mirror of
https://github.com/HChaZZY/Stockfish.git
synced 2025-12-24 19:16:49 +08:00
remove useless stuff
This commit is contained in:
Tomasz Sobczyk
@@ -49,14 +49,6 @@ SRCS = benchmark.cpp bitbase.cpp bitboard.cpp endgame.cpp evaluate.cpp main.cpp
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search.cpp thread.cpp timeman.cpp tt.cpp uci.cpp ucioption.cpp tune.cpp syzygy/tbprobe.cpp \
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nnue/evaluate_nnue.cpp \
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nnue/features/half_kp.cpp \
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nnue/features/half_ka.cpp \
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nnue/features/half_relative_kp.cpp \
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nnue/features/half_relative_ka.cpp \
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nnue/features/k.cpp \
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nnue/features/p.cpp \
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nnue/features/a.cpp \
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nnue/features/castling_right.cpp \
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nnue/features/enpassant.cpp \
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tools/sfen_packer.cpp \
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tools/gensfen.cpp \
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tools/gensfen_nonpv.cpp \
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@@ -1,54 +0,0 @@
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/*
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Stockfish, a UCI chess playing engine derived from Glaurung 2.1
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Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
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Stockfish is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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Stockfish is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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// Definition of input features and network structure used in NNUE evaluation function
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#ifndef NNUE_HALFKA_256X2_32_32_H_INCLUDED
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#define NNUE_HALFKA_256X2_32_32_H_INCLUDED
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#include "nnue/features/feature_set.h"
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#include "nnue/features/half_ka.h"
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#include "nnue/layers/input_slice.h"
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#include "nnue/layers/affine_transform.h"
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#include "nnue/layers/clipped_relu.h"
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namespace Eval::NNUE {
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// Input features used in evaluation function
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using RawFeatures = Features::FeatureSet<
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Features::HalfKA<Features::Side::kFriend>>;
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// Number of input feature dimensions after conversion
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constexpr IndexType kTransformedFeatureDimensions = 256;
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namespace Layers {
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// Define network structure
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using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
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using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
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using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
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using OutputLayer = AffineTransform<HiddenLayer2, 1>;
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} // namespace Layers
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using Network = Layers::OutputLayer;
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} // namespace Eval::NNUE
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#endif // #ifndef NNUE_HALFA_256X2_32_32_H_INCLUDED
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@@ -1,57 +0,0 @@
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/*
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Stockfish, a UCI chess playing engine derived from Glaurung 2.1
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Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
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Stockfish is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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Stockfish is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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// Definition of input features and network structure used in NNUE evaluation function
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#ifndef NNUE_HALFKP_CR_EP_256X2_32_32_H_INCLUDED
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#define NNUE_HALFKP_CR_EP_256X2_32_32_H_INCLUDED
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#include "nnue/features/feature_set.h"
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#include "nnue/features/half_kp.h"
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#include "nnue/features/castling_right.h"
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#include "nnue/features/enpassant.h"
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#include "nnue/layers/input_slice.h"
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#include "nnue/layers/affine_transform.h"
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#include "nnue/layers/clipped_relu.h"
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namespace Eval::NNUE {
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// Input features used in evaluation function
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using RawFeatures = Features::FeatureSet<
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Features::HalfKP<Features::Side::kFriend>, Features::CastlingRight,
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Features::EnPassant>;
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// Number of input feature dimensions after conversion
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constexpr IndexType kTransformedFeatureDimensions = 256;
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namespace Layers {
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// Define network structure
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using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
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using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
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using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
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using OutputLayer = AffineTransform<HiddenLayer2, 1>;
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} // namespace Layers
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using Network = Layers::OutputLayer;
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} // namespace Eval::NNUE
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#endif // #ifndef NNUE_HALFKP_CR_EP_256X2_32_32_H_INCLUDED
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@@ -1,37 +0,0 @@
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// Definition of input features and network structure used in NNUE evaluation function
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#ifndef NNUE_HALFKP_CR_256X2_32_32_H_INCLUDED
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#define NNUE_HALFKP_CR_256X2_32_32_H_INCLUDED
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#include "nnue/features/feature_set.h"
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#include "nnue/features/half_kp.h"
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#include "nnue/features/castling_right.h"
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#include "nnue/layers/input_slice.h"
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#include "nnue/layers/affine_transform.h"
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#include "nnue/layers/clipped_relu.h"
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namespace Eval::NNUE {
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// Input features used in evaluation function
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using RawFeatures = Features::FeatureSet<
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Features::HalfKP<Features::Side::kFriend>, Features::CastlingRight>;
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// Number of input feature dimensions after conversion
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constexpr IndexType kTransformedFeatureDimensions = 256;
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namespace Layers {
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// Define network structure
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using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
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using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
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using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
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using OutputLayer = AffineTransform<HiddenLayer2, 1>;
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} // namespace Layers
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using Network = Layers::OutputLayer;
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} // namespace Eval::NNUE
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#endif // #ifndef NNUE_HALFKP_CR_256X2_32_32_H_INCLUDED
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@@ -1,35 +0,0 @@
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// Definition of input features and network structure used in NNUE evaluation function
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#ifndef HALFKP_384X2_32_32_H
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#define HALFKP_384X2_32_32_H
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#include "nnue/features/feature_set.h"
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#include "nnue/features/half_kp.h"
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#include "nnue/layers/input_slice.h"
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#include "nnue/layers/affine_transform.h"
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#include "nnue/layers/clipped_relu.h"
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namespace Eval::NNUE {
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// Input features used in evaluation function
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using RawFeatures = Features::FeatureSet<
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Features::HalfKP<Features::Side::kFriend>>;
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// Number of input feature dimensions after conversion
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constexpr IndexType kTransformedFeatureDimensions = 384;
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namespace Layers {
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// define network structure
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using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
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using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
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using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
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using OutputLayer = AffineTransform<HiddenLayer2, 1>;
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} // namespace Layers
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using Network = Layers::OutputLayer;
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} // namespace Eval::NNUE
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#endif // HALFKP_384X2_32_32_H
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@@ -1,54 +0,0 @@
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#include "a.h"
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#include "index_list.h"
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// Definition of input feature A of NNUE evaluation function
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namespace Eval::NNUE::Features {
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// Orient a square according to perspective (rotate the board 180° for black)
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// Important note for "halfka": this arch was designed with "flip" in mind
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// although it still is untested which approach is better.
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// this has to stay until we find a better arch that works with "flip".
