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Update trace eval

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Updates the information printed in the "eval" command. Removes piece value estimation, and adds both small and big net eval information.

closes https://github.com/official-stockfish/Stockfish/pull/6743

No functional change
This commit is contained in:
sscg13
2026-04-19 07:10:20 +02:00
committed by Joost VandeVondele
parent c3bcf74925
commit de7b0cd7a6
2 changed files with 60 additions and 111 deletions
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src/evaluate.cpp
+24 -9
View File
@@ -107,16 +107,31 @@ std::string Eval::trace(Position& pos, const Eval::NNUE::Networks& networks) {
ss << std::showpoint << std::showpos << std::fixed << std::setprecision(2) << std::setw(15);
auto [psqt, positional] = networks.big.evaluate(pos, *accumulators, caches->big);
Value v = psqt + positional;
v = pos.side_to_move() == WHITE ? v : -v;
ss << "NNUE evaluation " << 0.01 * UCIEngine::to_cp(v, pos) << " (white side)\n";
auto [psqtSmall, positionalSmall] = networks.small.evaluate(pos, *accumulators, caches->small);
Value vSmall = psqtSmall + positionalSmall;
bool useBig = std::abs(vSmall) < 277;
ss << "(Small net) NNUE evaluation " << vSmall << " (side to move, internal units)\n";
vSmall = pos.side_to_move() == WHITE ? vSmall : -vSmall;
ss << "(Small net) NNUE evaluation " << 0.01 * UCIEngine::to_cp(vSmall, pos)
<< " (white side)\n";
v = evaluate(networks, pos, *accumulators, *caches, VALUE_ZERO);
v = pos.side_to_move() == WHITE ? v : -v;
ss << "Final evaluation " << 0.01 * UCIEngine::to_cp(v, pos) << " (white side)";
ss << " [with scaled NNUE, ...]";
ss << "\n";
auto [psqtBig, positionalBig] = networks.big.evaluate(pos, *accumulators, caches->big);
Value vBig = psqtBig + positionalBig;
ss << "(Big net) NNUE evaluation " << vBig << " (side to move, internal units)\n";
vBig = pos.side_to_move() == WHITE ? vBig : -vBig;
ss << "(Big net) NNUE evaluation " << 0.01 * UCIEngine::to_cp(vBig, pos)
<< " (white side)\n";
ss << "SimpleEval " << simple_eval(pos)
<< " (side to move, internal units)\n\n";
Value v = evaluate(networks, pos, *accumulators, *caches, VALUE_ZERO);
v = pos.side_to_move() == WHITE ? v : -v;
ss << "Final evaluation " << "(using "
<< (use_smallnet(pos) && !useBig ? "small net) " : "big net) ");
ss << 0.01 * UCIEngine::to_cp(v, pos) << " (white side)";
ss << " [with scaled NNUE, ...]\n";
return ss.str();
}
src/nnue/nnue_misc.cpp
+36 -102
View File
@@ -22,13 +22,10 @@
#include <cmath>
#include <cstdlib>
#include <cstring>
#include <iomanip>
#include <iosfwd>
#include <iostream>
#include <sstream>
#include <string_view>
#include <tuple>
#include "../position.h"
#include "../types.h"
@@ -39,45 +36,7 @@
namespace Stockfish::Eval::NNUE {
constexpr std::string_view PieceToChar(" PNBRQK pnbrqk");
namespace {
// Converts a Value into (centi)pawns and writes it in a buffer.
// The buffer must have capacity for at least 5 chars.
void format_cp_compact(Value v, char* buffer, const Position& pos) {
buffer[0] = (v < 0 ? '-' : v > 0 ? '+' : ' ');
int cp = std::abs(UCIEngine::to_cp(v, pos));
if (cp >= 10000)
{
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[3] = '.';
buffer[4] = '0' + cp / 10;
}
else
{
buffer[1] = '0' + cp / 100;
cp %= 100;
buffer[2] = '.';
buffer[3] = '0' + cp / 10;
cp %= 10;
