// Code for calculating NNUE evaluation function
+#include "evaluate_nnue.h"
+
+#include <cmath>
+#include <cstdlib>
+#include <cstring>
#include <fstream>
#include <iomanip>
#include <iostream>
-#include <set>
#include <sstream>
#include <string_view>
#include "../evaluate.h"
+#include "../misc.h"
#include "../position.h"
-#include "../uci.h"
#include "../types.h"
-
-#include "evaluate_nnue.h"
+#include "../uci.h"
+#include "nnue_accumulator.h"
+#include "nnue_common.h"
namespace Stockfish::Eval::NNUE {
- // Input feature converter
- LargePagePtr<FeatureTransformer> featureTransformer;
+// Input feature converter
+LargePagePtr<FeatureTransformer> featureTransformer;
- // Evaluation function
- AlignedPtr<Network> network[LayerStacks];
+// Evaluation function
+AlignedPtr<Network> network[LayerStacks];
- // Evaluation function file name
- std::string fileName;
- std::string netDescription;
+// Evaluation function file name
+std::string fileName;
+std::string netDescription;
- namespace Detail {
+namespace Detail {
- // Initialize the evaluation function parameters
- template <typename T>
- void initialize(AlignedPtr<T>& pointer) {
+// Initialize the evaluation function parameters
+template<typename T>
+void initialize(AlignedPtr<T>& pointer) {
pointer.reset(reinterpret_cast<T*>(std_aligned_alloc(alignof(T), sizeof(T))));
std::memset(pointer.get(), 0, sizeof(T));
- }
+}
- template <typename T>
- void initialize(LargePagePtr<T>& pointer) {
+template<typename T>
+void initialize(LargePagePtr<T>& pointer) {
- static_assert(alignof(T) <= 4096, "aligned_large_pages_alloc() may fail for such a big alignment requirement of T");
+ static_assert(alignof(T) <= 4096,
+ "aligned_large_pages_alloc() may fail for such a big alignment requirement of T");
pointer.reset(reinterpret_cast<T*>(aligned_large_pages_alloc(sizeof(T))));
std::memset(pointer.get(), 0, sizeof(T));
- }
+}
- // Read evaluation function parameters
- template <typename T>
- bool read_parameters(std::istream& stream, T& reference) {
+// Read evaluation function parameters
+template<typename T>
+bool read_parameters(std::istream& stream, T& reference) {
std::uint32_t header;
header = read_little_endian<std::uint32_t>(stream);
- if (!stream || header != T::get_hash_value()) return false;
+ if (!stream || header != T::get_hash_value())
+ return false;
return reference.read_parameters(stream);
- }
+}
- // Write evaluation function parameters
- template <typename T>
- bool write_parameters(std::ostream& stream, const T& reference) {
+// Write evaluation function parameters
+template<typename T>
+bool write_parameters(std::ostream& stream, const T& reference) {
write_little_endian<std::uint32_t>(stream, T::get_hash_value());
return reference.write_parameters(stream);
- }
+}
+
+} // namespace Detail
- } // namespace Detail
- // Initialize the evaluation function parameters
- static void initialize() {
+// Initialize the evaluation function parameters
+static void initialize() {
Detail::initialize(featureTransformer);
for (std::size_t i = 0; i < LayerStacks; ++i)
- Detail::initialize(network[i]);
- }
+ Detail::initialize(network[i]);
+}
- // Read network header
- static bool read_header(std::istream& stream, std::uint32_t* hashValue, std::string* desc)
- {
+// Read network header
+static bool read_header(std::istream& stream, std::uint32_t* hashValue, std::string* desc) {
std::uint32_t version, size;
- version = read_little_endian<std::uint32_t>(stream);
- *hashValue = read_little_endian<std::uint32_t>(stream);
- size = read_little_endian<std::uint32_t>(stream);
- if (!stream || version != Version) return false;
+ version = read_little_endian<std::uint32_t>(stream);
+ *hashValue = read_little_endian<std::uint32_t>(stream);
+ size = read_little_endian<std::uint32_t>(stream);
+ if (!stream || version != Version)
+ return false;
desc->resize(size);
stream.read(&(*desc)[0], size);
return !stream.fail();
- }
+}
- // Write network header
- static bool write_header(std::ostream& stream, std::uint32_t hashValue, const std::string& desc)
- {
+// Write network header
+static bool write_header(std::ostream& stream, std::uint32_t hashValue, const std::string& desc) {
write_little_endian<std::uint32_t>(stream, Version);
write_little_endian<std::uint32_t>(stream, hashValue);
- write_little_endian<std::uint32_t>(stream, (std::uint32_t)desc.size());
