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/* | ||
This file is part of Leela Chess Zero. | ||
Copyright (C) 2018 The LCZero Authors | ||
Leela Chess 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. | ||
Leela Chess 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 Leela Chess. If not, see <http://www.gnu.org/licenses/>. | ||
*/ | ||
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#include "analyzer/analyzer.h" | ||
#include "analyzer/table.h" | ||
#include "mcts/search.h" | ||
#include "neural/factory.h" | ||
#include "neural/loader.h" | ||
#include "utils/optionsparser.h" | ||
#include "utils/string.h" | ||
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#include <algorithm> | ||
#include <cmath> | ||
#include <iostream> | ||
#include <sstream> | ||
#include <string> | ||
#include <vector> | ||
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namespace lczero { | ||
namespace { | ||
const char* kTsvReportStr = "Filename of the tab-separated report file"; | ||
const char* kTxtReportStr = "Filename of the text report file"; | ||
const char* kMovesStr = "Moves in UCI format, space separated"; | ||
const char* kMovesToAnalyzeStr = "Number of (last) moves to analyze"; | ||
const char* kNodesStr = "(comma separated) How many nodes to calculate"; | ||
const char* kTrainExamplesStr = | ||
"How many examples of training data to generate"; | ||
const char* kWeightsStr = "Network weights file path"; | ||
const char* kNnBackendStr = "NN backend to use"; | ||
const char* kNnBackendOptionsStr = "NN backend parameters"; | ||
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const char* kAutoDiscover = "<autodiscover>"; | ||
} // namespace | ||
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Analyzer::Analyzer() { | ||
options_parser_.AddContext("play"); | ||
options_parser_.AddContext("training"); | ||
play_options_ = &options_parser_.GetOptionsDict("play"); | ||
play_options_ = &options_parser_.GetOptionsDict("training"); | ||
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options_parser_.Add<StringOption>(kTsvReportStr, "tsv-report"); | ||
options_parser_.Add<StringOption>(kTxtReportStr, "txt-report"); | ||
options_parser_.Add<StringOption>(kMovesStr, "moves"); | ||
options_parser_.Add<IntOption>(kMovesToAnalyzeStr, 1, 999, "num-moves") = 4; | ||
options_parser_.Add<StringOption>(kNodesStr, "nodes-list") = | ||
"10,50,100,200,400,600,800,1200,1600,5000,10000"; | ||
options_parser_.Add<IntOption>(kTrainExamplesStr, 1, 999, | ||
"training-examples") = 10; | ||
options_parser_.Add<StringOption>(kWeightsStr, "weights", 'w') = | ||
kAutoDiscover; | ||
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// TODO(mooskagh) Move all that to network factory. | ||
const auto backends = NetworkFactory::Get()->GetBackendsList(); | ||
options_parser_.Add<ChoiceOption>(kNnBackendStr, backends, "backend") = | ||
backends.empty() ? "<none>" : backends[0]; | ||
options_parser_.Add<StringOption>(kNnBackendOptionsStr, "backend-opts"); | ||
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Search::PopulateUciParams(&options_parser_); | ||
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// Overriding default options of search. | ||
auto defaults = options_parser_.GetMutableDefaultsOptions(); | ||
defaults->Set<int>(Search::kMiniBatchSizeStr, 1); // Minibatch = 1 | ||
defaults->Set<bool>(Search::kSmartPruningStr, false); // No smart pruning | ||
defaults->Set<bool>(Search::kVerboseStatsStr, true); // Verbose stats | ||
} | ||
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void Analyzer::GatherStats(Table3d* table, const Node* root_node, | ||
std::string& col, bool flip) { | ||
uint64_t total_n = 0; | ||
float factor = play_options_->Get<float>(Search::kCpuctStr) * | ||
std::sqrt(std::max(root_node->GetN(), 1u)); | ||
const float parent_q = | ||
-root_node->GetQ(0) - play_options_->Get<float>(Search::kFpuReductionStr); | ||
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for (Node* node : root_node->Children()) { | ||
const auto n = node->GetNStarted(); | ||
total_n += n; | ||
const auto u = factor * node->GetU(); | ||
const auto q = node->GetQ(parent_q); | ||
const auto move = node->GetMove(flip).as_string(); | ||
table->Add3dVal(col, move, "N", std::to_string(n)); | ||
table->Add3dVal(col, move, "U", std::to_string(u)); | ||
table->Add3dVal(col, move, "Q", std::to_string(q)); | ||
table->Add3dVal(col, move, "U+Q", std::to_string(u + q)); | ||
