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Add std:: qualifier to move() calls

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This commit is contained in:
Marenz
2022-08-30 11:12:15 +02:00
parent 19e3c7339e
commit f7cc29bec1
111 changed files with 362 additions and 362 deletions
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tools/yulPhaser/Chromosome.cpp
+1 -1
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@@ -43,7 +43,7 @@ Chromosome Chromosome::makeRandom(size_t _length)
for (size_t i = 0; i < _length; ++i)
steps.push_back(randomOptimisationStep());
return Chromosome(move(steps));
return Chromosome(std::move(steps));
}
ostream& phaser::operator<<(ostream& _stream, Chromosome const& _chromosome)
tools/yulPhaser/GeneticAlgorithms.cpp
+1 -1
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@@ -71,7 +71,7 @@ Population RandomAlgorithm::runNextRound(Population _population)
size_t replacementCount = _population.individuals().size() - elitePopulation.individuals().size();
return
move(elitePopulation) +
std::move(elitePopulation) +
Population::makeRandom(
_population.fitnessMetric(),
replacementCount,
tools/yulPhaser/Mutations.cpp
+4 -4
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@@ -44,7 +44,7 @@ function<Mutation> phaser::geneRandomisation(double _chance)
gene
);
return Chromosome(move(genes));
return Chromosome(std::move(genes));
};
}
@@ -57,7 +57,7 @@ function<Mutation> phaser::geneDeletion(double _chance)
if (!SimulationRNG::bernoulliTrial(_chance))
genes.push_back(gene);
return Chromosome(move(genes));
return Chromosome(std::move(genes));
};
}
@@ -77,7 +77,7 @@ function<Mutation> phaser::geneAddition(double _chance)
genes.push_back(Chromosome::randomGene());
}
return Chromosome(move(genes));
return Chromosome(std::move(genes));
};
}
@@ -102,7 +102,7 @@ function<Mutation> phaser::mutationSequence(vector<function<Mutation>> _mutation
{
Chromosome mutatedChromosome = _chromosome;
for (size_t i = 0; i < _mutations.size(); ++i)
mutatedChromosome = _mutations[i](move(mutatedChromosome));
mutatedChromosome = _mutations[i](std::move(mutatedChromosome));
return mutatedChromosome;
};
tools/yulPhaser/PairSelections.h
+1 -1
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@@ -107,7 +107,7 @@ class PairMosaicSelection: public PairSelection
{
public:
explicit PairMosaicSelection(std::vector<std::tuple<size_t, size_t>> _pattern, double _selectionSize = 1.0):
m_pattern(move(_pattern)),
m_pattern(std::move(_pattern)),
m_selectionSize(_selectionSize)
{
assert(m_pattern.size() > 0 || _selectionSize == 0.0);
tools/yulPhaser/Phaser.cpp
+19 -19
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@@ -239,8 +239,8 @@ unique_ptr<FitnessMetric> FitnessMetricFactory::build(
{
for (size_t i = 0; i < _programs.size(); ++i)
metrics.push_back(make_unique<ProgramSize>(
_programCaches[i] != nullptr ? optional<Program>{} : move(_programs[i]),
move(_programCaches[i]),
_programCaches[i] != nullptr ? optional<Program>{} : std::move(_programs[i]),
std::move(_programCaches[i]),
_weights,
_options.chromosomeRepetitions
));
@@ -251,8 +251,8 @@ unique_ptr<FitnessMetric> FitnessMetricFactory::build(
{
for (size_t i = 0; i < _programs.size(); ++i)
metrics.push_back(make_unique<RelativeProgramSize>(
_programCaches[i] != nullptr ? optional<Program>{} : move(_programs[i]),
move(_programCaches[i]),
_programCaches[i] != nullptr ? optional<Program>{} : std::move(_programs[i]),
std::move(_programCaches[i]),
_options.relativeMetricScale,
_weights,
_options.chromosomeRepetitions
@@ -266,13 +266,13 @@ unique_ptr<FitnessMetric> FitnessMetricFactory::build(
switch (_options.metricAggregator)
{
case MetricAggregatorChoice::Average:
return make_unique<FitnessMetricAverage>(move(metrics));
return make_unique<FitnessMetricAverage>(std::move(metrics));
case MetricAggregatorChoice::Sum:
return make_unique<FitnessMetricSum>(move(metrics));