+ write_little_endian<std::uint32_t>(stream, std::uint32_t(desc.size()));
stream.write(&desc[0], desc.size());
return !stream.fail();
- }
+}
- // Read network parameters
- static bool read_parameters(std::istream& stream) {
+// Read network parameters
+static bool read_parameters(std::istream& stream) {
std::uint32_t hashValue;
- if (!read_header(stream, &hashValue, &netDescription)) return false;
- if (hashValue != HashValue) return false;
- if (!Detail::read_parameters(stream, *featureTransformer)) return false;
+ if (!read_header(stream, &hashValue, &netDescription))
+ return false;
+ if (hashValue != HashValue)
+ return false;
+ if (!Detail::read_parameters(stream, *featureTransformer))
+ return false;
for (std::size_t i = 0; i < LayerStacks; ++i)
- if (!Detail::read_parameters(stream, *(network[i]))) return false;
+ if (!Detail::read_parameters(stream, *(network[i])))
+ return false;
return stream && stream.peek() == std::ios::traits_type::eof();
- }
+}
- // Write network parameters
- static bool write_parameters(std::ostream& stream) {
+// Write network parameters
+static bool write_parameters(std::ostream& stream) {
- if (!write_header(stream, HashValue, netDescription)) return false;
- if (!Detail::write_parameters(stream, *featureTransformer)) return false;
+ if (!write_header(stream, HashValue, netDescription))
+ return false;
+ if (!Detail::write_parameters(stream, *featureTransformer))
+ return false;
for (std::size_t i = 0; i < LayerStacks; ++i)
- if (!Detail::write_parameters(stream, *(network[i]))) return false;
- return (bool)stream;
- }
+ if (!Detail::write_parameters(stream, *(network[i])))
+ return false;
+ return bool(stream);
+}
- void hint_common_parent_position(const Position& pos) {
+void hint_common_parent_position(const Position& pos) {
featureTransformer->hint_common_access(pos);
- }
+}
- // Evaluation function. Perform differential calculation.
- Value evaluate(const Position& pos, bool adjusted, int* complexity) {
+// Evaluation function. Perform differential calculation.
+Value evaluate(const Position& pos, bool adjusted, int* complexity) {
// We manually align the arrays on the stack because with gcc < 9.3
// overaligning stack variables with alignas() doesn't work correctly.
constexpr uint64_t alignment = CacheLineSize;
- constexpr int delta = 24;
+ constexpr int delta = 24;
#if defined(ALIGNAS_ON_STACK_VARIABLES_BROKEN)
- TransformedFeatureType transformedFeaturesUnaligned[
- FeatureTransformer::BufferSize + alignment / sizeof(TransformedFeatureType)];
+ TransformedFeatureType
+ transformedFeaturesUnaligned[FeatureTransformer::BufferSize
+ + alignment / sizeof(TransformedFeatureType)];
auto* transformedFeatures = align_ptr_up<alignment>(&transformedFeaturesUnaligned[0]);
#else
- alignas(alignment)
- TransformedFeatureType transformedFeatures[FeatureTransformer::BufferSize];
+ alignas(alignment) TransformedFeatureType transformedFeatures[FeatureTransformer::BufferSize];
#endif
ASSERT_ALIGNED(transformedFeatures, alignment);
- const int
bucket = (pos.count<ALL_PIECES>() - 1) / 4;
- const auto psqt = featureTransformer->transform(pos, transformedFeatures, bucket);
+ const int
bucket = (pos.count<ALL_PIECES>() - 1) / 4;
+ const auto psqt = featureTransformer->transform(pos, transformedFeatures, bucket);
const auto positional = network[bucket]->propagate(transformedFeatures);
if (complexity)
- *complexity = abs(psqt - positional) / OutputScale;
+ *complexity = std::abs(psqt - positional) / OutputScale;
// Give more value to positional evaluation when adjusted flag is set
if (adjusted)
- return static_cast<Value>(((1024 - delta) * psqt + (1024 + delta) * positional) / (1024 * OutputScale));
+ return static_cast<Value>(((1024 - delta) * psqt + (1024 + delta) * positional)
+ / (1024 * OutputScale));
else
return static_cast<Value>((psqt + positional) / OutputScale);
- }
+}
- struct NnueEvalTrace {
+struct NnueEvalTrace {
static_assert(LayerStacks == PSQTBuckets);
- Value psqt[LayerStacks];
- Value positional[LayerStacks];
+ Value psqt[LayerStacks];
+ Value positional[LayerStacks];
std::size_t correctBucket;
- };
+};
- static NnueEvalTrace trace_evaluate(const Position& pos) {
+static NnueEvalTrace trace_evaluate(const Position& pos) {
// We manually align the arrays on the stack because with gcc < 9.3
// overaligning stack variables with alignas() doesn't work correctly.