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// allows us to use current master net for gensfen (primarily needed for higher quality data)
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inline Square orient(Color perspective, Square s) {
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return Square(int(s) ^ (bool(perspective) * 63));
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}
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// Find the index of the feature quantity from the king position and PieceSquare
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inline IndexType A::make_index(
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Color perspective, Square s, Piece pc) {
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return IndexType(orient(perspective, s) + kpp_board_index[pc][perspective]);
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}
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// Get a list of indices with a value of 1 among the features
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void A::append_active_indices(
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const Position& pos,
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Color perspective,
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IndexList* active) {
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Bitboard bb = pos.pieces();
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while (bb) {
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Square s = pop_lsb(&bb);
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active->push_back(make_index(perspective, s, pos.piece_on(s)));
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}
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}
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// Get a list of indices whose values have changed from the previous one in the feature quantity
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void A::append_changed_indices(
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const Position& pos,
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Color perspective,
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IndexList* removed,
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IndexList* added) {
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const auto& dp = pos.state()->dirtyPiece;
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for (int i = 0; i < dp.dirty_num; ++i) {
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Piece pc = dp.piece[i];
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if (dp.from[i] != SQ_NONE)
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removed->push_back(make_index(perspective, dp.from[i], pc));
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if (dp.to[i] != SQ_NONE)
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added->push_back(make_index(perspective, dp.to[i], pc));
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}
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}
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} // namespace Eval::NNUE::Features
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@@ -1,54 +0,0 @@
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#ifndef _NNUE_FEATURES_A_H_
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#define _NNUE_FEATURES_A_H_
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#include "features_common.h"
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#include "evaluate.h"
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// Definition of input feature A of NNUE evaluation function
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// A is a union of P features and K features, so technically the
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// same effect can be achieved by including both P and K features
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// but it would result in slower index appending because
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// P would conditionally exclude K features and vice versa,
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// where A doesn't have any conditionals.
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namespace Eval::NNUE::Features {
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// Feature P: PieceSquare of pieces other than balls
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class A {
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public:
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// feature quantity name
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static constexpr const char* kName = "A";
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// Hash value embedded in the evaluation function file
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static constexpr std::uint32_t kHashValue = 0x7A4C414Cu;
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// number of feature dimensions
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static constexpr IndexType kDimensions = PS_END2;
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// The maximum value of the number of indexes whose value is 1 at the same time among the feature values
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static constexpr IndexType kMaxActiveDimensions = 32;
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// Timing of full calculation instead of difference calculation
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static constexpr TriggerEvent kRefreshTrigger = TriggerEvent::kNone;
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// Get a list of indices with a value of 1 among the features
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static void append_active_indices(
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const Position& pos,
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Color perspective,
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IndexList* active);
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// Get a list of indices whose values have changed from the previous one in the feature quantity
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static void append_changed_indices(
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const Position& pos,
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Color perspective,
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IndexList* removed,
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IndexList* added);
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private:
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// Index of a feature for a given piece on some square
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static IndexType make_index(Color perspective, Square s, Piece pc);
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};
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} // namespace Eval::NNUE::Features
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#endif // #ifndef _NNUE_FEATURES_UNION_P_K_H_
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@@ -1,65 +0,0 @@
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#include "castling_right.h"
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#include "index_list.h"
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//Definition of input feature quantity CastlingRight of NNUE evaluation function
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namespace Eval::NNUE::Features {
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// Get a list of indices with a value of 1 among the features
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void CastlingRight::append_active_indices(
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const Position& pos,
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Color perspective,
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IndexList* active) {
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// do nothing if array size is small to avoid compiler warning
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if (RawFeatures::kMaxActiveDimensions < kMaxActiveDimensions) return;
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int castling_rights = pos.state()->castlingRights;
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int relative_castling_rights;
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if (perspective == WHITE) {
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relative_castling_rights = castling_rights;
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}
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else {
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// Invert the perspective.
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relative_castling_rights = ((castling_rights & 3) << 2)
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& ((castling_rights >> 2) & 3);
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}
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for (Eval::NNUE::IndexType i = 0; i < kDimensions; ++i) {
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if (relative_castling_rights & (1 << i)) {
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active->push_back(i);
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}
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}
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}
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// Get a list of indices whose values have changed from the previous one in the feature quantity
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void CastlingRight::append_changed_indices(
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const Position& pos,
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Color perspective,
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IndexList* removed,
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IndexList* /* added */) {
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int previous_castling_rights = pos.state()->previous->castlingRights;
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int current_castling_rights = pos.state()->castlingRights;
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int relative_previous_castling_rights;
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int relative_current_castling_rights;
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if (perspective == WHITE) {
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relative_previous_castling_rights = previous_castling_rights;
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relative_current_castling_rights = current_castling_rights;
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}
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else {
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// Invert the perspective.
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relative_previous_castling_rights = ((previous_castling_rights & 3) << 2)
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& ((previous_castling_rights >> 2) & 3);
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relative_current_castling_rights = ((current_castling_rights & 3) << 2)
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& ((current_castling_rights >> 2) & 3);
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}
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for (Eval::NNUE::IndexType i = 0; i < kDimensions; ++i) {
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if ((relative_previous_castling_rights & (1 << i)) &&
