diff --git a/src/nnue/architectures/halfkp-cr-ep_256x2-32-32.h b/src/nnue/architectures/halfkp-cr-ep_256x2-32-32.h
index a90de8e6..6327b78a 100644
--- a/src/nnue/architectures/halfkp-cr-ep_256x2-32-32.h
+++ b/src/nnue/architectures/halfkp-cr-ep_256x2-32-32.h
@@ -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
 
diff --git a/src/nnue/architectures/halfkp-cr_256x2-32-32.h b/src/nnue/architectures/halfkp-cr_256x2-32-32.h
index df14f499..dd587d1d 100644
--- a/src/nnue/architectures/halfkp-cr_256x2-32-32.h
+++ b/src/nnue/architectures/halfkp-cr_256x2-32-32.h
@@ -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
 
diff --git a/src/nnue/architectures/halfkp_256x2-32-32.h b/src/nnue/architectures/halfkp_256x2-32-32.h
index 9216bd41..333feb83 100644
--- a/src/nnue/architectures/halfkp_256x2-32-32.h
+++ b/src/nnue/architectures/halfkp_256x2-32-32.h
@@ -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
 
diff --git a/src/nnue/architectures/halfkp_384x2-32-32.h b/src/nnue/architectures/halfkp_384x2-32-32.h
index 3d28139a..96913295 100644
--- a/src/nnue/architectures/halfkp_384x2-32-32.h
+++ b/src/nnue/architectures/halfkp_384x2-32-32.h
@@ -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
diff --git a/src/nnue/architectures/k-p-cr-ep_256x2-32-32.h b/src/nnue/architectures/k-p-cr-ep_256x2-32-32.h
index e178b57b..14eeba54 100644
--- a/src/nnue/architectures/k-p-cr-ep_256x2-32-32.h
+++ b/src/nnue/architectures/k-p-cr-ep_256x2-32-32.h
@@ -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
diff --git a/src/nnue/architectures/k-p-cr_256x2-32-32.h b/src/nnue/architectures/k-p-cr_256x2-32-32.h
index d3c187c0..1db34b22 100644
--- a/src/nnue/architectures/k-p-cr_256x2-32-32.h
+++ b/src/nnue/architectures/k-p-cr_256x2-32-32.h
@@ -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
diff --git a/src/nnue/architectures/k-p_256x2-32-32.h b/src/nnue/architectures/k-p_256x2-32-32.h
index 0f340dee..92c9efcd 100644
--- a/src/nnue/architectures/k-p_256x2-32-32.h
+++ b/src/nnue/architectures/k-p_256x2-32-32.h
@@ -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