-
constexpr uint64_t alignment = CacheLineSize;
#if defined(ALIGNAS_ON_STACK_VARIABLES_BROKEN)
- TransformedFeatureType transformedFeaturesUnaligned[
- FeatureTransformer::BufferSize + alignment / sizeof(TransformedFeatureType)];
+ TransformedFeatureType
+ transformedFeaturesUnaligned[FeatureTransformer::BufferSize
+ + alignment / sizeof(TransformedFeatureType)];
auto* transformedFeatures = align_ptr_up<alignment>(&transformedFeaturesUnaligned[0]);
#else
- alignas(alignment)
- TransformedFeatureType transformedFeatures[FeatureTransformer::BufferSize];
+ alignas(alignment) TransformedFeatureType transformedFeatures[FeatureTransformer::BufferSize];
#endif
ASSERT_ALIGNED(transformedFeatures, alignment);
NnueEvalTrace t{};
t.correctBucket = (pos.count<ALL_PIECES>() - 1) / 4;
- for (IndexType bucket = 0; bucket < LayerStacks; ++bucket) {
- const auto materialist = featureTransformer->transform(pos, transformedFeatures, bucket);
- const auto positional = network[bucket]->propagate(transformedFeatures);
+ for (IndexType bucket = 0; bucket < LayerStacks; ++bucket)
+ {
+ const auto materialist = featureTransformer->transform(pos, transformedFeatures, bucket);
+ const auto positional = network[bucket]->propagate(transformedFeatures);
- t.psqt[bucket] = static_cast<Value>( materialist / OutputScale );
- t.positional[bucket] = static_cast<Value>( positional / OutputScale );
+ t.psqt[bucket] = static_cast<Value>(materialist / OutputScale);
+ t.positional[bucket] = static_cast<Value>(positional / OutputScale);
}
return t;
- }
+}
- constexpr std::string_view PieceToChar(" PNBRQK pnbrqk");
+constexpr std::string_view PieceToChar(" PNBRQK pnbrqk");
- // format_cp_compact() converts a Value into (centi)pawns and writes it in a buffer.
- // The buffer must have capacity for at least 5 chars.
- static void format_cp_compact(Value v, char* buffer) {
+// Converts a Value into (centi)pawns and writes it in a buffer.
+// The buffer must have capacity for at least 5 chars.
+static void format_cp_compact(Value v, char* buffer) {
buffer[0] = (v < 0 ? '-' : v > 0 ? '+' : ' ');
- int cp = std::abs(100 * v / UCI::NormalizeToPawnValue);
+ int cp = std::abs(UCI::to_cp(v));
if (cp >= 10000)
{
- buffer[1] = '0' + cp / 10000; cp %= 10000;
- buffer[2] = '0' + cp / 1000; cp %= 1000;
+ buffer[1] = '0' + cp / 10000;
+ cp %= 10000;
+ buffer[2] = '0' + cp / 1000;
+ cp %= 1000;
buffer[3] = '0' + cp / 100;
buffer[4] = ' ';
}
else if (cp >= 1000)
{
- buffer[1] = '0' + cp / 1000; cp %= 1000;
- buffer[2] = '0' + cp / 100; cp %= 100;
+ buffer[1] = '0' + cp / 1000;
+ cp %= 1000;
+ buffer[2] = '0' + cp / 100;
+ cp %= 100;
buffer[3] = '.';
buffer[4] = '0' + cp / 10;
}
else
{
- buffer[1] = '0' + cp / 100; cp %= 100;
+ buffer[1] = '0' + cp / 100;
+ cp %= 100;
buffer[2] = '.';
- buffer[3] = '0' + cp / 10; cp %= 10;
+ buffer[3] = '0' + cp / 10;
+ cp %= 10;
buffer[4] = '0' + cp / 1;
}
- }
+}
- // format_cp_aligned_dot() converts a Value into (centi)pawns, always keeping two decimals.
