CEA-LIST/RPCDataloader

A variant of the PyTorch Dataloader using remote workers.

35
/ 100
Emerging

When training machine learning models, you often need to load large amounts of data from disk. This tool helps machine learning engineers or researchers who are using PyTorch to load data more efficiently by distributing the data loading process across multiple remote computers. It takes your dataset's location and desired transformations, and outputs ready-to-use batches of data for your model training.

No commits in the last 6 months. Available on PyPI.

Use this if you are a machine learning engineer or researcher training PyTorch models and are bottlenecked by data loading from a single machine, or if you want to utilize data stored on multiple remote servers without copying it.

Not ideal if your dataset is small enough to fit on a single machine and data loading is not a performance bottleneck, or if you are not using PyTorch for your machine learning workflows.

machine-learning-engineering deep-learning-training distributed-computing data-pipeline-optimization
Stale 6m
Maintenance 0 / 25
Adoption 6 / 25
Maturity 25 / 25
Community 4 / 25

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Stars

21

Forks

1

Language

Python

License

Last pushed

Apr 01, 2023

Commits (30d)

0

Dependencies

5

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