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CONTRIBUTING.md

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Contributing to unda

Thanks for taking the time to contribute! 🎉👍

As a singular college student working on this crate for fun to better understand rust and machine learning it really does mean a lot :)

Development

Running code locally

To begin, please follow the same instructions listed in the README to ensure XLA is properly installed and sourced on your machine.

  1. Identify the latest compatible versions of CUDA and cuDNN. Adapt these instructions to install the two version of CUDA and cuDNN together.

  2. Install clang and libclang1.

  3. Download and extract xla_extension.

  4. Make sure LD_LIBRARY_PATH includes /path/to/xla_extension/lib, and make sure the relevant CUDA paths are also visible to the system.

Assuming you downloaded unda to /home/user/unda and you want to run the crate locally, it's relatively self explanatory as you would run any rust project:

cd /home/user/unda
cargo build --release
./target/release/unda

or run any of the example programs with

cd /home/user/unda
cargo run --release --example {example_name}

Once changes are made, please make a new branch and submit a PR :)

Running tests

Nothing special, just cargo test.