Sioni Summers

The `RandomForestClassifier` in scikit-learn is similar to the `GradientBoostingClassifier` in that an ensemble of Decision Trees is used. For binary classification tasks, I think conifer already works for `RandomForestClassifier`s. However,...

The HLS backend gives wrong results on an example regression task, for unknown reason. Running the `sklearn_regression.py` example with `conifer.backends.vivadohls` gives wrong results. VHDL backend gives correct results. ``` y_skl[:10]...

XGBoost 2.0.0

3

The XGBoost converter is not working for XGBoost 2.0.0. This issue is for tracking the development of the fix.

- helpful if running parallel builds

PR #53 probably broke synthesis for Vivado HLS (while it works with more recent Vitis HLS). In the HLS build log: ``` ERROR: [HLS 200-101] 'open_solution': Unknown option '-flow_target'. ```...

In the `decision_function` methods of HLS and C++ backends, the attribute `self.bridge` of the model is accessed to make the predictions. If `compile` hasn't already been called then this attribute...

I've refreshed the conifer notebook with the latest release to synchronise with the move to Vitis HLS.

Add a namespace to the NNPuppiTau model

2

#### PR description: We have had a recurring issue with hls4ml emulator models that are defined as externals that they sometimes clobber each other's symbols (arrays for weights typically) [[1](https://github.com/cms-sw/cmssw/issues/44435),...

Reimplement Alveo runtime with `pyxrt`

1

The Alveo runtime is using `pynq`, which is deprecating Alveo as of its `v3.1`. It would be good to implement the Alveo runtime with XRT's Python bindings `pyxrt` instead.

Some of the tests in `[test_backends.py](https://github.com/thesps/conifer/blob/master/tests/test_backends.py)` currently fail on the main branch due to numerical mismatches in the predictions between different backends.