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Or you can just use an immediately invoked lambda expression

Using compiler explorer (I don't have latest MSVC installed), it seems MSVC add a test for popcount, and other <bit> functions. int bitcount(uint64_t b) { return std::popcount<uint64_t>(b); } Small nitpick: it's almost never necessary to help the compiler by providing explicit template arguments. Y...

NNUE architecture learns king safety and attack very quickly but something simple as piece values maybe hard without factorizer, or having it as input directly. NNUE is just a tiny net, no magic in it. I feel like a 2x32 conv net I have can compete with it but I need to write a fast inference code ...

Isn't it more economical to handle perpetual checks as a post-processing step after the regular EGT generation instead of after every iteration? Here's what I do with the public information subset of Stratego endgames (not yet published) where perpetual chasing is forbidden. First, generate an EGT i...

I suppose the actual wording should read something like: If a move is played that repeats the position for the third time, either player may call it a repetition, with the repeating side getting 1/4 point, the other side 3/4 point. For engine vs. engine play I suppose it would be automatically scor...

For training I use C++ with libTorch. I've been experimenting with PyTorch, the data-loader from PyTorch is so slow that it is unusable. Writing a data-loader in Python is not done either, I've never seen a language as slow as PyThon, It makes me wonder why most data-scientists insist on using this...

Interesting read! Do you use any random exploration during the training games? (like AlphaZero did in the opening). Oh, and did I read that correctly that you have extended cutechess-cli to also work with 8x8 checkers and Othello? I once tried that, IIRC, there was some documentation on how you can ...

In a few months, everyone will be looking for ways to goose the nets — through size, architecture, etc. Those that use existing tools like tensorflow and pytorch instead of developing them from scratch will win the race(s). Writing gradient descent optimizers by hand never was a viable long term st...

Nice, I actually saw that post before. Couldn't ask on that forum because my account is still inactivated :P. So in your training data you have only the indexes? Yes, as described in that forum post, each pattern can take on 3**8 values, and each position only has one active pattern instance stored...

I have done something very similar in 10x10 draughts, explained here: http://laatste.info/bb3/viewtopic.php?f=53&t=8327
The key is understanding tf.gather and tf.reduce_sum