Remove conditional compilation on EVAL_LEARN

src/eval/evaluate_common.h

@@ -1,8 +1,6 @@
 #ifndef _EVALUATE_COMMON_H_
 #define _EVALUATE_COMMON_H_
 
-#if defined(EVAL_LEARN)
-
 // A common header-like function for modern evaluation functions.
 
 #include <string>
@@ -21,6 +19,4 @@ namespace Eval
 	double get_eta();
 }
 
-#endif // defined(EVAL_LEARN)
-
 #endif // _EVALUATE_KPPT_COMMON_H_

src/evaluate.cpp

@@ -43,11 +43,8 @@ namespace Eval {
       return UseNNUEMode::False;
     else if (mode == "true")
       return UseNNUEMode::True;
-
-#ifdef EVAL_LEARN
     else if (mode == "pure")
       return UseNNUEMode::Pure;
-#endif
 
     return UseNNUEMode::False;
   }
@@ -955,11 +952,9 @@ make_v:
 /// evaluation of the position from the point of view of the side to move.
 
 Value Eval::evaluate(const Position& pos) {
-#ifdef EVAL_LEARN
   if (useNNUE == UseNNUEMode::Pure) {
       return NNUE::evaluate(pos);
   }
-#endif
 
   bool classical = useNNUE == UseNNUEMode::False
                 || abs(eg_value(pos.psq_score())) * 16 > NNUEThreshold1 * (16 + pos.rule50_count());

src/evaluate.h

@@ -29,11 +29,8 @@ namespace Eval {
   enum struct UseNNUEMode
   {
     False,
-    True
+    True,
-
+    Pure
-#ifdef EVAL_LEARN
-    ,Pure
-#endif
   };
 
   std::string trace(const Position& pos);

src/learn/convert.cpp

@@ -1,5 +1,3 @@
-#if defined(EVAL_LEARN)
-
 #include "convert.h"
 
 #include "multi_think.h"
@@ -606,4 +604,3 @@ namespace Learner
         convert(args);
     }
 }
-#endif

src/learn/convert.h

@@ -5,7 +5,6 @@
 #include <string>
 #include <sstream>
 
-#if defined(EVAL_LEARN)
 namespace Learner {
     void convert_bin_from_pgn_extract(
         const std::vector<std::string>& filenames,
@@ -32,6 +31,5 @@ namespace Learner {
 
     void convert(std::istringstream& is);
 }
-#endif
 
 #endif

src/learn/gensfen.cpp

@@ -1,6 +1,4 @@
-#if defined(EVAL_LEARN)
+#include "gensfen.h"
-
-#include "gensfen.h"
 
 #include "packed_sfen.h"
 #include "multi_think.h"
@@ -1207,4 +1205,3 @@ namespace Learner
         std::cout << "gensfen finished." << endl;
     }
 }
-#endif

src/learn/gensfen.h

@@ -5,12 +5,10 @@
 
 #include <sstream>
 
-#if defined(EVAL_LEARN)
 namespace Learner {
 
     // Automatic generation of teacher position
     void gen_sfen(Position& pos, std::istringstream& is);
 }
-#endif
 
 #endif

src/learn/learn.cpp

@@ -17,8 +17,6 @@
 // → I will not be involved in the engine because it is a problem that the GUI should assist.
 // etc..
 
-#if defined(EVAL_LEARN)
-
 #include "learn.h"
 
 #include "convert.h"
@@ -2048,5 +2046,3 @@ namespace Learner
     }
 
 } // namespace Learner
-
-#endif // EVAL_LEARN

src/learn/learn.h

@@ -1,8 +1,6 @@
 #ifndef _LEARN_H_
 #define _LEARN_H_
 
-#if defined(EVAL_LEARN)
-
 // ----------------------
 // Floating point for learning
 // ----------------------
@@ -78,6 +76,4 @@ namespace Learner
     void learn(Position& pos, std::istringstream& is);
 }
 
-#endif
-
 #endif // ifndef _LEARN_H_

src/learn/learning_tools.cpp

@@ -1,7 +1,5 @@
 #include "learning_tools.h"
 
-#if defined (EVAL_LEARN)
-
 #include "misc.h"
 
 using namespace Eval;
@@ -18,5 +16,3 @@ namespace EvalLearningTools
 	uint64_t Weight::eta1_epoch;
 	uint64_t Weight::eta2_epoch;
 }
-
-#endif

src/learn/learning_tools.h

@@ -3,8 +3,6 @@
 
 // A set of machine learning tools related to the weight array used for machine learning of evaluation functions
 
