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Move declarations around and split them.

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This commit is contained in:
Tomasz Sobczyk
2020-09-11 12:05:46 +02:00
committed by nodchip
parent c6f5f6a082
commit 683c6146ce
14 changed files with 511 additions and 424 deletions
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3
src/learn/convert.cpp
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@@ -1,9 +1,10 @@
#if defined(EVAL_LEARN)
#include "convert.h"
// evaluate header for learning
#include "../eval/evaluate_common.h"
#include "learn.h"
#include "multi_think.h"
#include "../uci.h"
#include "../syzygy/tbprobe.h"

37
src/learn/convert.h Normal file
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@@ -0,0 +1,37 @@
#ifndef _CONVERT_H_
#define _CONVERT_H_
#include <vector>
#include <string>
#include <sstream>
#if defined(EVAL_LEARN)
namespace Learner {
void convert_bin_from_pgn_extract(
const std::vector<std::string>& filenames,
const std::string& output_file_name,
const bool pgn_eval_side_to_move,
const bool convert_no_eval_fens_as_score_zero);
void convert_bin(
const std::vector<std::string>& filenames,
const std::string& output_file_name,
const int ply_minimum,
const int ply_maximum,
const int interpolate_eval,
const int src_score_min_value,
const int src_score_max_value,
const int dest_score_min_value,
const int dest_score_max_value,
const bool check_invalid_fen,
const bool check_illegal_move);
void convert_plain(
const std::vector<std::string>& filenames,
const std::string& output_file_name);
void convert(std::istringstream& is);
}
#endif
#endif

4
src/learn/gensfen.cpp
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@@ -1,5 +1,8 @@
#if defined(EVAL_LEARN)
#include "gensfen.h"
#include "packed_sfen.h"
#include "../eval/evaluate_common.h"
#include "../misc.h"
#include "../nnue/evaluate_nnue_learner.h"
@@ -8,7 +11,6 @@
#include "../thread.h"
#include "../tt.h"
#include "../uci.h"
#include "learn.h"
#include "multi_think.h"
#include "../extra/nnue_data_binpack_format.h"

16
src/learn/gensfen.h Normal file
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@@ -0,0 +1,16 @@
#ifndef _GENSFEN_H_
#define _GENSFEN_H_
#include <sstream>
#include "../position.h"
#if defined(EVAL_LEARN)
namespace Learner {
// Automatic generation of teacher position
void gen_sfen(Position& pos, std::istringstream& is);
}
#endif
#endif

5
src/learn/learner.cpp → src/learn/learn.cpp
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@@ -19,6 +19,9 @@
#if defined(EVAL_LEARN)
#include "learn.h"
#include "convert.h"
#include "../eval/evaluate_common.h"
#include "../misc.h"
#include "../nnue/evaluate_nnue_learner.h"
@@ -27,7 +30,7 @@
#include "../thread.h"
#include "../tt.h"
#include "../uci.h"
#include "learn.h"
#include "../search.h"
#include "multi_think.h"
#include "../extra/nnue_data_binpack_format.h"