} | ||
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for (Node* node : root_node->Children()) { | ||
auto n = node->GetNStarted(); | ||
table->Add3dVal(col, node->GetMove(flip).as_string(), "N%", | ||
std::to_string(static_cast<double>(n) / total_n)); | ||
} | ||
} | ||
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void Analyzer::RunOnePosition(const std::vector<Move>& moves) { | ||
NNCache cache(200000); | ||
NodeTree tree; | ||
tree.ResetToPosition(ChessBoard::kStartingFen, moves); | ||
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auto nodeses = ParseIntList(play_options_->Get<std::string>(kNodesStr)); | ||
std::sort(nodeses.begin(), nodeses.end()); | ||
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Table3d table; | ||
std::vector<std::string> cols; | ||
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// Run search in increasing number of nodes. | ||
for (int nodes : nodeses) { | ||
WriteToLog("Nodes: " + std::to_string(nodes)); | ||
SearchLimits limits; | ||
limits.visits = nodes; | ||
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Search search(tree, network_.get(), | ||
std::bind(&Analyzer::OnBestMove, this, std::placeholders::_1), | ||
std::bind(&Analyzer::OnInfo, this, std::placeholders::_1), | ||
limits, *play_options_, &cache); | ||
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search.RunBlocking(1); | ||
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auto col = std::to_string(nodes); | ||
cols.push_back(col); | ||
GatherStats(&table, tree.GetCurrentHead(), col, tree.IsBlackToMove()); | ||
table.AddColVal(col, "bestmove", search.GetBestMove().first.as_string()); | ||
} | ||
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// Fetch MCTS-agnostic per-move stats P and V. | ||
std::vector<const Node*> nodes; | ||
for (Node* iter : tree.GetCurrentHead()->Children()) { | ||
nodes.emplace_back(iter); | ||
} | ||
std::sort(nodes.begin(), nodes.end(), [](const Node* a, const Node* b) { | ||
return a->GetNStarted() > b->GetNStarted(); | ||
}); | ||
std::vector<std::string> rows; | ||
for (const Node* node : nodes) { | ||
auto move = node->GetMove(tree.IsBlackToMove()).as_string(); | ||
rows.push_back(move); | ||
table.AddRowVal(move, "P", std::to_string(node->GetP())); | ||
table.AddRowVal(move, "V", std::to_string(node->GetV())); | ||
} | ||
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// Dump table to log. | ||
auto lines = table.RenderTable(cols, rows, {"N", "N%", "U", "Q", "U+Q"}, | ||
{"P", "V"}, {"bestmove"}); | ||
for (const auto& line : lines) WriteToTsvLog(line); | ||
} | ||
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void Analyzer::Run() { | ||
if (!options_parser_.ProcessAllFlags()) return; | ||
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// Open log files. | ||
if (!play_options_->Get<std::string>(kTxtReportStr).empty()) { | ||
log_.open(play_options_->Get<std::string>(kTxtReportStr).c_str()); | ||
} | ||
if (!play_options_->Get<std::string>(kTsvReportStr).empty()) { | ||
tsvlog_.open(play_options_->Get<std::string>(kTsvReportStr).c_str()); | ||
} | ||
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// Load network | ||
InitializeNetwork(); | ||
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// Parse moves. | ||
std::vector<std::string> moves_str = | ||
StrSplitAtWhitespace(play_options_->Get<std::string>(kMovesStr)); | ||
std::vector<Move> moves; | ||
for (const auto& move : moves_str) moves.emplace_back(move); | ||
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for (int i = 0; i < play_options_->Get<int>(kMovesToAnalyzeStr); ++i) { | ||
// Write position to logs. | ||
std::string initial_pos; | ||
if (moves_str.empty()) { | ||
WriteToLog("Position: startpos"); | ||
WriteToTsvLog({"Startpos."}); | ||
} else { | ||
WriteToLog("Position: moves " + StrJoin(moves_str)); | ||
WriteToTsvLog({"Moves " + StrJoin(moves_str)}); | ||
} | ||
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// Run Mcts at different depths. | ||
RunOnePosition(moves); | ||
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// Run training several times. | ||
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if (moves.empty()) break; | ||
moves.pop_back(); | ||
moves_str.pop_back(); | ||
WriteToTsvLog({}); | ||
} | ||
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// DumpFlags(); | ||
} | ||
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void Analyzer::InitializeNetwork() { | ||