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(relative_current_castling_rights & (1 << i)) == 0) {
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removed->push_back(i);
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}
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}
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}
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} // namespace Eval::NNUE::Features
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@@ -1,44 +0,0 @@
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#ifndef _NNUE_FEATURES_CASTLING_RIGHT_H_
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#define _NNUE_FEATURES_CASTLING_RIGHT_H_
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#include "features_common.h"
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#include "evaluate.h"
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//Definition of input feature quantity CastlingRight of NNUE evaluation function
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namespace Eval::NNUE::Features {
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class CastlingRight {
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public:
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// feature quantity name
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static constexpr const char* kName = "CastlingRight";
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// Hash value embedded in the evaluation function file
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static constexpr std::uint32_t kHashValue = 0x913968AAu;
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// number of feature dimensions
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static constexpr IndexType kDimensions = 4;
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// The maximum value of the number of indexes whose value is 1 at the same time among the feature values
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static constexpr IndexType kMaxActiveDimensions = 4;
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|
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// Timing of full calculation instead of difference calculation
|
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static constexpr TriggerEvent kRefreshTrigger = TriggerEvent::kNone;
|
||||
|
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// Get a list of indices with a value of 1 among the features
|
||||
static void append_active_indices(
|
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const Position& pos,
|
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Color perspective,
|
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IndexList* active);
|
||||
|
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// Get a list of indices whose values have changed from the previous one in the feature quantity
|
||||
static void append_changed_indices(
|
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const Position& pos,
|
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Color perspective,
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IndexList* removed,
|
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IndexList* added);
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};
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||||
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} // namespace Eval::NNUE::Features
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#endif
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@@ -1,49 +0,0 @@
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#include "enpassant.h"
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#include "index_list.h"
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//Definition of input feature quantity EnPassant of NNUE evaluation function
|
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namespace Eval::NNUE::Features {
|
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// Get a list of indices with a value of 1 among the features
|
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void EnPassant::append_active_indices(
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const Position& pos,
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||||
Color /* perspective */,
|
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IndexList* active) {
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||||
// do nothing if array size is small to avoid compiler warning
|
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if (RawFeatures::kMaxActiveDimensions < kMaxActiveDimensions)
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return;
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||||
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auto epSquare = pos.state()->epSquare;
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if (epSquare == SQ_NONE)
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return;
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auto file = file_of(epSquare);
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active->push_back(file);
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}
|
||||
|
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// Get a list of indices whose values have changed from the previous one in the feature quantity
|
||||
void EnPassant::append_changed_indices(
|
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const Position& pos,
|
||||
Color /* perspective */,
|
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IndexList* removed,
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||||
IndexList* added) {
|
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auto previous_epSquare = pos.state()->previous->epSquare;
|
||||
auto epSquare = pos.state()->epSquare;
|
||||
|
||||
if (previous_epSquare != SQ_NONE) {
|
||||
if (epSquare != SQ_NONE && file_of(epSquare) == file_of(previous_epSquare))
|
||||
return;
|
||||
|
||||
auto file = file_of(previous_epSquare);
|
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removed->push_back(file);
|
||||
}
|
||||
|
||||
if (epSquare != SQ_NONE) {
|
||||
auto file = file_of(epSquare);
|
||||
added->push_back(file);
|
||||
}
|
||||
}
|
||||
|
||||
} // namespace Eval::NNUE::Features
|
||||
@@ -1,40 +0,0 @@
|
||||
#ifndef _NNUE_FEATURES_ENPASSANT_H_
|
||||
#define _NNUE_FEATURES_ENPASSANT_H_
|
||||
|
||||
#include "features_common.h"
|
||||
|
||||
#include "evaluate.h"
|
||||
|
||||
//Definition of input feature quantity EnPassant of NNUE evaluation function
|
||||
namespace Eval::NNUE::Features {
|
||||
|
||||
class EnPassant {
|
||||
public:
|
||||
// feature quantity name
|
||||
static constexpr const char* kName = "EnPassant";
|
||||
// Hash value embedded in the evaluation function file
|
||||
static constexpr std::uint32_t kHashValue = 0x02924F91u;
|
||||
// number of feature dimensions
|
||||
static constexpr IndexType kDimensions = 8;
|
||||
// The maximum value of the number of indexes whose value is 1 at the same time among the feature values
|
||||
static constexpr IndexType kMaxActiveDimensions = 1;
|
||||
// Timing of full calculation instead of difference calculation
|
||||
static constexpr TriggerEvent kRefreshTrigger = TriggerEvent::kNone;
|
||||
|
||||
// Get a list of indices with a value of 1 among the features
|
||||
static void append_active_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* active);
|
||||
|
||||
// Get a list of indices whose values have changed from the previous one in the feature quantity
|
||||
static void append_changed_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* removed,
|
||||
IndexList* added);
|
||||
};
|
||||
|
||||
} // namespace Eval::NNUE::Features
|
||||
|
||||
#endif
|
||||
@@ -1,93 +0,0 @@
|
||||
/*
|
||||
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
|
||||
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
|
||||
|
||||
Stockfish is free software: you can redistribute it and/or modify
|
||||
it under the terms of the GNU General Public License as published by
|
||||
the Free Software Foundation, either version 3 of the License, or
|
||||
(at your option) any later version.
|
||||
|
||||
Stockfish is distributed in the hope that it will be useful,
|
||||
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
GNU General Public License for more details.
|
||||
|
||||
You should have received a copy of the GNU General Public License
|
||||
along with this program. If not, see <http://www.gnu.org/licenses/>.
|
||||
*/
|
||||
|
||||
//Definition of input features HalfKA of NNUE evaluation function
|
||||
|
||||
#include "half_ka.h"
|
||||
#include "index_list.h"
|
||||
|
||||
namespace Eval::NNUE::Features {
|
||||
|
||||
// Orient a square according to perspective (rotate the board 180° for black)
|
||||
// Important note for "halfka": this arch was designed with "flip" in mind
|
||||
// although it still is untested which approach is better.
|
||||
// this has to stay until we find a better arch that works with "flip".
|
||||
// allows us to use current master net for gensfen (primarily needed for higher quality data)
|
||||
inline Square orient(Color perspective, Square s) {
|
||||
return Square(int(s) ^ (bool(perspective) * 63));
|
||||
}
|
||||
|
||||
// Find the index of the feature quantity from the king position and PieceSquare
|
||||
template <Side AssociatedKing>
|
||||
inline IndexType HalfKA<AssociatedKing>::make_index(
|
||||
Color perspective,
|
||||
Square s,
|
||||
Piece pc,
|
||||
Square ksq) {
|
||||
|
||||
return IndexType(orient(perspective, s) + kpp_board_index[pc][perspective] + PS_END2 * ksq);
|
||||
}
|
||||
|
||||
// Get a list of indices for active features
|
||||
template <Side AssociatedKing>
|
||||
void HalfKA<AssociatedKing>::append_active_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* active) {
|
||||
|
||||
Square ksq = orient(
|
||||
perspective,
|
||||
pos.square<KING>(
|
||||
AssociatedKing == Side::kFriend ? perspective : ~perspective));
|
||||
|
||||
Bitboard bb = pos.pieces();
|
||||
while (bb) {
|
||||
Square s = pop_lsb(&bb);
|
||||
active->push_back(make_index(perspective, s, pos.piece_on(s), ksq));
|
||||
}
|
||||
}
|
||||
|
||||
// Get a list of indices for recently changed features
|
||||
template <Side AssociatedKing>
|
||||
void HalfKA<AssociatedKing>::append_changed_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* removed,
|
||||
IndexList* added) {
|
||||
|
||||
Square ksq = orient(
|
||||
perspective,
|
||||
pos.square<KING>(
|
||||
AssociatedKing == Side::kFriend ? perspective : ~perspective));
|
||||
|
||||
const auto& dp = pos.state()->dirtyPiece;
|
||||
for (int i = 0; i < dp.dirty_num; ++i) {
|
||||
Piece pc = dp.piece[i];
|
||||
|
||||
if (dp.from[i] != SQ_NONE)
|
||||
removed->push_back(make_index(perspective, dp.from[i], pc, ksq));
|
||||
|
||||
if (dp.to[i] != SQ_NONE)
|
||||
added->push_back(make_index(perspective, dp.to[i], pc, ksq));
|
||||
}
|
||||
}
|
||||
|
||||
template class HalfKA<Side::kFriend>;
|
||||
template class HalfKA<Side::kEnemy>;
|
||||
|
||||
} // namespace Eval::NNUE::Features
|
||||
@@ -1,75 +0,0 @@
|
||||
/*
|
||||
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
|
||||
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
|
||||
|
||||
Stockfish is free software: you can redistribute it and/or modify
|
||||
it under the terms of the GNU General Public License as published by
|
||||
the Free Software Foundation, either version 3 of the License, or
|
||||
(at your option) any later version.
