Status and Features

Status

The latest stable release is v0.5.0. This release brings the new IOType: io_stream and support for larger CNN models, see: <https://arxiv.org/abs/2101.05108>.

Features

A list of suppported ML codes and architectures, including a summary table is below. Dependences are given in the Setup page.

ML code support:

  • Keras/Tensorflow/QKeras, PyTorch, Onnx

Neural network architectures:

  • Fully Connected NNs (multi-layer perceptron)

  • Convolutional NNs (1D/2D)

  • Recurrent NN/LSTM, in prototyping

A summary of the on-going status of the hls4ml tool is in the table below.

Architectures/Toolkits

Keras/TensorFlow/QKeras

PyTorch

ONNX

MLP

supported

supported

supported

Conv1D/Conv2D

supported

in development

in development

RNN/LSTM

in development

in development

in development

Other feature notes:

  • hls4ml is tested on Linux, and supports Vivado HLS versions 2018.2 to 2020.1. Vitis HLS is not yet supported. Windows and macOS are not supported.

  • BDT support has moved to the Conifer package

Example Models

We also provide and documented several example models that have been implemented in hls4ml in this Github repository.