-#if defined (EVAL_LEARN)
-
 #include "learn.h"
 
 #include "misc.h"  // PRNG , my_insertion_sort
@@ -98,5 +96,4 @@ namespace EvalLearningTools
 	};
 }
 
-#endif // defined (EVAL_LEARN)
 #endif

src/learn/multi_think.cpp

@@ -1,6 +1,4 @@
-#if defined(EVAL_LEARN)
+#include "multi_think.h"
-
-#include "multi_think.h"
 
 #include "tt.h"
 #include "uci.h"
@@ -118,6 +116,3 @@ void MultiThink::go_think()
 		Options[s.first] = std::string(s.second);
 
 }
-
-
-#endif // defined(EVAL_LEARN)

src/learn/multi_think.h

@@ -1,8 +1,6 @@
 #ifndef _MULTI_THINK_
 #define _MULTI_THINK_
 
-#if defined(EVAL_LEARN)
-
 #include "learn.h"
 
 #include "misc.h"
@@ -151,6 +149,4 @@ protected:
 	std::mutex task_mutex;
 };
 
-#endif // defined(EVAL_LEARN) && defined(YANEURAOU_2018_OTAFUKU_ENGINE)
-
 #endif

src/learn/packed_sfen.h

@@ -4,7 +4,6 @@
 #include <vector>
 #include <cstdint>
 
-#if defined(EVAL_LEARN)
 namespace Learner {
 
     // packed sfen
@@ -45,5 +44,3 @@ namespace Learner {
     using PSVector = std::vector<PackedSfenValue>;
 }
 #endif
-
-#endif

src/learn/sfen_packer.cpp

@@ -1,6 +1,4 @@
-#if defined (EVAL_LEARN)
+#include "sfen_packer.h"
-
-#include "sfen_packer.h"
 
 #include "packed_sfen.h"
 
@@ -402,6 +400,3 @@ namespace Learner {
     return sfen;
   }
 }
-
-
-#endif // USE_SFEN_PACKER

src/learn/sfen_packer.h

@@ -1,8 +1,6 @@
 #ifndef _SFEN_PACKER_H_
 #define _SFEN_PACKER_H_
 
-#if defined(EVAL_LEARN)
-
 #include "types.h"
 
 #include "learn/packed_sfen.h"
@@ -20,5 +18,3 @@ namespace Learner {
 }
 
 #endif
-
-#endif

src/nnue/evaluate_nnue_learner.cpp

@@ -1,7 +1,5 @@
 // Code for learning NNUE evaluation function
 
-#if defined(EVAL_LEARN)
-
 #include <random>
 #include <fstream>
 #include <filesystem>
@@ -238,5 +236,3 @@ double get_eta() {
 }
 
 }  // namespace Eval
-
-#endif  // defined(EVAL_LEARN)

src/nnue/evaluate_nnue_learner.h

@@ -3,8 +3,6 @@
 #ifndef _EVALUATE_NNUE_LEARNER_H_
 #define _EVALUATE_NNUE_LEARNER_H_
 
-#if defined(EVAL_LEARN)
-
 #include "../learn/learn.h"
 
 namespace Eval {
@@ -41,6 +39,4 @@ void CheckHealth();
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_LEARN)
-
 #endif

src/nnue/trainer/trainer.h

@@ -3,8 +3,6 @@
 #ifndef _NNUE_TRAINER_H_
 #define _NNUE_TRAINER_H_
 
-#if defined(EVAL_LEARN)
-
 #include "../nnue_common.h"
 #include "../features/index_list.h"
 
@@ -120,6 +118,4 @@ std::shared_ptr<T> MakeAlignedSharedPtr(ArgumentTypes&&... arguments) {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_LEARN)
-
 #endif

src/nnue/trainer/trainer_affine_transform.h

@@ -3,8 +3,6 @@
 #ifndef _NNUE_TRAINER_AFFINE_TRANSFORM_H_
 #define _NNUE_TRAINER_AFFINE_TRANSFORM_H_
 
-#if defined(EVAL_LEARN)
-
 #include "../../learn/learn.h"
 #include "../layers/affine_transform.h"
 #include "trainer.h"
@@ -296,6 +294,4 @@ class Trainer<Layers::AffineTransform<PreviousLayer, OutputDimensions>> {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_LEARN)
-
 #endif

src/nnue/trainer/trainer_clipped_relu.h

@@ -3,8 +3,6 @@
 #ifndef _NNUE_TRAINER_CLIPPED_RELU_H_
 #define _NNUE_TRAINER_CLIPPED_RELU_H_
 
