fastmachinelearning/hls4ml: coris

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

• @siorpaes made their first contribution in https://github.com/fastmachinelearning/hls4ml/pull/424
• @jmitrevs made their first contribution in https://github.com/fastmachinelearning/hls4ml/pull/403
• @anders-wind made their first contribution in https://github.com/fastmachinelearning/hls4ml/pull/302
• @KOVI89alipes made their first contribution in https://github.com/fastmachinelearning/hls4ml/pull/318
• @maksgraczyk made their first contribution in https://github.com/fastmachinelearning/hls4ml/pull/323
• @Keb-L made their first contribution in https://github.com/fastmachinelearning/hls4ml/pull/332
• @ConsVin made their first contribution in https://github.com/fastmachinelearning/hls4ml/pull/307
• @nicologhielmetti made their first contribution in https://github.com/fastmachinelearning/hls4ml/pull/298

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