From a868fe162d7e37ba60fd4516783fb6f929ef1752 Mon Sep 17 00:00:00 2001 From: rn5f107s2 Date: Thu, 12 Sep 2024 17:16:50 +0200 Subject: [PATCH] bench 10561225 --- Makefile | 2 +- src/Nets/params.bin | Bin 0 -> 803908 bytes src/nnue.cpp | 28 ++++++++++++++++++++-------- src/nnue.h | 26 +++++++++++++++++--------- 4 files changed, 38 insertions(+), 18 deletions(-) create mode 100644 src/Nets/params.bin diff --git a/Makefile b/Makefile index 27f359e..58f6901 100644 --- a/Makefile +++ b/Makefile @@ -3,7 +3,7 @@ OBJ_DIR=build MOLY_DIR=src CXX=clang++ -DEFAULT_NET_NAME=moly_20240526.nnue +DEFAULT_NET_NAME=params.bin DEFAULT_EXE = $(OBJ_DIR)/Molybdenum DATAGEN_EXE = $(OBJ_DIR)/Datagen diff --git a/src/Nets/params.bin b/src/Nets/params.bin new file mode 100644 index 0000000000000000000000000000000000000000..264600f81e63ff4bca956414f0e977e7d19046e1 GIT binary patch literal 803908 zcmWKX`9n@k9L3v9w5J6vqEbRaJ$LS%Cn7tgELkJFdX*)V(xy#|il~T6N&8;UojY?M 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z>dpH=n0%atqD%YmW|JR$URa183~>DW)y(@%TLembr+~k|obcZGQjGIY0w>c$cu&oi z%bquvY4kNkH<_K{zsrXU6ZOi`FR}=H&)Q?%4}CmqRKg$m+sLloYCv8o(gnetworkData); void Net::loadDefaultNet() { - weights0 = defaultWeights.weights0; + for (size_t i = 0; i < defaultWeights.weights0.size(); i++) + weights0[i] = int16_t(defaultWeights.weights0[i] * 255); + + for (size_t i = 0; i < defaultWeights.bias0.size(); i++) + bias0[i] = int16_t(defaultWeights.bias0[i] * 255); + weights1 = defaultWeights.weights1; - bias0 = defaultWeights.bias0; - bias1 = defaultWeights.bias1; + bias1 = defaultWeights.bias1; + weights2 = defaultWeights.weights2; + bias2 = defaultWeights.bias2; } void Net::initAccumulator(std::array &bitboards) { @@ -52,12 +58,18 @@ void Net::initAccumulator(std::array &bitboards) { } int Net::calculate(Color c) { - int output = 0; + float out = bias2[0]; + std::array output = bias1; - for (int n = 0; n != L1_SIZE; n++) { - output += screlu(accumulator[ c][n]) * weights1[n ]; - output += screlu(accumulator[!c][n]) * weights1[n + L1_SIZE]; + for (int n = 0; n < L1_SIZE; n++) { + for (int m = 0; m < L2_SIZE; m++) { + output[m] += screlu(float(accumulator[ c][n]) / 255.0f) * weights1[n * L2_SIZE + m ]; + output[m] += screlu(float(accumulator[!c][n]) / 255.0f) * weights1[n * L2_SIZE + m + L1_SIZE * L2_SIZE]; + } } - return ((output / 255) + bias1[0]) * 133 / (64 * 255); + for (int n = 0; n < L2_SIZE; n++) + out += screlu(output[n]) * weights2[n]; + + return int(out * 133.0f); } diff --git a/src/nnue.h b/src/nnue.h index 37b717d..62c07e7 100644 --- a/src/nnue.h +++ b/src/nnue.h @@ -14,23 +14,26 @@ enum Toggle { static const int INPUT_SIZE = 12 * 64; static const int L1_SIZE = 256; -static const int OUTPUT_SIZE = 1; -static const int NET_SIZE = 3; -static const std::array LAYER_SIZE = {INPUT_SIZE, L1_SIZE, OUTPUT_SIZE}; +static const int L2_SIZE = 8; +static const int OUT_SIZE = 1; struct Weights { - std::array weights0{}; - std::array bias0{}; - std::array weights1{}; - std::array bias1{}; + std::array weights0{}; + std::array bias0{}; + std::array weights1{}; + std::array bias1{}; + std::array weights2{}; + std::array bias2{}; }; class Net { public: std::array weights0{}; std::array bias0{}; - std::array weights1{}; - std::array bias1{}; + std::array weights1{}; + std::array bias1{}; + std::array weights2{}; + std::array bias2{}; std::array, 2> accumulator{}; Stack, 2>, MAXDEPTH> accumulatorStack; @@ -50,6 +53,11 @@ inline int screlu(int16_t input) { return clamped * clamped; } +inline float screlu(float input) { + float clamped = std::clamp(input, 0.0f, 1.0f); + return clamped * clamped; +} + template inline int index(int pc, int sq) { int square = C ? sq : sq ^ 56;