Cleanup architecture files.

This commit is contained in:
Tomasz Sobczyk
2020-10-14 20:24:26 +02:00
committed by nodchip
parent c93f8732bf
commit ca760c3a5b
7 changed files with 153 additions and 169 deletions
@@ -1,19 +1,19 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
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 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.
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/>.
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 and network structure used in NNUE evaluation function
@@ -21,36 +21,36 @@
#ifndef NNUE_HALFKP_CR_EP_256X2_32_32_H_INCLUDED
#define NNUE_HALFKP_CR_EP_256X2_32_32_H_INCLUDED
#include "../features/feature_set.h"
#include "../features/half_kp.h"
#include "../features/castling_right.h"
#include "../features/enpassant.h"
#include "nnue/features/feature_set.h"
#include "nnue/features/half_kp.h"
#include "nnue/features/castling_right.h"
#include "nnue/features/enpassant.h"
#include "../layers/input_slice.h"
#include "../layers/affine_transform.h"
#include "../layers/clipped_relu.h"
#include "nnue/layers/input_slice.h"
#include "nnue/layers/affine_transform.h"
#include "nnue/layers/clipped_relu.h"
namespace Eval::NNUE {
// Input features used in evaluation function
using RawFeatures = Features::FeatureSet<
Features::HalfKP<Features::Side::kFriend>, Features::CastlingRight,
Features::EnPassant>;
// Input features used in evaluation function
using RawFeatures = Features::FeatureSet<
Features::HalfKP<Features::Side::kFriend>, Features::CastlingRight,
Features::EnPassant>;
// Number of input feature dimensions after conversion
constexpr IndexType kTransformedFeatureDimensions = 256;
// Number of input feature dimensions after conversion
constexpr IndexType kTransformedFeatureDimensions = 256;
namespace Layers {
namespace Layers {
// Define network structure
using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
using OutputLayer = AffineTransform<HiddenLayer2, 1>;
// Define network structure
using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
using OutputLayer = AffineTransform<HiddenLayer2, 1>;
} // namespace Layers
} // namespace Layers
using Network = Layers::OutputLayer;
using Network = Layers::OutputLayer;
} // namespace Eval::NNUE
+19 -19
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@@ -3,34 +3,34 @@
#ifndef NNUE_HALFKP_CR_256X2_32_32_H_INCLUDED
#define NNUE_HALFKP_CR_256X2_32_32_H_INCLUDED
#include "../features/feature_set.h"
#include "../features/half_kp.h"
#include "../features/castling_right.h"
#include "nnue/features/feature_set.h"
#include "nnue/features/half_kp.h"
#include "nnue/features/castling_right.h"
#include "../layers/input_slice.h"
#include "../layers/affine_transform.h"
#include "../layers/clipped_relu.h"
#include "nnue/layers/input_slice.h"
#include "nnue/layers/affine_transform.h"
#include "nnue/layers/clipped_relu.h"
namespace Eval::NNUE {
// Input features used in evaluation function
using RawFeatures = Features::FeatureSet<
Features::HalfKP<Features::Side::kFriend>, Features::CastlingRight>;
// Input features used in evaluation function
using RawFeatures = Features::FeatureSet<
Features::HalfKP<Features::Side::kFriend>, Features::CastlingRight>;
// Number of input feature dimensions after conversion
constexpr IndexType kTransformedFeatureDimensions = 256;
// Number of input feature dimensions after conversion
constexpr IndexType kTransformedFeatureDimensions = 256;
namespace Layers {
namespace Layers {
// Define network structure
using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
using OutputLayer = AffineTransform<HiddenLayer2, 1>;
// Define network structure
using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
using OutputLayer = AffineTransform<HiddenLayer2, 1>;
} // namespace Layers
} // namespace Layers
using Network = Layers::OutputLayer;
using Network = Layers::OutputLayer;
} // namespace Eval::NNUE
+30 -30
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@@ -1,19 +1,19 @@
/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
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 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.