- static void format_cp_aligned_dot(Value v, std::stringstream &stream) {
- const double cp = 1.0 * std::abs(int(v)) / UCI::NormalizeToPawnValue;
+// Converts a Value into pawns, always keeping two decimals
+static void format_cp_aligned_dot(Value v, std::stringstream& stream) {
- stream << (v < 0 ? '-' : v > 0 ? '+' : ' ')
- << std::setiosflags(std::ios::fixed)
- << std::setw(6)
- << std::setprecision(2)
- << cp;
- }
+ const double pawns = std::abs(0.01 * UCI::to_cp(v));
+ stream << (v < 0 ? '-'
+ : v > 0 ? '+'
+ : ' ')
+ << std::setiosflags(std::ios::fixed) << std::setw(6) << std::setprecision(2) << pawns;
+}
- // trace() returns a string with the value of each piece on a board,
- // and a table for (PSQT, Layers) values bucket by bucket.
- std::string trace(Position& pos) {
+// Returns a string with the value of each piece on a board,
+// and a table for (PSQT, Layers) values bucket by bucket.
+std::string trace(Position& pos) {
std::stringstream ss;
- char board[3*8+1][8*8+2];
+ char board[3 * 8 + 1][8 * 8 + 2];
std::memset(board, ' ', sizeof(board));
- for (int row = 0; row < 3*8+1; ++row)
- board[row][8*8+1] = '\0';
+ for (int row = 0; row < 3 * 8 + 1; ++row)
+ board[row][8 * 8 + 1] = '\0';
// A lambda to output one box of the board
auto writeSquare = [&board](File file, Rank rank, Piece pc, Value value) {
-
- const int x = ((int)file) * 8;
- const int y = (7 - (int)rank) * 3;
- for (int i = 1; i < 8; ++i)
- board[y][x+i] = board[y+3][x+i] = '-';
- for (int i = 1; i < 3; ++i)
- board[y+i][x] = board[y+i][x+8] = '|';
- board[y][x] = board[y][x+8] = board[y+3][x+8] = board[y+3][x] = '+';
- if (pc != NO_PIECE)
- board[y+1][x+4] = PieceToChar[pc];
- if (value != VALUE_NONE)
- format_cp_compact(value, &board[y+2][x+2]);
+ const int x = int(file) * 8;
+ const int y = (7 - int(rank)) * 3;
+ for (int i = 1; i < 8; ++i)
+ board[y][x + i] = board[y + 3][x + i] = '-';
+ for (int i = 1; i < 3; ++i)
+ board[y + i][x] = board[y + i][x + 8] = '|';
+ board[y][x] = board[y][x + 8] = board[y + 3][x + 8] = board[y + 3][x] = '+';
+ if (pc != NO_PIECE)
+ board[y + 1][x + 4] = PieceToChar[pc];
+ if (value != VALUE_NONE)
+ format_cp_compact(value, &board[y + 2][x + 2]);
};
// We estimate the value of each piece by doing a differential evaluation from
// the current base eval, simulating the removal of the piece from its square.