|
||||
|
||||
Stockfish is distributed in the hope that it will be useful,
|
||||
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
GNU General Public License for more details.
|
||||
|
||||
You should have received a copy of the GNU General Public License
|
||||
along with this program. If not, see <http://www.gnu.org/licenses/>.
|
||||
*/
|
||||
|
||||
#ifndef NNUE_FEATURES_HALF_KA_H_INCLUDED
|
||||
#define NNUE_FEATURES_HALF_KA_H_INCLUDED
|
||||
|
||||
#include "features_common.h"
|
||||
|
||||
#include "evaluate.h"
|
||||
|
||||
//Definition of input features HalfKPK of NNUE evaluation function
|
||||
namespace Eval::NNUE::Features {
|
||||
|
||||
// Feature HalfKPK: Combination of the position of own king
|
||||
// and the position of pieces other than kings
|
||||
template <Side AssociatedKing>
|
||||
class HalfKA {
|
||||
|
||||
public:
|
||||
// Feature name
|
||||
static constexpr const char* kName = (AssociatedKing == Side::kFriend) ?
|
||||
"HalfKA(Friend)" : "HalfKA(Enemy)";
|
||||
|
||||
// Hash value embedded in the evaluation file
|
||||
static constexpr std::uint32_t kHashValue =
|
||||
0x5F134CB9u ^ (AssociatedKing == Side::kFriend);
|
||||
|
||||
// Number of feature dimensions
|
||||
static constexpr IndexType kDimensions =
|
||||
static_cast<IndexType>(SQUARE_NB) * static_cast<IndexType>(PS_END2);
|
||||
|
||||
// Maximum number of simultaneously active features
|
||||
static constexpr IndexType kMaxActiveDimensions = 32;
|
||||
|
||||
// Trigger for full calculation instead of difference calculation
|
||||
static constexpr TriggerEvent kRefreshTrigger =
|
||||
(AssociatedKing == Side::kFriend) ?
|
||||
TriggerEvent::kFriendKingMoved : TriggerEvent::kEnemyKingMoved;
|
||||
|
||||
// Get a list of indices for active features
|
||||
static void append_active_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* active);
|
||||
|
||||
// Get a list of indices for recently changed features
|
||||
static void append_changed_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* removed,
|
||||
IndexList* added);
|
||||
|
||||
private:
|
||||
// Index of a feature for a given king position and another piece on some square
|
||||
static IndexType make_index(Color perspective, Square s, Piece pc, Square sq_k);
|
||||
};
|
||||
|
||||
} // namespace Eval::NNUE::Features
|
||||
|
||||
#endif // #ifndef NNUE_FEATURES_HALF_KA_H_INCLUDED
|
||||
@@ -1,90 +0,0 @@
|
||||
#include "half_relative_ka.h"
|
||||
#include "index_list.h"
|
||||
|
||||
//Definition of input features HalfRelativeKA of NNUE evaluation function
|
||||
namespace Eval::NNUE::Features {
|
||||
|
||||
// Orient a square according to perspective (rotate the board 180° for black)
|
||||
// Important note for "halfka": this arch was designed with "flip" in mind
|
||||
// although it still is untested which approach is better.
|
||||
// this has to stay until we find a better arch that works with "flip".
|
||||
// allows us to use current master net for gensfen (primarily needed for higher quality data)
|
||||
inline Square orient(Color perspective, Square s) {
|
||||
return Square(int(s) ^ (bool(perspective) * 63));
|
||||
}
|
||||
|
||||
// Find the index of the feature quantity from the ball position and PieceSquare
|
||||
template <Side AssociatedKing>
|
||||
inline IndexType HalfRelativeKA<AssociatedKing>::make_index(
|
||||
Color perspective,
|
||||
Square s,
|
||||
Piece pc,
|
||||
Square sq_k) {
|
||||
|
||||
const IndexType p = IndexType(orient(perspective, s) + kpp_board_index[pc][perspective]);
|
||||
return make_index(sq_k, p);
|
||||
}
|
||||
|
||||
// Find the index of the feature quantity from the ball position and PieceSquare
|
||||
template <Side AssociatedKing>
|
||||
inline IndexType HalfRelativeKA<AssociatedKing>::make_index(
|
||||
Square sq_k,
|
||||
IndexType p) {
|
||||
|
||||
constexpr IndexType W = kBoardWidth;
|
||||
constexpr IndexType H = kBoardHeight;
|
||||
const IndexType piece_index = (p - PS_W_PAWN) / SQUARE_NB;
|
||||
const Square sq_p = static_cast<Square>((p - PS_W_PAWN) % SQUARE_NB);
|
||||
const IndexType relative_file = file_of(sq_p) - file_of(sq_k) + (W / 2);
|
||||
const IndexType relative_rank = rank_of(sq_p) - rank_of(sq_k) + (H / 2);
|
||||
return H * W * piece_index + H * relative_file + relative_rank;
|
||||
}
|
||||
|
||||
// Get a list of indices with a value of 1 among the features
|
||||
template <Side AssociatedKing>
|
||||
void HalfRelativeKA<AssociatedKing>::append_active_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* active) {
|
||||
|
||||
Square ksq = orient(
|
||||
perspective,
|
||||
pos.square<KING>(
|
||||
AssociatedKing == Side::kFriend ? perspective : ~perspective));
|
||||
|
||||
Bitboard bb = pos.pieces();
|
||||
while (bb) {
|
||||
Square s = pop_lsb(&bb);
|
||||
active->push_back(make_index(perspective, s, pos.piece_on(s), ksq));
|
||||
}
|
||||
}
|
||||
|
||||
// Get a list of indices whose values have changed from the previous one in the feature quantity
|
||||
template <Side AssociatedKing>
|
||||
void HalfRelativeKA<AssociatedKing>::append_changed_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* removed,
|
||||
IndexList* added) {
|
||||
|
||||
Square ksq = orient(
|
||||
perspective,
|
||||
pos.square<KING>(
|
||||
AssociatedKing == Side::kFriend ? perspective : ~perspective));
|
||||
|
||||
const auto& dp = pos.state()->dirtyPiece;
|
||||
for (int i = 0; i < dp.dirty_num; ++i) {
|
||||
Piece pc = dp.piece[i];
|
||||
|
||||
if (dp.from[i] != SQ_NONE)
|
||||
removed->push_back(make_index(perspective, dp.from[i], pc, ksq));
|
||||
|
||||
if (dp.to[i] != SQ_NONE)
|
||||
added->push_back(make_index(perspective, dp.to[i], pc, ksq));
|
||||
}
|
||||
}
|
||||
|
||||
template class HalfRelativeKA<Side::kFriend>;
|
||||
template class HalfRelativeKA<Side::kEnemy>;
|
||||
|
||||
} // namespace Eval::NNUE::Features
|
||||
@@ -1,68 +0,0 @@
|
||||
#ifndef _NNUE_FEATURES_HALF_RELATIVE_KA_H_
|
||||
#define _NNUE_FEATURES_HALF_RELATIVE_KA_H_
|
||||
|
||||
#include "features_common.h"
|
||||
|
||||
#include "evaluate.h"
|
||||
|
||||
// Definition of input features HalfRelativeKA of NNUE evaluation function
|
||||
// K - King
|
||||
// A - Any piece
|
||||
// KA - product of K and A
|
||||
namespace Eval::NNUE::Features {
|
||||
|
||||
// Feature HalfRelativeKA: Relative position of each piece other than the ball based on own ball or enemy ball
|
||||
template <Side AssociatedKing>
|
||||
class HalfRelativeKA {
|
||||
public:
|
||||
// feature quantity name
|
||||
static constexpr const char* kName = (AssociatedKing == Side::kFriend) ?
