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# TorchArrow: a data processing library for PyTorch
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**This library is currently in the Beta stage and does not have a stable release. The API and implementation may change based on
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user feedback or performance. Future changes may not be backward compatible.
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If you have suggestions on the API or use cases you'd like to be covered, please open a
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GitHub issue. We'd love to hear thoughts and feedback.**
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**This library currently does not have a stable release. The API and implementation may change.
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Future changes may not be backward compatible.**
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TorchArrow is a [torch](https://github.com/pytorch/pytorch).Tensor-like Python DataFrame library for data preprocessing in PyTorch models, with two high-level features:
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python setup.py install
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```
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## Documentation
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You can find the API documentation [here](https://pytorch.org/torcharrow/).
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This [10 minutes tutorial](https://github.com/pytorch/torcharrow/blob/main/tutorial/tutorial.ipynb) provides a short introduction to TorchArrow, and you can also try it in [this Colab](https://colab.research.google.com/drive/1mQ3S6dwmU-zhBe2Tdvq_VRAnjQ3paiay).
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## Examples
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You can find the example about integrating a TorchRec based training loop utilizing TorchArrow's on-the-fly preprocessing
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[here](https://github.com/pytorch/torchrec/tree/main/examples/torcharrow). More examples are coming soon!
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## Contributing
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We welcome PRs! See the [CONTRIBUTING](CONTRIBUTING.md) file.
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## Beta Usage and Feedback
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We'd love to hear from and work with early adopters to shape our design. Please reach out by raising an issue if you're
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interested in using this library for your project.
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## Future Plans
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We hope to continue to expand the library, harden API, and gather feedback to enable future releases. Stay tuned!
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## License
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TorchArrow is BSD licensed, as found in the [LICENSE](LICENSE) file.

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