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fastmachinelearning/hls4ml: coris

vloncar; Sioni Summers; Javier Duarte; Nhan Tran; Ben Kreis; jngadiub; Nicolò Ghielmetti; Duc Hoang; EJ Kreinar; Kelvin Lin; Maksymilian Graczyk; Adrian Alan Pol; ngpaladi; Dejan Golubovic; Yutaro Iiyama; Zhenbin Wu; Delon; Paolo Cretaro; veyron8800; Anders Wind; David; GDG; Jovan Mitrevski; Konstantin Vinogradov; Konstantin Vinogradov; Petr Zejdl; Sarun Nuntaviriyakul; Thea Aarrestad; drankincms

What's Changed

  • VivadoAccelerator backend: target pynq-z2 and zcu102 boards directly from hls4ml by @nicologhielmetti
  • Updated PyTorch and ONNX converters by @Duchstf
  • line_buffer Conv2D implementation for io_stream: reduced resource usage and latency by @Keb-L, @violatingcp, @vloncar
  • Support QConv2DBatchnorm layer from QKeras by @nicologhielmetti
  • Improved profiling plots - easier to compare original vs hls4ml converted models by @maksgraczyk
  • Better derivation of data types for QKeras models by @jmduarte, @thesps
  • Improved CI by @thesps
  • More support for models with branches, skip connections, Merge and Concatenate layers by @jmduarte, @vloncar
  • Support for Dense layers over multi-dimensional tensors by @vloncar
  • Overall improvements by @vloncar, @jmduarte, @thesps, @jmitrevs & others

New Contributors

Full Changelog: https://github.com/fastmachinelearning/hls4ml/compare/v0.5.0...v0.6.0

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