|
||||
"HalfRelativeKA(Friend)" : "HalfRelativeKA(Enemy)";
|
||||
|
||||
// Hash value embedded in the evaluation function file
|
||||
static constexpr std::uint32_t kHashValue =
|
||||
0xA123051Fu ^ (AssociatedKing == Side::kFriend);
|
||||
|
||||
static constexpr IndexType kNumPieceKinds = 6 * 2;
|
||||
|
||||
// width of the virtual board with the ball in the center
|
||||
static constexpr IndexType kBoardWidth = FILE_NB * 2 - 1;
|
||||
|
||||
// height of a virtual board with balls in the center
|
||||
static constexpr IndexType kBoardHeight = RANK_NB * 2 - 1;
|
||||
|
||||
// number of feature dimensions
|
||||
static constexpr IndexType kDimensions =
|
||||
kNumPieceKinds * kBoardHeight * kBoardWidth;
|
||||
|
||||
// The maximum value of the number of indexes whose value is 1 at the same time among the feature values
|
||||
static constexpr IndexType kMaxActiveDimensions = 32;
|
||||
|
||||
// Timing of full calculation instead of difference calculation
|
||||
static constexpr TriggerEvent kRefreshTrigger =
|
||||
(AssociatedKing == Side::kFriend) ?
|
||||
TriggerEvent::kFriendKingMoved : TriggerEvent::kEnemyKingMoved;
|
||||
|
||||
// Get a list of indices with a value of 1 among the features
|
||||
static void append_active_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* active);
|
||||
|
||||
// Get a list of indices whose values have changed from the previous one in the feature quantity
|
||||
static void append_changed_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* removed,
|
||||
IndexList* added);
|
||||
|
||||
// Find the index of the feature quantity from the ball position and PieceSquare
|
||||
static IndexType make_index(Square s, IndexType p);
|
||||
|
||||
// Find the index of the feature quantity from the ball position and PieceSquare
|
||||
static IndexType make_index(Color perspective, Square s, Piece pc, Square sq_k);
|
||||
};
|
||||
|
||||
} // namespace Eval::NNUE::Features
|
||||
|
||||
#endif // #ifndef _NNUE_FEATURES_HALF_RELATIVE_KA_H_
|
||||
@@ -1,91 +0,0 @@
|
||||
#include "half_relative_kp.h"
|
||||
#include "index_list.h"
|
||||
|
||||
//Definition of input features HalfRelativeKP of NNUE evaluation function
|
||||
namespace Eval::NNUE::Features {
|
||||
|
||||
// Orient a square according to perspective (rotate the board 180° for black)
|
||||
// this has to stay until we find a better arch that works with "flip".
|
||||
// allows us to use current master net for gensfen (primarily needed for higher quality data)
|
||||
inline Square orient(Color perspective, Square s) {
|
||||
return Square(int(s) ^ (bool(perspective) * 63));
|
||||
}
|
||||
|
||||
// Find the index of the feature quantity from the ball position and PieceSquare
|
||||
template <Side AssociatedKing>
|
||||
inline IndexType HalfRelativeKP<AssociatedKing>::make_index(
|
||||
Color perspective,
|
||||
Square s,
|
||||
Piece pc,
|
||||
Square sq_k) {
|
||||
|
||||
const IndexType p = IndexType(orient(perspective, s) + kpp_board_index[pc][perspective]);
|
||||
return make_index(sq_k, p);
|
||||
}
|
||||
|
||||
// Find the index of the feature quantity from the ball position and PieceSquare
|
||||
template <Side AssociatedKing>
|
||||
inline IndexType HalfRelativeKP<AssociatedKing>::make_index(
|
||||
Square sq_k,
|
||||
IndexType p) {
|
||||
|
||||
constexpr IndexType W = kBoardWidth;
|
||||
constexpr IndexType H = kBoardHeight;
|
||||
const IndexType piece_index = (p - PS_W_PAWN) / SQUARE_NB;
|
||||
const Square sq_p = static_cast<Square>((p - PS_W_PAWN) % SQUARE_NB);
|
||||
const IndexType relative_file = file_of(sq_p) - file_of(sq_k) + (W / 2);
|
||||
const IndexType relative_rank = rank_of(sq_p) - rank_of(sq_k) + (H / 2);
|
||||
return H * W * piece_index + H * relative_file + relative_rank;
|
||||
}
|
||||
|
||||
// Get a list of indices with a value of 1 among the features
|
||||
template <Side AssociatedKing>
|
||||
void HalfRelativeKP<AssociatedKing>::append_active_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* active) {
|
||||
|
||||
Square ksq = orient(
|
||||
perspective,
|
||||
pos.square<KING>(
|
||||
AssociatedKing == Side::kFriend ? perspective : ~perspective));
|
||||
|
||||
Bitboard bb = pos.pieces() & ~pos.pieces(KING);
|
||||
while (bb) {
|
||||
Square s = pop_lsb(&bb);
|
||||
active->push_back(make_index(perspective, s, pos.piece_on(s), ksq));
|
||||
}
|
||||
}
|
||||
|
||||
// Get a list of indices whose values have changed from the previous one in the feature quantity
|
||||
template <Side AssociatedKing>
|
||||
void HalfRelativeKP<AssociatedKing>::append_changed_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* removed,
|
||||
IndexList* added) {
|
||||
|
||||
Square ksq = orient(
|
||||
perspective,
|
||||
pos.square<KING>(
|
||||
AssociatedKing == Side::kFriend ? perspective : ~perspective));
|
||||
|
||||
const auto& dp = pos.state()->dirtyPiece;
|
||||
for (int i = 0; i < dp.dirty_num; ++i) {
|
||||
Piece pc = dp.piece[i];
|
||||
|
||||
if (type_of(pc) == KING)
|
||||
continue;
|
||||
|
||||
if (dp.from[i] != SQ_NONE)
|
||||
removed->push_back(make_index(perspective, dp.from[i], pc, ksq));
|
||||
|
||||
if (dp.to[i] != SQ_NONE)
|
||||
added->push_back(make_index(perspective, dp.to[i], pc, ksq));
|
||||
}
|
||||
}
|
||||
|
||||
template class HalfRelativeKP<Side::kFriend>;
|
||||
template class HalfRelativeKP<Side::kEnemy>;
|
||||
|
||||
} // namespace Eval::NNUE::Features
|
||||
@@ -1,66 +0,0 @@
|
||||
#ifndef _NNUE_FEATURES_HALF_RELATIVE_KP_H_
|
||||
#define _NNUE_FEATURES_HALF_RELATIVE_KP_H_
|
||||
|
||||
#include "features_common.h"
|
||||
|
||||
#include "evaluate.h"
|
||||
|
||||
