.. toctree::
:hidden:
:caption: Introduction
intro/introduction
intro/status
intro/setup
intro/faq
intro/release_notes
intro/reference
.. toctree::
:hidden:
:glob:
:caption: User Guide
api/concepts
api/configuration
api/command
api/serialization
.. toctree::
:hidden:
:glob:
:caption: Frontends
frontend/keras
frontend/pytorch
frontend/qonnx
.. toctree::
:hidden:
:glob:
:caption: Backends
backend/vitis
backend/accelerator
backend/oneapi
backend/catapult
backend/quartus
backend/sr
backend/xls
.. toctree::
:hidden:
:caption: Advanced Features
advanced/profiling
advanced/auto
advanced/hgq
advanced/da
advanced/precision
advanced/fifo_depth
advanced/extension
advanced/snn
advanced/model_optimization
advanced/bramfactor
advanced/plugins
.. toctree::
:hidden:
:glob:
:caption: Internals
ir/ir
ir/modelgraph
ir/multimodelgraph
ir/flows
ir/attributes
.. toctree::
:hidden:
:glob:
:caption: Autogenerated API Reference
autodoc/hls4ml.backends
autodoc/hls4ml.converters
autodoc/hls4ml.model
autodoc/hls4ml.optimization
autodoc/hls4ml.report
autodoc/hls4ml.utils
autodoc/hls4ml.writer
hls4ml is a Python package for machine learning inference in FPGAs. We create firmware implementations of machine learning algorithms using high level synthesis language (HLS). We translate traditional open-source machine learning package models into HLS that can be configured for your use-case!
The project is currently in development, so please let us know if you are interested, your experiences with the package, and if you would like new features to be added. You can reach us through our GitHub page.
For the latest status including current and planned features, see the :ref:`Status and Features` page.
Detailed tutorials on how to use hls4ml's various functionalities can be found here.