e2508389c2
Introduce documentation for using emlearn (TinyML library) as an external module in Zephyr. Signed-off-by: Benjamin Cabé <benjamin@zephyrproject.org>
53 lines
1.6 KiB
ReStructuredText
53 lines
1.6 KiB
ReStructuredText
.. _external_module_emlearn:
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emlearn
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#######
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Introduction
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************
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`emlearn`_ is an open source library for deploying machine learning models on micro-controllers
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and embedded systems. It provides portable C code generation from models trained with
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scikit-learn or Keras.
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A Python library allows converting complex machine learning models to a minimal C code
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representation, which enables running ML inference on resource-constrained embedded devices.
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emlearn is licensed under the MIT license.
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Usage with Zephyr
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*****************
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The emlearn repository is a Zephyr :ref:`module <modules>` which provides TinyML capabilities to
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Zephyr applications, allowing machine learning models to be run directly on Zephyr-powered devices.
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To pull in emlearn as a Zephyr module, either add it as a West project in the ``west.yaml``
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file or pull it in by adding a submanifest (e.g. ``zephyr/submanifests/emlearn.yaml``) file
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with the following content and run ``west update``:
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.. code-block:: yaml
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manifest:
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projects:
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- name: emlearn
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url: https://github.com/emlearn/emlearn.git
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revision: master
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path: modules/lib/emlearn # adjust the path as needed
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For more detailed instructions and API documentation, refer to the `emlearn documentation`_, and in
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particular the `Getting Started on Zephyr RTOS`_ section.
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References
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**********
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.. target-notes::
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.. _emlearn:
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https://github.com/emlearn/emlearn
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.. _emlearn documentation:
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https://emlearn.readthedocs.io/en/latest/
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.. _Getting Started on Zephyr RTOS:
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https://emlearn.readthedocs.io/en/latest/getting_started_zephyr.html
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