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/>.
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 and network structure used in NNUE evaluation function
@@ -21,33 +21,33 @@
#ifndef NNUE_HALFKP_256X2_32_32_H_INCLUDED
#define NNUE_HALFKP_256X2_32_32_H_INCLUDED
#include "../features/feature_set.h"
#include "../features/half_kp.h"
#include "nnue/features/feature_set.h"
#include "nnue/features/half_kp.h"
#include "../layers/input_slice.h"
#include "../layers/affine_transform.h"
#include "../layers/clipped_relu.h"
#include "nnue/layers/input_slice.h"
#include "nnue/layers/affine_transform.h"
#include "nnue/layers/clipped_relu.h"
namespace Eval::NNUE {
// Input features used in evaluation function
using RawFeatures = Features::FeatureSet<
Features::HalfKP<Features::Side::kFriend>>;
// Input features used in evaluation function
using RawFeatures = Features::FeatureSet<
Features::HalfKP<Features::Side::kFriend>>;
// Number of input feature dimensions after conversion
constexpr IndexType kTransformedFeatureDimensions = 256;
// Number of input feature dimensions after conversion
constexpr IndexType kTransformedFeatureDimensions = 256;
namespace Layers {
namespace Layers {
// Define network structure
using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
using OutputLayer = AffineTransform<HiddenLayer2, 1>;
// Define network structure
using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
using OutputLayer = AffineTransform<HiddenLayer2, 1>;
} // namespace Layers
} // namespace Layers
using Network = Layers::OutputLayer;
using Network = Layers::OutputLayer;
} // namespace Eval::NNUE
+20 -24
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@@ -3,37 +3,33 @@
#ifndef HALFKP_384X2_32_32_H
#define HALFKP_384X2_32_32_H
#include "../features/feature_set.h"
#include "../features/half_kp.h"
#include "nnue/features/feature_set.h"
#include "nnue/features/half_kp.h"
#include "../layers/input_slice.h"
#include "../layers/affine_transform.h"
#include "../layers/clipped_relu.h"
#include "nnue/layers/input_slice.h"
#include "nnue/layers/affine_transform.h"
#include "nnue/layers/clipped_relu.h"
namespace Eval {
namespace Eval::NNUE {
namespace NNUE {
// Input features used in evaluation function
using RawFeatures = Features::FeatureSet<
Features::HalfKP<Features::Side::kFriend>>;
// Input features used in evaluation function
using RawFeatures = Features::FeatureSet<
Features::HalfKP<Features::Side::kFriend>>;
// Number of input feature dimensions after conversion
constexpr IndexType kTransformedFeatureDimensions = 384;
// Number of input feature dimensions after conversion
constexpr IndexType kTransformedFeatureDimensions = 384;
namespace Layers {
namespace Layers {
// define network structure
using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
using OutputLayer = AffineTransform<HiddenLayer2, 1>;
// define network structure
using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
using OutputLayer = AffineTransform<HiddenLayer2, 1>;
} // namespace Layers
} // namespace Layers
using Network = Layers::OutputLayer;
using Network = Layers::OutputLayer;
} // namespace NNUE
} // namespace Eval
} // namespace Eval::NNUE
#endif // HALFKP_384X2_32_32_H
+16 -20
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@@ -3,40 +3,36 @@
#ifndef K_P_CR_EP_256X2_32_32_H
#define K_P_CR_EP_256X2_32_32_H
#include "../features/feature_set.h"
#include "../features/k.h"
#include "../features/p.h"
#include "../features/castling_right.h"
#include "../features/enpassant.h"
#include "nnue/features/feature_set.h"
#include "nnue/features/k.h"
#include "nnue/features/p.h"
#include "nnue/features/castling_right.h"
#include "nnue/features/enpassant.h"
#include "../layers/input_slice.h"
#include "../layers/affine_transform.h"
#include "../layers/clipped_relu.h"
#include "nnue/layers/input_slice.h"
#include "nnue/layers/affine_transform.h"