return make_unique<FitnessMetricSum>(std::move(metrics));
case MetricAggregatorChoice::Maximum:
return make_unique<FitnessMetricMaximum>(move(metrics));
return make_unique<FitnessMetricMaximum>(std::move(metrics));
case MetricAggregatorChoice::Minimum:
return make_unique<FitnessMetricMinimum>(move(metrics));
return make_unique<FitnessMetricMinimum>(std::move(metrics));
default:
assertThrow(false, solidity::util::Exception, "Invalid MetricAggregatorChoice value.");
}
@@ -309,7 +309,7 @@ Population PopulationFactory::build(
for (size_t populationSize: _options.randomPopulation)
combinedSize += populationSize;
population = move(population) + buildRandom(
population = std::move(population) + buildRandom(
combinedSize,
_options.minChromosomeLength,
_options.maxChromosomeLength,
@@ -317,7 +317,7 @@ Population PopulationFactory::build(
);
for (string const& populationFilePath: _options.populationFromFile)
population = move(population) + buildFromFile(populationFilePath, _fitnessMetric);
population = std::move(population) + buildFromFile(populationFilePath, _fitnessMetric);
return population;
}
@@ -331,7 +331,7 @@ Population PopulationFactory::buildFromStrings(
for (string const& geneSequence: _geneSequences)
chromosomes.emplace_back(geneSequence);
return Population(move(_fitnessMetric), move(chromosomes));
return Population(std::move(_fitnessMetric), std::move(chromosomes));
}
Population PopulationFactory::buildRandom(
@@ -342,7 +342,7 @@ Population PopulationFactory::buildRandom(
)
{
return Population::makeRandom(
move(_fitnessMetric),
std::move(_fitnessMetric),
_populationSize,
_minChromosomeLength,
_maxChromosomeLength
@@ -354,7 +354,7 @@ Population PopulationFactory::buildFromFile(
shared_ptr<FitnessMetric> _fitnessMetric
)
{
return buildFromStrings(readLinesFromFile(_filePath), move(_fitnessMetric));
return buildFromStrings(readLinesFromFile(_filePath), std::move(_fitnessMetric));
}
ProgramCacheFactory::Options ProgramCacheFactory::Options::fromCommandLine(po::variables_map const& _arguments)
@@ -371,7 +371,7 @@ vector<shared_ptr<ProgramCache>> ProgramCacheFactory::build(
{
vector<shared_ptr<ProgramCache>> programCaches;
for (Program& program: _programs)
programCaches.push_back(_options.programCacheEnabled ? make_shared<ProgramCache>(move(program)) : nullptr);
programCaches.push_back(_options.programCacheEnabled ? make_shared<ProgramCache>(std::move(program)) : nullptr);
return programCaches;
}
@@ -400,7 +400,7 @@ vector<Program> ProgramFactory::build(Options const& _options)
}
get<Program>(programOrErrors).optimise(Chromosome(_options.prefix).optimisationSteps());
inputPrograms.push_back(move(get<Program>(programOrErrors)));
inputPrograms.push_back(std::move(get<Program>(programOrErrors)));
}
return inputPrograms;
@@ -823,12 +823,12 @@ void Phaser::runPhaser(po::variables_map const& _arguments)
programCaches,
codeWeights
);
Population population = PopulationFactory::build(populationOptions, move(fitnessMetric));
Population population = PopulationFactory::build(populationOptions, std::move(fitnessMetric));
if (_arguments["mode"].as<PhaserMode>() == PhaserMode::RunAlgorithm)
runAlgorithm(_arguments, move(population), move(programCaches));
runAlgorithm(_arguments, std::move(population), std::move(programCaches));
else
printOptimisedProgramsOrASTs(_arguments, population, move(programs), _arguments["mode"].as<PhaserMode>());
printOptimisedProgramsOrASTs(_arguments, population, std::move(programs), _arguments["mode"].as<PhaserMode>());
}
void Phaser::runAlgorithm(
@@ -844,7 +844,7 @@ void Phaser::runAlgorithm(
_population.individuals().size()
);
AlgorithmRunner algorithmRunner(move(_population), move(_programCaches), buildAlgorithmRunnerOptions(_arguments), cout);
AlgorithmRunner algorithmRunner(std::move(_population), std::move(_programCaches), buildAlgorithmRunnerOptions(_arguments), cout);
algorithmRunner.run(*geneticAlgorithm);
}
tools/yulPhaser/Population.cpp
+7 -7