//Definition of input features HalfRelativeKP of NNUE evaluation function
|
||||
namespace Eval::NNUE::Features {
|
||||
|
||||
// Feature HalfRelativeKP: Relative position of each piece other than the ball based on own ball or enemy ball
|
||||
template <Side AssociatedKing>
|
||||
class HalfRelativeKP {
|
||||
public:
|
||||
// feature quantity name
|
||||
static constexpr const char* kName = (AssociatedKing == Side::kFriend) ?
|
||||
"HalfRelativeKP(Friend)" : "HalfRelativeKP(Enemy)";
|
||||
|
||||
// Hash value embedded in the evaluation function file
|
||||
static constexpr std::uint32_t kHashValue =
|
||||
0xF9180919u ^ (AssociatedKing == Side::kFriend);
|
||||
|
||||
// Piece type excluding balls
|
||||
static constexpr IndexType kNumPieceKinds = 5 * 2;
|
||||
|
||||
// width of the virtual board with the ball in the center
|
||||
static constexpr IndexType kBoardWidth = FILE_NB * 2 - 1;
|
||||
|
||||
// height of a virtual board with balls in the center
|
||||
static constexpr IndexType kBoardHeight = RANK_NB * 2 - 1;
|
||||
|
||||
// number of feature dimensions
|
||||
static constexpr IndexType kDimensions =
|
||||
kNumPieceKinds * kBoardHeight * kBoardWidth;
|
||||
|
||||
// The maximum value of the number of indexes whose value is 1 at the same time among the feature values
|
||||
static constexpr IndexType kMaxActiveDimensions = 30; // Kings don't count
|
||||
|
||||
// Timing of full calculation instead of difference calculation
|
||||
static constexpr TriggerEvent kRefreshTrigger =
|
||||
(AssociatedKing == Side::kFriend) ?
|
||||
TriggerEvent::kFriendKingMoved : TriggerEvent::kEnemyKingMoved;
|
||||
|
||||
// Get a list of indices with a value of 1 among the features
|
||||
static void append_active_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* active);
|
||||
|
||||
// Get a list of indices whose values have changed from the previous one in the feature quantity
|
||||
static void append_changed_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* removed,
|
||||
IndexList* added);
|
||||
|
||||
// Find the index of the feature quantity from the ball position and PieceSquare
|
||||
static IndexType make_index(Square s, IndexType p);
|
||||
|
||||
// Find the index of the feature quantity from the ball position and PieceSquare
|
||||
static IndexType make_index(Color perspective, Square s, Piece pc, Square sq_k);
|
||||
};
|
||||
|
||||
} // namespace Eval::NNUE::Features
|
||||
|
||||
#endif
|
||||
@@ -1,45 +0,0 @@
|
||||
#include "k.h"
|
||||
#include "index_list.h"
|
||||
|
||||
//Definition of input feature quantity K of NNUE evaluation function
|
||||
namespace Eval::NNUE::Features {
|
||||
|
||||
// Orient a square according to perspective (rotate the board 180° for black)
|
||||
// this has to stay until we find a better arch that works with "flip".
|
||||
// allows us to use current master net for gensfen (primarily needed for higher quality data)
|
||||
inline Square orient(Color perspective, Square s) {
|
||||
return Square(int(s) ^ (bool(perspective) * 63));
|
||||
}
|
||||
|
||||
// Index of a feature for a given king position.
|
||||
IndexType K::make_index(Color perspective, Square s, Color king_color) {
|
||||
return IndexType(orient(perspective, s) + bool(perspective ^ king_color) * 64);
|
||||
}
|
||||
|
||||
// Get a list of indices with a value of 1 among the features
|
||||
void K::append_active_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* active) {
|
||||
|
||||
for (auto color : Colors) {
|
||||
active->push_back(make_index(perspective, pos.square<KING>(color), color));
|
||||
}
|
||||
}
|
||||
|
||||
// Get a list of indices whose values have changed from the previous one in the feature quantity
|
||||
void K::append_changed_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* removed,
|
||||
IndexList* added) {
|
||||
|
||||
const auto& dp = pos.state()->dirtyPiece;
|
||||
if (type_of(dp.piece[0]) == KING)
|
||||
{
|
||||
removed->push_back(make_index(perspective, dp.from[0], color_of(dp.piece[0])));
|
||||
added->push_back(make_index(perspective, dp.to[0], color_of(dp.piece[0])));
|
||||
}
|
||||
}
|
||||
|
||||
} // namespace Eval::NNUE::Features
|
||||
@@ -1,49 +0,0 @@
|
||||
#ifndef _NNUE_FEATURES_K_H_
|
||||
#define _NNUE_FEATURES_K_H_
|
||||
|
||||
#include "features_common.h"
|
||||
|
||||
#include "evaluate.h"
|
||||
|
||||
//Definition of input feature quantity K of NNUE evaluation function
|
||||
namespace Eval::NNUE::Features {
|
||||
|
||||
// Feature K: Ball position
|
||||
class K {
|
||||
public:
|
||||
// feature quantity name
|
||||
static constexpr const char* kName = "K";
|
||||
|
||||
// Hash value embedded in the evaluation function file
|
||||
static constexpr std::uint32_t kHashValue = 0xD3CEE169u;
|
||||
|
||||
// number of feature dimensions
|
||||
static constexpr IndexType kDimensions = SQUARE_NB * 2;
|
||||
|
||||
// The maximum value of the number of indexes whose value is 1 at the same time among the feature values
|
||||
static constexpr IndexType kMaxActiveDimensions = 2;
|
||||
|
||||
// Timing of full calculation instead of difference calculation
|
||||
static constexpr TriggerEvent kRefreshTrigger = TriggerEvent::kNone;
|
||||
|
||||
// Get a list of indices with a value of 1 among the features
|
||||
static void append_active_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* active);
|
||||
|
||||
// Get a list of indices whose values have changed from the previous one in the feature quantity
|
||||
static void append_changed_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* removed,
|
||||
IndexList* added);
|
||||
|
||||
private:
|
||||
// Index of a feature for a given king position.