buffer[4] = '0' + cp / 1;
}
}
// Converts a Value into pawns, always keeping two decimals
@@ -100,67 +59,13 @@ trace(Position& pos, const Eval::NNUE::Networks& networks, Eval::NNUE::Accumulat
std::stringstream ss;
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';
// A lambda to output one box of the board
auto writeSquare = [&board, &pos](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 (is_valid(value))
format_cp_compact(value, &board[y + 2][x + 2], pos);
};
auto accumulators = std::make_unique<AccumulatorStack>();
// 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.
auto [psqt, positional] = networks.big.evaluate(pos, *accumulators, caches.big);
Value base = psqt + positional;
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)
{
pos.remove_piece(sq);
accumulators->reset();
std::tie(psqt, positional) = networks.big.evaluate(pos, *accumulators, caches.big);
Value eval = psqt + positional;
eval = pos.side_to_move() == WHITE ? eval : -eval;
v = base - eval;
pos.put_piece(pc, sq);
}
writeSquare(f, r, pc, v);
}
ss << " NNUE derived piece values:\n";
for (int row = 0; row < 3 * 8 + 1; ++row)
ss << board[row] << '\n';
ss << '\n';
accumulators->reset();
auto t = networks.big.trace_evaluate(pos, *accumulators, caches.big);
auto tSmall = networks.small.trace_evaluate(pos, *accumulators, caches.small);
ss << " NNUE network contributions "
<< (pos.side_to_move() == WHITE ? "(White to move)" : "(Black to move)") << std::endl
ss << "(Small net) NNUE network contributions (Normalized, "
<< (pos.side_to_move() == WHITE ? "White to move)" : "Black to move)") << std::endl
<< "+------------+------------+------------+------------+\n"
<< "| Bucket | Material | Positional | Total |\n"
<< "| | (PSQT) | (Layers) | |\n"
@@ -170,16 +75,45 @@ trace(Position& pos, const Eval::NNUE::Networks& networks, Eval::NNUE::Accumulat
{
ss << "| " << bucket << " " //
<< " | ";
format_cp_aligned_dot(t.psqt[bucket], ss, pos);
format_cp_aligned_dot(tSmall.psqt[bucket], ss, pos);
ss << " " //
<< " | ";
format_cp_aligned_dot(t.positional[bucket], ss, pos);
format_cp_aligned_dot(tSmall.positional[bucket], ss, pos);
ss << " " //
<< " | ";
format_cp_aligned_dot(t.psqt[bucket] + t.positional[bucket], ss, pos);
format_cp_aligned_dot(tSmall.psqt[bucket] + tSmall.positional[bucket], ss, pos);
ss << " " //
<< " |";
if (bucket == t.correctBucket)
if (bucket == tSmall.correctBucket)
ss << " <-- this bucket is used";
ss << '\n';
}
ss << "+------------+------------+------------+------------+\n\n";
auto tBig = networks.big.trace_evaluate(pos, *accumulators, caches.big);
ss << "(Big net) NNUE network contributions (Normalized, "
<< (pos.side_to_move() == WHITE ? "White to move)" : "Black to move)") << std::endl
<< "+------------+------------+------------+------------+\n"
<< "| Bucket | Material | Positional | Total |\n"
<< "| | (PSQT) | (Layers) | |\n"
<< "+------------+------------+------------+------------+\n";
for (std::size_t bucket = 0; bucket < LayerStacks; ++bucket)
{
ss << "| " << bucket << " " //
<< " | ";
format_cp_aligned_dot(tBig.psqt[bucket], ss, pos);
ss << " " //
<< " | ";
format_cp_aligned_dot(tBig.positional[bucket], ss, pos);
ss << " " //
<< " | ";
format_cp_aligned_dot(tBig.psqt[bucket] + tBig.positional[bucket], ss, pos);
ss << " " //
<< " |";
if (bucket == tBig.correctBucket)
ss << " <-- this bucket is used";
ss << '\n';
}