Value base = evaluate(pos);
- base = pos.side_to_move() == WHITE ? base : -base;
+ base = pos.side_to_move() == WHITE ? base : -base;
for (File f = FILE_A; f <= FILE_H; ++f)
- for (Rank r = RANK_1; r <= RANK_8; ++r)
- {
- Square sq = make_square(f, r);
- Piece pc = pos.piece_on(sq);
- Value v = VALUE_NONE;
-
- if (pc != NO_PIECE && type_of(pc) != KING)
+ for (Rank r = RANK_1; r <= RANK_8; ++r)
{
- auto st = pos.state();
+ Square sq = make_square(f, r);
+ Piece pc = pos.piece_on(sq);
+ Value v = VALUE_NONE;
- pos.remove_piece(sq);
- st->accumulator.computed[WHITE] = false;
- st->accumulator.computed[BLACK] = false;
+ if (pc != NO_PIECE && type_of(pc) != KING)
+ {
+ auto st = pos.state();
- Value eval = evaluate(pos);
- eval = pos.side_to_move() == WHITE ? eval : -eval;
- v = base - eval;
+ pos.remove_piece(sq);
+ st->accumulator.computed[WHITE] = false;
+ st->accumulator.computed[BLACK] = false;
- pos.put_piece(pc, sq);
- st->accumulator.computed[WHITE] = false;
- st->accumulator.computed[BLACK] = false;
- }
+ Value eval = evaluate(pos);
+ eval = pos.side_to_move() == WHITE ? eval : -eval;
+ v = base - eval;
+
+ pos.put_piece(pc, sq);
+ st->accumulator.computed[WHITE] = false;
+ st->accumulator.computed[BLACK] = false;
+ }
- writeSquare(f, r, pc, v);
- }
+ writeSquare(f, r, pc, v);
+ }
ss << " NNUE derived piece values:\n";
- for (int row = 0; row < 3*8+1; ++row)
+ for (int row = 0; row < 3 * 8 + 1; ++row)
ss << board[row] << '\n';
ss << '\n';
for (std::size_t bucket = 0; bucket < LayerStacks; ++bucket)
{
- ss << "| " << bucket << " ";
- ss << " | "; format_cp_aligned_dot(t.psqt[bucket], ss); ss << " "
- << " | "; format_cp_aligned_dot(t.positional[bucket], ss); ss << " "
- << " | "; format_cp_aligned_dot(t.psqt[bucket] + t.positional[bucket], ss); ss << " "
- << " |";
- if (bucket == t.correctBucket)
- ss << " <-- this bucket is used";
- ss << '\n';
+ ss << "| " << bucket << " ";
+ ss << " | ";
+ format_cp_aligned_dot(t.psqt[bucket], ss);
+ ss << " "
+ << " | ";
+ format_cp_aligned_dot(t.positional[bucket], ss);
+ ss << " "
+ << " | ";
+ format_cp_aligned_dot(t.psqt[bucket] + t.positional[bucket], ss);
+ ss << " "
+ << " |";
+ if (bucket == t.correctBucket)
+ ss << " <-- this bucket is used";
+ ss << '\n';
}
ss << "+------------+------------+------------+------------+\n";
return ss.str();
- }
+}
- // Load eval, from a file stream or a memory stream
- bool load_eval(std::string name, std::istream& stream) {
+// Load eval, from a file stream or a memory stream
+bool load_eval(std::string name, std::istream& stream) {
initialize();
fileName = name;
return read_parameters(stream);
- }
+}
- // Save eval, to a file stream or a memory stream
- bool save_eval(std::ostream& stream) {
+// Save eval, to a file stream or a memory stream
+bool save_eval(std::ostream& stream) {
if (fileName.empty())
- return false;
+ return false;
return write_parameters(stream);
- }
+}
- /// Save eval, to a file given by its name
- bool save_eval(const std::optional<std::string>& filename) {
+// Save eval, to a file given by its name
+bool save_eval(const std::optional<std::string>& filename) {
std::string actualFilename;
std::string msg;
{
if (currentEvalFileName != EvalFileDefaultName)
{
- msg = "Failed to export a net. A non-embedded net can only be saved if the filename is specified";
+ msg = "Failed to export a net. "
+ "A non-embedded net can only be saved if the filename is specified";
- sync_cout << msg << sync_endl;
- return false;
+ sync_cout << msg << sync_endl;
+ return false;
}
actualFilename = EvalFileDefaultName;
}
std::ofstream stream(actualFilename, std::ios_base::binary);
- bool saved = save_eval(stream);
+ bool saved = save_eval(stream);
- msg = saved ? "Network saved successfully to " + actualFilename
- : "Failed to export a net";
+ msg = saved ? "Network saved successfully to " + actualFilename : "Failed to export a net";
sync_cout << msg << sync_endl;
return saved;
- }
+}
-} // namespace Stockfish::Eval::NNUE
+} // namespace Stockfish::Eval::NNUE
projects / stockfish / blobdiff