|
||||
static IndexType make_index(Color perspective, Square s, Color king_color);
|
||||
};
|
||||
|
||||
} // namespace Eval::NNUE::Features
|
||||
|
||||
#endif
|
||||
@@ -1,55 +0,0 @@
|
||||
#include "p.h"
|
||||
#include "index_list.h"
|
||||
|
||||
//Definition of input feature P of NNUE evaluation function
|
||||
namespace Eval::NNUE::Features {
|
||||
|
||||
// Orient a square according to perspective (rotate the board 180° for black)
|
||||
// this has to stay until we find a better arch that works with "flip".
|
||||
// allows us to use current master net for gensfen (primarily needed for higher quality data)
|
||||
inline Square orient(Color perspective, Square s) {
|
||||
return Square(int(s) ^ (bool(perspective) * 63));
|
||||
}
|
||||
|
||||
// Find the index of the feature quantity from the king position and PieceSquare
|
||||
inline IndexType P::make_index(
|
||||
Color perspective, Square s, Piece pc) {
|
||||
return IndexType(orient(perspective, s) + kpp_board_index[pc][perspective]);
|
||||
}
|
||||
|
||||
// Get a list of indices with a value of 1 among the features
|
||||
void P::append_active_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* active) {
|
||||
|
||||
Bitboard bb = pos.pieces() & ~pos.pieces(KING);
|
||||
while (bb) {
|
||||
Square s = pop_lsb(&bb);
|
||||
active->push_back(make_index(perspective, s, pos.piece_on(s)));
|
||||
}
|
||||
}
|
||||
|
||||
// Get a list of indices whose values have changed from the previous one in the feature quantity
|
||||
void P::append_changed_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* removed,
|
||||
IndexList* added) {
|
||||
|
||||
const auto& dp = pos.state()->dirtyPiece;
|
||||
for (int i = 0; i < dp.dirty_num; ++i) {
|
||||
Piece pc = dp.piece[i];
|
||||
|
||||
if (type_of(pc) == KING)
|
||||
continue;
|
||||
|
||||
if (dp.from[i] != SQ_NONE)
|
||||
removed->push_back(make_index(perspective, dp.from[i], pc));
|
||||
|
||||
if (dp.to[i] != SQ_NONE)
|
||||
added->push_back(make_index(perspective, dp.to[i], pc));
|
||||
}
|
||||
}
|
||||
|
||||
} // namespace Eval::NNUE::Features
|
||||
@@ -1,49 +0,0 @@
|
||||
#ifndef _NNUE_FEATURES_P_H_
|
||||
#define _NNUE_FEATURES_P_H_
|
||||
|
||||
#include "features_common.h"
|
||||
|
||||
#include "evaluate.h"
|
||||
|
||||
//Definition of input feature P of NNUE evaluation function
|
||||
namespace Eval::NNUE::Features {
|
||||
|
||||
// Feature P: PieceSquare of pieces other than balls
|
||||
class P {
|
||||
public:
|
||||
// feature quantity name
|
||||
static constexpr const char* kName = "P";
|
||||
|
||||
// Hash value embedded in the evaluation function file
|
||||
static constexpr std::uint32_t kHashValue = 0x764CFB4Bu;
|
||||
|
||||
// number of feature dimensions
|
||||
static constexpr IndexType kDimensions = PS_END;
|
||||
|
||||
// The maximum value of the number of indexes whose value is 1 at the same time among the feature values
|
||||
static constexpr IndexType kMaxActiveDimensions = 30; // Kings don't count
|
||||
|
||||
// Timing of full calculation instead of difference calculation
|
||||
static constexpr TriggerEvent kRefreshTrigger = TriggerEvent::kNone;
|
||||
|
||||
// Get a list of indices with a value of 1 among the features
|
||||
static void append_active_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* active);
|
||||
|
||||
// Get a list of indices whose values have changed from the previous one in the feature quantity
|
||||
static void append_changed_indices(
|
||||
const Position& pos,
|
||||
Color perspective,
|
||||
IndexList* removed,
|
||||
IndexList* added);
|
||||
|
||||
private:
|
||||
// Index of a feature for a given piece on some square
|
||||
static IndexType make_index(Color perspective, Square s, Piece pc);
|
||||
};
|
||||
|
||||
} // namespace Eval::NNUE::Features
|
||||
|
||||
#endif
|
||||
@@ -1,196 +0,0 @@
|
||||
#ifndef _NNUE_LAYERS_SUM_H_
|
||||
#define _NNUE_LAYERS_SUM_H_
|
||||
|
||||
#include "nnue/nnue_common.h"
|
||||
|
||||
// Definition of layer Sum of NNUE evaluation function
|
||||
namespace Eval::NNUE::Layers {
|
||||
|
||||
// Layer that sums the output of multiple layers
|
||||
template <typename FirstPreviousLayer, typename... RemainingPreviousLayers>
|
||||
class Sum : public Sum<RemainingPreviousLayers...> {
|
||||
private:
|
||||
using Head = FirstPreviousLayer;
|
||||
using Tail = Sum<RemainingPreviousLayers...>;
|
||||
|
||||
public:
|
||||
// Input/output type
|
||||
using InputType = typename Head::OutputType;
|
||||
|
||||
using OutputType = InputType;
|
||||
|
||||
static_assert(std::is_same<InputType, typename Tail::InputType>::value, "");
|
||||
|
||||
// number of input/output dimensions
|
||||
static constexpr IndexType kInputDimensions = Head::kOutputDimensions;
|
||||
|
||||
static constexpr IndexType kOutputDimensions = kInputDimensions;
|
||||
|
||||
static_assert(kInputDimensions == Tail::kInputDimensions ,"");
|
||||
|
||||
// Size of forward propagation buffer used in this layer
|
||||
static constexpr std::size_t kSelfBufferSize =
|
||||
CeilToMultiple(kOutputDimensions * sizeof(OutputType), kCacheLineSize);
|
||||
|
||||
// Size of the forward propagation buffer used from the input layer to this layer
|
||||
static constexpr std::size_t kBufferSize =
|
||||
