Comments (2)
Thanks for reaching out! I haven't done any development for Windows, and I think it's true that there will be some steps that are Linux-centric. That said, I think you might still be able to make some progress if you're already familiar with using Vivado HLS. I think you should be able to convert
and write
a model, creating all the .cpp
and .tcl
files for the HLS project. From there you can create a Vivado HLS project using the HLS software directly, rather than using the compile
and build
methods of the conifer model. Do you think that can work for you?
I'm also open to adding support for Windows to conifer, we recently made some modifications to support emulation on OSX for example.
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It's not a big deal for me, I also have a Linux which I can use. I just wanted to be sure.
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Related Issues (20)
- scikit-learn AdaBoostClassifier
- xgboost precision HOT 2
- xgboost example VivadoHLS segfault HOT 5
- Long synthesis time on Vitis HOT 2
- ONNX Conversion Fails with ONNX model produced from xgboost
- XGBoost feature error HOT 4
- `ImportError: cannot import name 'backends'` when importing conifer HOT 2
- 'XGBClassifer' object has no attribute 'save config' HOT 5
- Bitstream generation feature HOT 3
- Type error 'module' object is not callable HOT 2
- VHDL Backend : Missing assignement in AddReduce.vhd ? HOT 7
- Exception: Couldn't find Xilinx ap_ headers HOT 8
- XGBoost 2.0.0 HOT 2
- README links broken HOT 1
- RF results HOT 2
- Expression balancing HOT 6
- Vivado HLS build broken
- Random Forest - Only one branch generated in Vivado HLS HOT 1
- Possibly undefined bridge in HLS and CPP backends
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