61 lines
2.0 KiB
C++
61 lines
2.0 KiB
C++
/*
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Stockfish, a UCI chess playing engine derived from Glaurung 2.1
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Copyright (C) 2004-2021 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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// Input features and network structure used in NNUE evaluation function
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#ifndef NNUE_ARCHITECTURE_H_INCLUDED
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#define NNUE_ARCHITECTURE_H_INCLUDED
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#include "nnue_common.h"
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#include "features/half_ka_v2_hm.h"
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#include "layers/input_slice.h"
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#include "layers/affine_transform.h"
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#include "layers/clipped_relu.h"
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namespace Stockfish::Eval::NNUE {
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// Input features used in evaluation function
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using FeatureSet = Features::HalfKAv2_hm;
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// Number of input feature dimensions after conversion
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constexpr IndexType TransformedFeatureDimensions = 1024;
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constexpr IndexType PSQTBuckets = 8;
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constexpr IndexType LayerStacks = 8;
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namespace Layers {
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// Define network structure
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using InputLayer = InputSlice<TransformedFeatureDimensions * 2>;
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using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 8>>;
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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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static_assert(TransformedFeatureDimensions % MaxSimdWidth == 0, "");
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static_assert(Network::OutputDimensions == 1, "");
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static_assert(std::is_same<Network::OutputType, std::int32_t>::value, "");
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} // namespace Stockfish::Eval::NNUE
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#endif // #ifndef NNUE_ARCHITECTURE_H_INCLUDED
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