ocf-datapipes 0.5.1

Pytorch Datapipes built for use in Open Climate Fix's nowcasting/forecasting work

ocf_datapipes

OCF's DataPipe based dataloader for training and inference

Usage

Adding a new DataPipe

A general outline for a new DataPipe should go something like this:

from torchdata.datapipes.iter import IterDataPipe
from torchdata.datapipes import functional_datapipe

@functional_datapipe("<pipelet_name>")
class <PipeletName>IterDataPipe(IterDataPipe):
    def __init__(self):
        pass

    def __iter__(self):
        pass

Experimental DataPipes

For new datapipes being developed for new models or input modalities, to somewhat separate the more experimental and in development datapipes from the ones better tested for production purposes, there is an ocf_datapipes.experimental namespace for developing these more research-y datapipes. These datapipes might not, and probably are not, tested. Once the model(s) using them are in production, they should be upgraded to one of the other namespaces and have tests added.

Citation

If you find this code useful, please cite the following:

@misc{ocf_datapipes,
  author = {Bieker, Jacob, and Dudfield, Peter, and Kelly, Jack},
  title = {OCF Datapipes},
  year = {2022},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/openclimatefix/ocf_datapipes}},
}