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@@ -68,7 +68,7 @@ Population Population::makeRandom(
for (size_t i = 0; i < _size; ++i)
chromosomes.push_back(Chromosome::makeRandom(_chromosomeLengthGenerator()));
return Population(move(_fitnessMetric), move(chromosomes));
return Population(std::move(_fitnessMetric), std::move(chromosomes));
}
Population Population::makeRandom(
@@ -79,7 +79,7 @@ Population Population::makeRandom(
)
{
return makeRandom(
move(_fitnessMetric),
std::move(_fitnessMetric),
_size,
std::bind(uniformChromosomeLength, _minChromosomeLength, _maxChromosomeLength)
);
@@ -112,7 +112,7 @@ Population Population::crossover(PairSelection const& _selection, function<Cross
m_individuals[i].chromosome,
m_individuals[j].chromosome
);
crossedIndividuals.emplace_back(move(childChromosome), *m_fitnessMetric);
crossedIndividuals.emplace_back(std::move(childChromosome), *m_fitnessMetric);
}
return Population(m_fitnessMetric, crossedIndividuals);
@@ -132,8 +132,8 @@ tuple<Population, Population> Population::symmetricCrossoverWithRemainder(
m_individuals[i].chromosome,
m_individuals[j].chromosome
);
crossedIndividuals.emplace_back(move(get<0>(children)), *m_fitnessMetric);
crossedIndividuals.emplace_back(move(get<1>(children)), *m_fitnessMetric);
crossedIndividuals.emplace_back(std::move(get<0>(children)), *m_fitnessMetric);
crossedIndividuals.emplace_back(std::move(get<1>(children)), *m_fitnessMetric);
indexSelected[i] = true;
indexSelected[j] = true;
}
@@ -159,7 +159,7 @@ Population operator+(Population _a, Population _b)
assert(_a.m_fitnessMetric == _b.m_fitnessMetric);
using ::operator+; // Import the std::vector concat operator from CommonData.h
return Population(_a.m_fitnessMetric, move(_a.m_individuals) + move(_b.m_individuals));
return Population(_a.m_fitnessMetric, std::move(_a.m_individuals) + std::move(_b.m_individuals));
}
}
@@ -193,7 +193,7 @@ vector<Individual> Population::chromosomesToIndividuals(
{
vector<Individual> individuals;
for (auto& chromosome: _chromosomes)
individuals.emplace_back(move(chromosome), _fitnessMetric);
individuals.emplace_back(std::move(chromosome), _fitnessMetric);
return individuals;
}
tools/yulPhaser/Program.cpp
+3 -3
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@@ -102,7 +102,7 @@ variant<Program, ErrorList> Program::load(CharStream& _sourceCode)
void Program::optimise(vector<string> const& _optimisationSteps)
{
m_ast = applyOptimisationSteps(m_dialect, m_nameDispenser, move(m_ast), _optimisationSteps);
m_ast = applyOptimisationSteps(m_dialect, m_nameDispenser, std::move(m_ast), _optimisationSteps);
}
ostream& phaser::operator<<(ostream& _stream, Program const& _program)
@@ -153,7 +153,7 @@ variant<unique_ptr<Block>, ErrorList> Program::parseObject(Dialect const& _diale
// to refactor ObjectParser and Object to use unique_ptr instead).
auto astCopy = make_unique<Block>(get<Block>(ASTCopier{}(*selectedObject->code)));
return variant<unique_ptr<Block>, ErrorList>(move(astCopy));
return variant<unique_ptr<Block>, ErrorList>(std::move(astCopy));
}
variant<unique_ptr<AsmAnalysisInfo>, ErrorList> Program::analyzeAST(Dialect const& _dialect, Block const& _ast)
@@ -168,7 +168,7 @@ variant<unique_ptr<AsmAnalysisInfo>, ErrorList> Program::analyzeAST(Dialect cons
return errors;
assert(errorReporter.errors().empty());
return variant<unique_ptr<AsmAnalysisInfo>, ErrorList>(move(analysisInfo));
return variant<unique_ptr<AsmAnalysisInfo>, ErrorList>(std::move(analysisInfo));
}
unique_ptr<Block> Program::disambiguateAST(
tools/yulPhaser/Selections.h
+1 -1
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@@ -86,7 +86,7 @@ class MosaicSelection: public Selection
{
public:
explicit MosaicSelection(std::vector<size_t> _pattern, double _selectionSize = 1.0):
m_pattern(move(_pattern)),
m_pattern(std::move(_pattern)),
m_selectionSize(_selectionSize)
{
assert(m_pattern.size() > 0 || _selectionSize == 0.0);