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The tensorflow-haskell package provides Haskell-language bindings for TensorFlow, giving Haskell developers the ability to build and run computation graphs, machine learning models, and leverage TensorFlow's ecosystem—though it is not an official Google release. As an expedient we use docker for building. Once you have docker working, the following commands will compile and run the tests. Run the install_macos_dependencies.sh script in the tools/ directory. The script installs dependencies via Homebrew and then downloads and installs the TensorFlow library on your machine under /usr/local. The stack.yaml file describes a NixOS environment containing the necessary dependencies.
Features
- Exposes TensorFlow Core and computational graph APIs to Haskell
- Enables building complex models and graph-based computations
- Compatibility with additional binding packages like tensorflow-ops
- Haskell interface integrates into the broader TensorFlow ecosystem
- Useful for prototyping ML tasks in a statically typed environment
- Serves as a foundation for further ML workflows in Haskell
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DesignLicense
Apache License V2.0Follow TensorFlow Haskell
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