-#if defined(EVAL_LEARN)
-
 #include "../../learn/learn.h"
 #include "../layers/clipped_relu.h"
 #include "trainer.h"
@@ -137,6 +135,4 @@ class Trainer<Layers::ClippedReLU<PreviousLayer>> {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_LEARN)
-
 #endif

src/nnue/trainer/trainer_feature_transformer.h

@@ -3,8 +3,6 @@
 #ifndef _NNUE_TRAINER_FEATURE_TRANSFORMER_H_
 #define _NNUE_TRAINER_FEATURE_TRANSFORMER_H_
 
-#if defined(EVAL_LEARN)
-
 #include "../../learn/learn.h"
 #include "../nnue_feature_transformer.h"
 #include "trainer.h"
@@ -372,6 +370,4 @@ class Trainer<FeatureTransformer> {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_LEARN)
-
 #endif

src/nnue/trainer/trainer_input_slice.h

@@ -3,8 +3,6 @@
 #ifndef _NNUE_TRAINER_INPUT_SLICE_H_
 #define _NNUE_TRAINER_INPUT_SLICE_H_
 
-#if defined(EVAL_LEARN)
-
 #include "../../learn/learn.h"
 #include "../layers/input_slice.h"
 #include "trainer.h"
@@ -246,6 +244,4 @@ class Trainer<Layers::InputSlice<OutputDimensions, Offset>> {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_LEARN)
-
 #endif

src/nnue/trainer/trainer_sum.h

@@ -3,8 +3,6 @@
 #ifndef _NNUE_TRAINER_SUM_H_
 #define _NNUE_TRAINER_SUM_H_
 
-#if defined(EVAL_LEARN)
-
 #include "../../learn/learn.h"
 #include "../layers/sum.h"
 #include "trainer.h"
@@ -185,6 +183,4 @@ class Trainer<Layers::Sum<PreviousLayer>> {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_LEARN)
-
 #endif

src/position.cpp

@@ -32,10 +32,8 @@
 #include "uci.h"
 #include "syzygy/tbprobe.h"
 
-#if defined(EVAL_LEARN)
 #include "learn/packed_sfen.h"
 #include "learn/sfen_packer.h"
-#endif
 
 using std::string;
 
@@ -1352,8 +1350,6 @@ bool Position::pos_is_ok() const {
   return true;
 }
 
-#if defined(EVAL_LEARN)
-
 // Add a function that directly unpacks for speed. It's pretty tough.
 // Write it by combining packer::unpack() and Position::set().
 // If there is a problem with the passed phase and there is an error, non-zero is returned.
@@ -1385,5 +1381,3 @@ void Position::sfen_pack(Learner::PackedSfen& sfen)
 {
   sfen = Learner::sfen_pack(*this);
 }
-
-#endif

src/position.h

@@ -30,10 +30,8 @@
 
 #include "nnue/nnue_accumulator.h"
 
-#if defined(EVAL_LEARN)
 #include "learn/packed_sfen.h"
 #include "learn/sfen_packer.h"
-#endif
 
 
 /// StateInfo struct stores information needed to restore a Position object to
@@ -177,7 +175,6 @@ public:
   // Used by NNUE
   StateInfo* state() const;
 
-#if defined(EVAL_LEARN)
   // --sfenization helper
 
   friend int Learner::set_from_packed_sfen(Position& pos, const Learner::PackedSfen& sfen, StateInfo* si, Thread* th, bool mirror);
@@ -199,7 +196,6 @@ public:
 
   // Returns the position of the ball on the c side.
   Square king_square(Color c) const { return pieceList[make_piece(c, KING)][0]; }
-#endif // EVAL_LEARN
 
 private:
   // Initialization helpers (used while setting up a position)

src/search.cpp

@@ -54,9 +54,7 @@ using std::string;
 using Eval::evaluate;
 using namespace Search;
 