118
src/learn/learn.h
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@@ -14,7 +14,7 @@
// Even if it is a double type, there is almost no difference in the way of convergence, so fix it to float.
// when using float
typedef float LearnFloatType;
using LearnFloatType = float;
// when using double
//typedef double LearnFloatType;
@@ -36,105 +36,47 @@ typedef float LearnFloatType;
// ----------------------
// Definition of struct used in Learner
// ----------------------
#include "packed_sfen.h"
#include "../position.h"
#include <sstream>
namespace Learner
{
// ----------------------
// Settings for learning
// ----------------------
// ----------------------
// Settings for learning
// ----------------------
// mini-batch size.
// Calculate the gradient by combining this number of phases.
// If you make it smaller, the number of update_weights() will increase and the convergence will be faster. The gradient is incorrect.
// If you increase it, the number of update_weights() decreases, so the convergence will be slow. The slope will come out accurately.
// I don't think you need to change this value in most cases.
// mini-batch size.
// Calculate the gradient by combining this number of phases.
// If you make it smaller, the number of update_weights() will increase and the convergence will be faster. The gradient is incorrect.
// If you increase it, the number of update_weights() decreases, so the convergence will be slow. The slope will come out accurately.
// I don't think you need to change this value in most cases.
constexpr std::size_t LEARN_MINI_BATCH_SIZE = 1000 * 1000 * 1;
constexpr std::size_t LEARN_MINI_BATCH_SIZE = 1000 * 1000 * 1;
// The number of phases to read from the file at one time. After reading this much, shuffle.
// It is better to have a certain size, but this number x 40 bytes x 3 times as much memory is consumed. 400MB*3 is consumed in the 10M phase.
// Must be a multiple of THREAD_BUFFER_SIZE(=10000).
// The number of phases to read from the file at one time. After reading this much, shuffle.
// It is better to have a certain size, but this number x 40 bytes x 3 times as much memory is consumed. 400MB*3 is consumed in the 10M phase.
// Must be a multiple of THREAD_BUFFER_SIZE(=10000).
constexpr std::size_t LEARN_SFEN_READ_SIZE = 1000 * 1000 * 10;
constexpr std::size_t LEARN_SFEN_READ_SIZE = 1000 * 1000 * 10;
// Saving interval of evaluation function at learning. Save each time you learn this number of phases.
// Needless to say, the longer the saving interval, the shorter the learning time.
// Folder name is incremented for each save like 0/, 1/, 2/...
// By default, once every 1 billion phases.
constexpr std::size_t LEARN_EVAL_SAVE_INTERVAL = 1000000000ULL;
// Saving interval of evaluation function at learning. Save each time you learn this number of phases.
// Needless to say, the longer the saving interval, the shorter the learning time.
// Folder name is incremented for each save like 0/, 1/, 2/...
// By default, once every 1 billion phases.
constexpr std::size_t LEARN_EVAL_SAVE_INTERVAL = 1000000000ULL;
// Reduce the output of rmse during learning to 1 for this number of times.
// rmse calculation is done in one thread, so it takes some time, so reducing the output is effective.
constexpr std::size_t LEARN_RMSE_OUTPUT_INTERVAL = 1;
// Reduce the output of rmse during learning to 1 for this number of times.
// rmse calculation is done in one thread, so it takes some time, so reducing the output is effective.
constexpr std::size_t LEARN_RMSE_OUTPUT_INTERVAL = 1;
//Structure in which PackedSfen and evaluation value are integrated
// If you write different contents for each option, it will be a problem when reusing the teacher game
// For the time being, write all the following members regardless of the options.
struct PackedSfenValue
{
// phase
PackedSfen sfen;
double calc_grad(Value shallow, const PackedSfenValue& psv);
// Evaluation value returned from Learner::search()
int16_t score;
// PV first move
// Used when finding the match rate with the teacher
uint16_t move;
// Trouble of the phase from the initial phase.
uint16_t gamePly;
// 1 if the player on this side ultimately wins the game. -1 if you are losing.
// 0 if a draw is reached.
// The draw is in the teacher position generation command gensfen,
// Only write if LEARN_GENSFEN_DRAW_RESULT is enabled.
int8_t game_result;
// When exchanging the file that wrote the teacher aspect with other people
//Because this structure size is not fixed, pad it so that it is 40 bytes in any environment.
uint8_t padding;
// 32 + 2 + 2 + 2 + 1 + 1 = 40bytes
};
// Type that returns the reading line and the evaluation value at that time
// Used in Learner::search(), Learner::qsearch().
typedef std::pair<Value, std::vector<Move> > ValueAndPV;
// Phase array: PSVector stands for packed sfen vector.
typedef std::vector<PackedSfenValue> PSVector;
// So far, only Yaneura King 2018 Otafuku has this stub
// This stub is required if EVAL_LEARN is defined.
extern Learner::ValueAndPV search(Position& pos, int depth , size_t multiPV = 1 , uint64_t NodesLimit = 0);
extern Learner::ValueAndPV qsearch(Position& pos);
double calc_grad(Value shallow, const PackedSfenValue& psv);
void convert_bin_from_pgn_extract(
const std::vector<std::string>& filenames,
const std::string& output_file_name,
const bool pgn_eval_side_to_move,
const bool convert_no_eval_fens_as_score_zero);
void convert_bin(
const std::vector<std::string>& filenames,
const std::string& output_file_name,
const int ply_minimum,
const int ply_maximum,
const int interpolate_eval,
const int src_score_min_value,
const int src_score_max_value,
const int dest_score_min_value,
const int dest_score_max_value,
const bool check_invalid_fen,
const bool check_illegal_move);
void convert_plain(
const std::vector<std::string>& filenames,
const std::string& output_file_name);
// Learning from the generated game record
void learn(Position& pos, std::istringstream& is);
}
#endif

49
src/learn/packed_sfen.h Normal file
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@@ -0,0 +1,49 @@
#ifndef _PACKED_SFEN_H_
#define _PACKED_SFEN_H_
#include <vector>
#include <cstdint>
#if defined(EVAL_LEARN)
namespace Learner {
// packed sfen
struct PackedSfen { std::uint8_t data[32]; };
// Structure in which PackedSfen and evaluation value are integrated
// If you write different contents for each option, it will be a problem when reusing the teacher game
// For the time being, write all the following members regardless of the options.
struct PackedSfenValue
{
// phase
PackedSfen sfen;
// Evaluation value returned from Learner::search()
std::int16_t score;
// PV first move
// Used when finding the match rate with the teacher
std::uint16_t move;
// Trouble of the phase from the initial phase.
std::uint16_t gamePly;
// 1 if the player on this side ultimately wins the game. -1 if you are losing.
// 0 if a draw is reached.
// The draw is in the teacher position generation command gensfen,
// Only write if LEARN_GENSFEN_DRAW_RESULT is enabled.
std::int8_t game_result;
// When exchanging the file that wrote the teacher aspect with other people
//Because this structure size is not fixed, pad it so that it is 40 bytes in any environment.
std::uint8_t padding;
// 32 + 2 + 2 + 2 + 1 + 1 = 40bytes
};
// Phase array: PSVector stands for packed sfen vector.
using PSVector = std::vector<PackedSfenValue>;
}
#endif
#endif