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How to train with a specific set of features/games #82
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Hi Yamil, I have some examples in another repository that might help you. https://github.com/macfergus/badukai Here are some key files: The differences from the processor in the book are:
I wrote the badukai code after finishing the book, so it uses similar conventions to the book, but not identical. I hope this makes it easier to follow rather than harder 😅. Let me know if this helps! |
This is great! Thank you |
Hi all!!
As I experiment with different hyperparameters, I would like to be able to train different networks with exactly the same feature-labels, so that any different in performance would be due to the hyperparameters and not the data itself.
Similarly, I have my own collection of historical go games, and would like to be able to train networks with those games instead of the KGS games.
As I'm relatively new to Python, the task of modifying the existing code (
parallel_processor.py, generator.py, etc
) is quite daunting. So before I give it a try myself I rather ask. Has anyone implemented something in this line, and would be willing to share it?Thanks a lot
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