-#if defined(EVAL_LEARN)
 bool Search::prune_at_shallow_depth_on_pv_node = false;
-#endif
 
 namespace {
 
@@ -991,9 +989,7 @@ moves_loop: // When in check, search starts from here
       ss->moveCount = ++moveCount;
 
       if (rootNode && thisThread == Threads.main() && Time.elapsed() > 3000
-#if defined(EVAL_LEARN)
           && !Limits.silent
-#endif
           )
           sync_cout << "info depth " << depth
                     << " currmove " << UCI::move(move, pos.is_chess960())
@@ -1011,9 +1007,7 @@ moves_loop: // When in check, search starts from here
 
       // Step 12. Pruning at shallow depth (~200 Elo)
       if (  !rootNode
-#ifdef EVAL_LEARN
           && (PvNode ? prune_at_shallow_depth_on_pv_node : true)
-#endif
           && pos.non_pawn_material(us)
           && bestValue > VALUE_TB_LOSS_IN_MAX_PLY)
       {
@@ -1564,10 +1558,8 @@ moves_loop: // When in check, search starts from here
 
       // Check for legality just before making the move
       if (
-#if defined(EVAL_LEARN)
         // HACK: pos.piece_on(from_sq(m)) sometimes will be NO_PIECE during machine learning.
         !pos.pseudo_legal(move) ||
-#endif // EVAL_LEARN
         !pos.legal(move)
         )
       {
@@ -1978,7 +1970,6 @@ void Tablebases::rank_root_moves(Position& pos, Search::RootMoves& rootMoves) {
 
 // --- expose the functions such as fixed depth search used for learning to the outside
 
-#if defined (EVAL_LEARN)
 
 namespace Learner
 {
@@ -2278,4 +2269,3 @@ namespace Learner
   }
 
 }
-#endif

src/search.h

@@ -32,10 +32,7 @@ namespace Search {
 /// Threshold used for countermoves based pruning
 constexpr int CounterMovePruneThreshold = 0;
 
-
-#if defined(EVAL_LEARN)
 extern bool prune_at_shallow_depth_on_pv_node;
-#endif
 
 /// Stack struct keeps track of the information we need to remember from nodes
 /// shallower and deeper in the tree during the search. Each search thread has
@@ -90,9 +87,7 @@ struct LimitsType {
     time[WHITE] = time[BLACK] = inc[WHITE] = inc[BLACK] = npmsec = movetime = TimePoint(0);
     movestogo = depth = mate = perft = infinite = 0;
     nodes = 0;
-#if defined (EVAL_LEARN)
     silent = false;
-#endif
   }
 
   bool use_time_management() const {
@@ -103,11 +98,9 @@ struct LimitsType {
   TimePoint time[COLOR_NB], inc[COLOR_NB], npmsec, movetime, startTime;
   int movestogo, depth, mate, perft, infinite;
   int64_t nodes;
-#if defined (EVAL_LEARN)
   // Silent mode that does not output to the screen (for continuous self-play in process)
   // Do not output PV at this time.
   bool silent;
-#endif
 };
 
 extern LimitsType Limits;
@@ -117,7 +110,6 @@ void clear();
 
 } // namespace Search
 
-#if defined(EVAL_LEARN)
 namespace Learner {
 
   // A pair of reader and evaluation value. Returned by Learner::search(),Learner::qsearch().
@@ -126,6 +118,5 @@ namespace Learner {
   ValueAndPV qsearch(Position& pos);
   ValueAndPV search(Position& pos, int depth_, size_t multiPV = 1, uint64_t nodesLimit = 0);
 }
-#endif
 
 #endif // #ifndef SEARCH_H_INCLUDED

src/tt.cpp

@@ -28,9 +28,7 @@
 
 TranspositionTable TT; // Our global transposition table
 
-#ifdef EVAL_LEARN
 bool TranspositionTable::enable_transposition_table = true;
-#endif
 
 /// TTEntry::save() populates the TTEntry with a new node's data, possibly
 /// overwriting an old position. Update is not atomic and can be racy.
@@ -120,12 +118,10 @@ void TranspositionTable::clear() {
 
 TTEntry* TranspositionTable::probe(const Key key, bool& found) const {
 
-#ifdef EVAL_LEARN
   if (!enable_transposition_table) {
       found = false;
       return first_entry(0);
   }
-#endif
 
