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OMG! Just yesterday I published my reworked GoNEAT library that implements HyperNEAT combined with phased search and backpropagation [1]. But it's kind of imp

OMG! Just yesterday I published my reworked GoNEAT library that implements HyperNEAT combined with phased search and backpropagation [1]. But it's kind of impossible to enter for me because of the hard pytorch requirements :( would love to see the project as a gym, so that you can run your own ANN design algorithm. I get that most data science students still use python, but the evolutionary world is kinda in C++ and other native languages. Anyways, great project nonetheless. [1] https://github.com/cookiengineer/goneat https://github.com/cookiengineer/goneat

codetiger 14d ago
Where do you see a hard requirement? I have added support for ONNX model upload for now and would love to extend support for other formats. How you build the model is totally upto you. I don’t check anything other than format and inference time and model size.
codetiger 14d ago
Saw your repo and understood you question better. The requirement are now limiting Neural Networks only, not a direct algorithm implementation