std::string network_path = play_options_->Get<std::string>(kWeightsStr); | ||
std::string backend = play_options_->Get<std::string>(kNnBackendStr); | ||
std::string backend_options = | ||
play_options_->Get<std::string>(kNnBackendOptionsStr); | ||
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std::string net_path = network_path; | ||
if (net_path == kAutoDiscover) { | ||
net_path = DiscoveryWeightsFile(); | ||
} | ||
Weights weights = LoadWeightsFromFile(net_path); | ||
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OptionsDict network_options = OptionsDict::FromString( | ||
backend_options, &options_parser_.GetOptionsDict()); | ||
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network_ = NetworkFactory::Get()->Create(backend, weights, network_options); | ||
} | ||
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void Analyzer::WriteToLog(const std::string& line) const { | ||
std::cout << line << std::endl; | ||
if (log_) log_ << line << std::endl; | ||
} | ||
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void Analyzer::WriteToTsvLog(const std::vector<std::string>& line) const { | ||
if (!tsvlog_) return; | ||
bool first = true; | ||
for (const auto& chunk : line) { | ||
if (first) { | ||
first = false; | ||
} else { | ||
tsvlog_ << "\t"; | ||
} | ||
tsvlog_ << chunk; | ||
} | ||
tsvlog_ << std::endl; | ||
} | ||
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void Analyzer::OnBestMove(const BestMoveInfo& move) const { | ||
WriteToLog("BestMove: " + move.bestmove.as_string()); | ||
} | ||
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void Analyzer::OnInfo(const ThinkingInfo& info) const { | ||
std::string res = "Info"; | ||
if (info.depth >= 0) res += " depth " + std::to_string(info.depth); | ||
if (info.seldepth >= 0) res += " seldepth " + std::to_string(info.seldepth); | ||
if (info.time >= 0) res += " time " + std::to_string(info.time); | ||
if (info.nodes >= 0) res += " nodes " + std::to_string(info.nodes); | ||
if (info.score) res += " score cp " + std::to_string(*info.score); | ||
if (info.nps >= 0) res += " nps " + std::to_string(info.nps); | ||
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if (!info.pv.empty()) { | ||
res += " pv"; | ||
for (const auto& move : info.pv) res += " " + move.as_string(); | ||
} | ||
if (!info.comment.empty()) res += " string " + info.comment; | ||
WriteToLog(res); | ||
} | ||
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} // namespace lczero |
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Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,56 @@ | ||
/* | ||
This file is part of Leela Chess Zero. | ||
Copyright (C) 2018 The LCZero Authors | ||
Leela Chess 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. | ||
Leela Chess 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 Leela Chess. If not, see <http://www.gnu.org/licenses/>. | ||
*/ | ||
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#pragma once | ||
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#include <fstream> | ||
#include "analyzer/table.h" | ||
#include "chess/board.h" | ||
#include "chess/callbacks.h" | ||
#include "mcts/node.h" | ||
#include "neural/network.h" | ||
#include "utils/optionsparser.h" | ||
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namespace lczero { | ||
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class Analyzer { | ||
public: | ||
Analyzer(); | ||
void Run(); | ||
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private: | ||
void RunOnePosition(const std::vector<Move>& position); | ||
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void WriteToLog(const std::string& line) const; | ||
void WriteToTsvLog(const std::vector<std::string>& line) const; | ||
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void InitializeNetwork(); | ||
void OnBestMove(const BestMoveInfo& move) const; | ||
void OnInfo(const ThinkingInfo& info) const; | ||
void GatherStats(Table3d* table, const Node* root_node, std::string& col, | ||
bool flip); | ||
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std::unique_ptr<Network> network_; | ||
OptionsParser options_parser_; | ||
const OptionsDict* play_options_; | ||
// const OptionsDict* training_options_; | ||
mutable std::ofstream log_; | ||
mutable std::ofstream tsvlog_; | ||
}; | ||
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} // namespace lczero |
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