig3-log.txt) that can be visualized using the Jupyter Notebook (plot.ipynb).

History

This work is started as a collaboration between Earthmover and Zeus AI. It leverages a number of open source projects, including Zarr, Dask, Xarray, and Xbatcher -- all of which have been supported by a number of grants from NSF, NASA, and CZI.

As of February 2024, some of the improvements discovered in this project are being upstreamed into Xbatcher.

License

MIT