#include "nnue/layers/clipped_relu.h"
namespace Eval {
namespace NNUE {
namespace Eval::NNUE {
// Input features used in evaluation function
using RawFeatures = Features::FeatureSet<Features::K, Features::P,
Features::CastlingRight, Features::EnPassant>;
Features::CastlingRight, Features::EnPassant>;
// Number of input feature dimensions after conversion
constexpr IndexType kTransformedFeatureDimensions = 256;
namespace Layers {
// define network structure
using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
using OutputLayer = AffineTransform<HiddenLayer2, 1>;
// define network structure
using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
using OutputLayer = AffineTransform<HiddenLayer2, 1>;
} // namespace Layers
using Network = Layers::OutputLayer;
} // namespace NNUE
} // namespace Eval
} // namespace Eval::NNUE
#endif // K_P_CR_EP_256X2_32_32_H
+15 -19
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@@ -3,39 +3,35 @@
#ifndef K_P_CR_256X2_32_32_H
#define K_P_CR_256X2_32_32_H
#include "../features/feature_set.h"
#include "../features/k.h"
#include "../features/p.h"
#include "../features/castling_right.h"
#include "nnue/features/feature_set.h"
#include "nnue/features/k.h"
#include "nnue/features/p.h"
#include "nnue/features/castling_right.h"
#include "../layers/input_slice.h"
#include "../layers/affine_transform.h"
#include "../layers/clipped_relu.h"
#include "nnue/layers/input_slice.h"
#include "nnue/layers/affine_transform.h"
#include "nnue/layers/clipped_relu.h"
namespace Eval {
namespace NNUE {
namespace Eval::NNUE {
// Input features used in evaluation function
using RawFeatures = Features::FeatureSet<Features::K, Features::P,
Features::CastlingRight>;
Features::CastlingRight>;
// Number of input feature dimensions after conversion
constexpr IndexType kTransformedFeatureDimensions = 256;
namespace Layers {
// define network structure
using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
using OutputLayer = AffineTransform<HiddenLayer2, 1>;
// define network structure
using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
using OutputLayer = AffineTransform<HiddenLayer2, 1>;
} // namespace Layers
using Network = Layers::OutputLayer;
} // namespace NNUE
} // namespace Eval
} // namespace Eval::NNUE
#endif // K_P_CR_256X2_32_32_H
+20 -24
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@@ -3,37 +3,33 @@
#ifndef K_P_256X2_32_32_H
#define K_P_256X2_32_32_H
#include "../features/feature_set.h"
#include "../features/k.h"
#include "../features/p.h"
#include "nnue/features/feature_set.h"
#include "nnue/features/k.h"
#include "nnue/features/p.h"
#include "../layers/input_slice.h"
#include "../layers/affine_transform.h"
#include "../layers/clipped_relu.h"
#include "nnue/layers/input_slice.h"
#include "nnue/layers/affine_transform.h"
#include "nnue/layers/clipped_relu.h"
namespace Eval {
namespace Eval::NNUE {
namespace NNUE {
// Input features used in evaluation function
using RawFeatures = Features::FeatureSet<Features::K, Features::P>;
// Input features used in evaluation function
using RawFeatures = Features::FeatureSet<Features::K, Features::P>;
// Number of input feature dimensions after conversion
constexpr IndexType kTransformedFeatureDimensions = 256;
// Number of input feature dimensions after conversion
constexpr IndexType kTransformedFeatureDimensions = 256;
namespace Layers {
namespace Layers {
// define network structure
using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
using OutputLayer = AffineTransform<HiddenLayer2, 1>;
// define network structure
using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
using OutputLayer = AffineTransform<HiddenLayer2, 1>;
} // namespace Layers
} // namespace Layers
using Network = Layers::OutputLayer;
using Network = Layers::OutputLayer;
} // namespace NNUE
} // namespace Eval
} // namespace Eval::NNUE
#endif // K_P_256X2_32_32_H