   TTEntry* const tte = first_entry(key);
   const uint16_t key16 = (uint16_t)key;  // Use the low 16 bits as key inside the cluster

src/tt.h

@@ -84,9 +84,7 @@ public:
     return &table[mul_hi64(key, clusterCount)].entry[0];
   }
 
-#ifdef EVAL_LEARN
   static bool enable_transposition_table;
-#endif
 
 private:
   friend struct TTEntry;

src/uci.cpp

@@ -245,7 +245,6 @@ double UCI::win_rate_model_double(double v, int ply) {
 // Call qsearch(),search() directly for testing
 // --------------------
 
-#if defined(EVAL_LEARN)
 void qsearch_cmd(Position& pos)
 {
   cout << "qsearch : ";
@@ -277,8 +276,6 @@ void search_cmd(Position& pos, istringstream& is)
   cout << endl;
 }
 
-#endif
-
 /// UCI::loop() waits for a command from stdin, parses it and calls the appropriate
 /// function. Also intercepts EOF from stdin to ensure gracefully exiting if the
 /// GUI dies unexpectedly. When called with some command line arguments, e.g. to
@@ -334,7 +331,7 @@ void UCI::loop(int argc, char* argv[]) {
       else if (token == "d")        sync_cout << pos << sync_endl;
       else if (token == "eval")     trace_eval(pos);
       else if (token == "compiler") sync_cout << compiler_info() << sync_endl;
-#if defined (EVAL_LEARN)
+
       else if (token == "gensfen") Learner::gen_sfen(pos, is);
       else if (token == "learn") Learner::learn(pos, is);
       else if (token == "convert") Learner::convert(is);
@@ -343,8 +340,6 @@ void UCI::loop(int argc, char* argv[]) {
       else if (token == "qsearch") qsearch_cmd(pos);
       else if (token == "search") search_cmd(pos, is);
 
-#endif
-
       // test command
       else if (token == "test") test_cmd(pos, is);
       else

src/ucioption.cpp

@@ -42,14 +42,12 @@ void on_threads(const Option& o) { Threads.set(size_t(o)); }
 void on_tb_path(const Option& o) { Tablebases::init(o); }
 void on_use_NNUE(const Option& ) { Eval::init_NNUE(); }
 void on_eval_file(const Option& ) { Eval::init_NNUE(); }
-#ifdef EVAL_LEARN
 void on_prune_at_shallow_depth_on_pv_node(const Option& o) {
     Search::prune_at_shallow_depth_on_pv_node = o;
 }
 void on_enable_transposition_table(const Option& o) {
     TranspositionTable::enable_transposition_table = o;
 }
-#endif
 
 /// Our case insensitive less() function as required by UCI protocol
 bool CaseInsensitiveLess::operator() (const string& s1, const string& s2) const {
@@ -86,11 +84,7 @@ void init(OptionsMap& o) {
   o["SyzygyProbeDepth"]      << Option(1, 1, 100);
   o["Syzygy50MoveRule"]      << Option(true);
   o["SyzygyProbeLimit"]      << Option(7, 0, 7);
-#if defined(EVAL_LEARN)
   o["Use NNUE"]              << Option("true var true var false var pure", "true", on_use_NNUE);
-#else
-  o["Use NNUE"]              << Option("true var true var false", "true", on_use_NNUE);
-#endif
   // The default must follow the format nn-[SHA256 first 12 digits].nnue
   // for the build process (profile-build and fishtest) to work.
   o["EvalFile"]              << Option("nn-82215d0fd0df.nnue", on_eval_file);
@@ -102,7 +96,6 @@ void init(OptionsMap& o) {
   o["SkipLoadingEval"]       << Option(false);
   // how many moves to use a fixed move
   // o["BookMoves"] << Option(16, 0, 10000);
-#if defined(EVAL_LEARN)
   // When learning the evaluation function, you can change the folder to save the evaluation function.
   // Evalsave by default. This folder shall be prepared in advance.
   // Automatically create a folder under this folder like "0/", "1/", ... and save the evaluation function file there.
@@ -111,7 +104,6 @@ void init(OptionsMap& o) {
   o["PruneAtShallowDepthOnPvNode"] << Option(false, on_prune_at_shallow_depth_on_pv_node);
   // Enable transposition table.
   o["EnableTranspositionTable"] << Option(true, on_enable_transposition_table);
-#endif
 }