std::max(Head::kBufferSize + kSelfBufferSize, Tail::kBufferSize);
|
||||
|
||||
static constexpr int kLayerIndex = Tail::kLayerIndex + 1;
|
||||
|
||||
// Hash value embedded in the evaluation function file
|
||||
static constexpr std::uint32_t GetHashValue() {
|
||||
std::uint32_t hash_value = 0xBCE400B4u;
|
||||
hash_value ^= Head::GetHashValue() >> 1;
|
||||
hash_value ^= Head::GetHashValue() << 31;
|
||||
hash_value ^= Tail::GetHashValue() >> 2;
|
||||
hash_value ^= Tail::GetHashValue() << 30;
|
||||
return hash_value;
|
||||
}
|
||||
|
||||
static std::string get_name() {
|
||||
return "Sum[" +
|
||||
std::to_string(kOutputDimensions) + "]";
|
||||
}
|
||||
|
||||
// A string that represents the structure from the input layer to this layer
|
||||
static std::string get_structure_string() {
|
||||
return get_name() + "(" + get_summands_string() + ")";
|
||||
}
|
||||
|
||||
static std::string get_layers_info() {
|
||||
std::string info = Tail::get_layers_info();
|
||||
info += "\n - ";
|
||||
info += std::to_string(kLayerIndex);
|
||||
info += " - ";
|
||||
info += get_name();
|
||||
return info;
|
||||
}
|
||||
|
||||
// read parameters
|
||||
bool ReadParameters(std::istream& stream) {
|
||||
if (!Tail::ReadParameters(stream))
|
||||
return false;
|
||||
|
||||
return previous_layer_.ReadParameters(stream);
|
||||
}
|
||||
|
||||
// write parameters
|
||||
bool WriteParameters(std::ostream& stream) const {
|
||||
if (!Tail::WriteParameters(stream))
|
||||
return false;
|
||||
|
||||
return previous_layer_.WriteParameters(stream);
|
||||
}
|
||||
|
||||
// forward propagation
|
||||
const OutputType* propagate(
|
||||
const TransformedFeatureType* transformed_features, char* buffer) const {
|
||||
|
||||
Tail::propagate(transformed_features, buffer);
|
||||
|
||||
const auto head_output = previous_layer_.Propagate(
|
||||
transformed_features, buffer + kSelfBufferSize);
|
||||
|
||||
const auto output = reinterpret_cast<OutputType*>(buffer);
|
||||
|
||||
for (IndexType i = 0; i <kOutputDimensions; ++i) {
|
||||
output[i] += head_output[i];
|
||||
}
|
||||
|
||||
return output;
|
||||
}
|
||||
|
||||
protected:
|
||||
// A string that represents the list of layers to be summed
|
||||
static std::string get_summands_string() {
|
||||
return Head::get_structure_string() + "," + Tail::get_summands_string();
|
||||
}
|
||||
|
||||
// Make the learning class a friend
|
||||
friend class Trainer<Sum>;
|
||||
|
||||
// the layer immediately before this layer
|
||||
FirstPreviousLayer previous_layer_;
|
||||
};
|
||||
|
||||
// Layer that sums the output of multiple layers (when there is one template argument)
|
||||
template <typename PreviousLayer>
|
||||
class Sum<PreviousLayer> {
|
||||
public:
|
||||
// Input/output type
|
||||
using InputType = typename PreviousLayer::OutputType;
|
||||
|
||||
using OutputType = InputType;
|
||||
|
||||
// number of input/output dimensions
|
||||
static constexpr IndexType kInputDimensions =
|
||||
PreviousLayer::kOutputDimensions;
|
||||
|
||||
static constexpr IndexType kOutputDimensions = kInputDimensions;
|
||||
|
||||
// Size of the forward propagation buffer used from the input layer to this layer
|
||||
static constexpr std::size_t kBufferSize = PreviousLayer::kBufferSize;
|
||||
|
||||
static constexpr int kLayerIndex = PreviousLayer::kLayerIndex + 1;
|
||||
|
||||
// Hash value embedded in the evaluation function file
|
||||
static constexpr std::uint32_t GetHashValue() {
|
||||
std::uint32_t hash_value = 0xBCE400B4u;
|
||||
hash_value ^= PreviousLayer::GetHashValue() >> 1;
|
||||
hash_value ^= PreviousLayer::GetHashValue() << 31;
|
||||
return hash_value;
|
||||
}
|
||||
|
||||
static std::string get_name() {
|
||||
return "Sum[" +
|
||||
std::to_string(kOutputDimensions) + "]";
|
||||
}
|
||||
|
||||
// A string that represents the structure from the input layer to this layer
|
||||
static std::string get_structure_string() {
|
||||
return get_name() + "(" + get_summands_string() + ")";
|
||||
}
|
||||
|
||||
static std::string get_layers_info() {
|
||||
std::string info = PreviousLayer::get_layers_info();
|
||||
info += '\n';
|
||||
info += std::to_string(kLayerIndex);
|
||||
info += ": ";
|
||||
info += get_name();
|
||||
return info;
|
||||
}
|
||||
|
||||
// read parameters
|
||||
bool ReadParameters(std::istream& stream) {
|
||||
return previous_layer_.ReadParameters(stream);
|
||||
}
|
||||
|
||||
// write parameters
|
||||
bool WriteParameters(std::ostream& stream) const {
|
||||
return previous_layer_.WriteParameters(stream);
|
||||
}
|
||||
|
||||
// forward propagation
|
||||
const OutputType* Propagate(
|
||||
const TransformedFeatureType* transformed_features, char* buffer) const {
|
||||
|
||||
return previous_layer_.Propagate(transformed_features, buffer);
|
||||
}
|
||||
|
||||
protected:
|
||||
// A string that represents the list of layers to be summed
|
||||
static std::string get_summands_string() {
|
||||
return PreviousLayer::get_structure_string();
|
||||
}
|
||||
|
||||
// Make the learning class a friend
|
||||
friend class Trainer<Sum>;
|
||||
|
||||
// the layer immediately before this layer
|
||||
PreviousLayer previous_layer_;
|
||||
};
|
||||
|
||||
} // namespace Eval::NNUE::Layers
|
||||
|
||||
#endif
|
||||
Reference in New Issue
Block a user