| defaultScenario {irace} | R Documentation |
Default scenario settings
Description
Return scenario object with default values.
Usage
defaultScenario(scenario = list(), params_def = .irace.params.def)
Arguments
scenario |
( |
params_def |
( |
Value
A list indexed by the irace parameter names, containing the default values for each parameter, except for those already present in the scenario passed as argument. The scenario list contains the following elements:
General options:
scenarioFilePath of the file that describes the configuration scenario setup and other irace settings. (Default:
"./scenario.txt")execDirDirectory where the programs will be run. (Default:
"./")logFileFile to save tuning results as an R dataset, either absolute path or relative to execDir. (Default:
"./irace.Rdata")quietReduce the output generated by irace to a minimum. (Default:
0)debugLevelDebug level of the output of
irace. Set this to 0 to silence all debug messages. Higher values provide more verbose debug messages. (Default:0)seedSeed of the random number generator (by default, generate a random seed). (Default:
NA)repairConfigurationUser-defined R function that takes a configuration generated by irace and repairs it. (Default:
"")postselectionPercentage of the configuration budget used to perform a postselection race of the best configurations of each iteration after the execution of irace. (Default:
0)aclibEnable/disable AClib mode. This option enables compatibility with GenericWrapper4AC as targetRunner script. (Default:
0)
Elitist
irace:elitistEnable/disable elitist irace. (Default:
1)elitistNewInstancesNumber of instances added to the execution list before previous instances in elitist irace. (Default:
1)elitistLimitIn elitist irace, maximum number per race of elimination tests that do not eliminate a configuration. Use 0 for no limit. (Default:
2)
Internal
iraceoptions:sampleInstancesRandomly sample the training instances or use them in the order given. (Default:
1)softRestartEnable/disable the soft restart strategy that avoids premature convergence of the probabilistic model. (Default:
1)softRestartThresholdSoft restart threshold value for numerical parameters. If
NA,NULLor"", it is computed as10^-digits. (Default:"")nbIterationsMaximum number of iterations. (Default:
0)nbExperimentsPerIterationNumber of runs of the target algorithm per iteration. (Default:
0)minNbSurvivalMinimum number of configurations needed to continue the execution of each race (iteration). (Default:
0)nbConfigurationsNumber of configurations to be sampled and evaluated at each iteration. (Default:
0)muParameter used to define the number of configurations sampled and evaluated at each iteration. (Default:
5)
Target algorithm parameters:
parameterFileFile that contains the description of the parameters of the target algorithm. (Default:
"./parameters.txt")forbiddenExpsVector of R logical expressions that cannot evaluate to
TRUEfor any evaluated configuration. (Default:"")forbiddenFileFile that contains a list of logical expressions that cannot be
TRUEfor any evaluated configuration. If empty orNULL, do not use forbidden expressions. (Default:"")digitsMaximum number of decimal places that are significant for numerical (real) parameters. (Default:
4)
Target algorithm execution:
targetRunnerExecutable called for each configuration that executes the target algorithm to be tuned. See the templates and examples provided. (Default:
"./target-runner")targetRunnerLauncherExecutable that will be used to launch the target runner, when
targetRunnercannot be executed directly (.e.g, a Python script in Windows). (Default:"")targetRunnerLauncherArgsCommand-line arguments provided to
targetRunnerLauncher. The substrings{targetRunner}and{targetRunnerArgs}will be replaced by the value of the optiontargetRunnerand by the arguments usually passed when callingtargetRunner, respectively. Example:"-m {targetRunner} --args {targetRunnerArgs}". (Default:"{targetRunner} {targetRunnerArgs}")targetRunnerRetriesNumber of times to retry a call to
targetRunnerif the call failed. (Default:0)targetRunnerDataOptional data passed to
targetRunner. This is ignored by the defaulttargetRunnerfunction, but it may be used by customtargetRunnerfunctions to pass persistent data around. (Default:"")targetRunnerParallelOptional R function to provide custom parallelization of
targetRunner. (Default:"")targetEvaluatorOptional script or R function that provides a numeric value for each configuration. See templates/target-evaluator.tmpl (Default:
"")deterministicIf the target algorithm is deterministic, configurations will be evaluated only once per instance. (Default:
0)parallelNumber of calls to
targetRunnerto execute in parallel. Values0or1mean no parallelization. (Default:0)loadBalancingEnable/disable load-balancing when executing experiments in parallel. Load-balancing makes better use of computing resources, but increases communication overhead. If this overhead is large, disabling load-balancing may be faster. (Default:
1)mpiEnable/disable MPI. Use
Rmpito executetargetRunnerin parallel (parameterparallelis the number of slaves). (Default:0)batchmodeSpecify how irace waits for jobs to finish when
targetRunnersubmits jobs to a batch cluster: sge, pbs, torque, slurm or htcondor.targetRunnermust submit jobs to the cluster using, for example,qsub. (Default:0)
Initial configurations:
initConfigurationsData frame describing initial configurations (usually read from a file using
readConfigurations). (Default:"")configurationsFileFile that contains a table of initial configurations. If empty or
NULL, all initial configurations are randomly generated. (Default:"")
Training instances:
instancesCharacter vector of the instances to be used in the
targetRunner. (Default:"")trainInstancesDirDirectory where training instances are located; either absolute path or relative to current directory. If no
trainInstancesFilesis provided, all the files intrainInstancesDirwill be listed as instances. (Default:"./Instances")trainInstancesFileFile that contains a list of training instances and optionally additional parameters for them. If
trainInstancesDiris provided,iracewill search for the files in this folder. (Default:"")
Tuning budget:
maxExperimentsMaximum number of runs (invocations of
targetRunner) that will be performed. It determines the maximum budget of experiments for the tuning. (Default:0)maxTimeMaximum total execution time in seconds for the executions of
targetRunner.targetRunnermust return two values: cost and time. (Default:0)budgetEstimationFraction (smaller than 1) of the budget used to estimate the mean computation time of a configuration. Only used when
maxTime> 0 (Default:0.02)minMeasurableTimeMinimum time unit that is still (significantly) measureable. (Default:
0.01)
Statistical test:
testTypeStatistical test used for elimination. The default value selects
t-testifcappingis enabled orF-test, otherwise. Valid values are: F-test (Friedman test), t-test (pairwise t-tests with no correction), t-test-bonferroni (t-test with Bonferroni's correction for multiple comparisons), t-test-holm (t-test with Holm's correction for multiple comparisons). (Default:"")firstTestNumber of instances evaluated before the first elimination test. It must be a multiple of
eachTest. (Default:5)eachTestNumber of instances evaluated between elimination tests. (Default:
1)confidenceConfidence level for the elimination test. (Default:
0.95)
Adaptive capping:
cappingEnable the use of adaptive capping, a technique designed for minimizing the computation time of configurations. This is only available when
elitistis active. (Default:0)cappingTypeMeasure used to obtain the execution bound from the performance of the elite configurations.
median: Median performance of the elite configurations.
mean: Mean performance of the elite configurations.
best: Best performance of the elite configurations.
worst: Worst performance of the elite configurations.
(Default:
"median")boundTypeMethod to calculate the mean performance of elite configurations.
candidate: Mean execution times across the executed instances and the current one.
instance: Execution time of the current instance.
(Default:
"candidate")boundMaxMaximum execution bound for
targetRunner. It must be specified when capping is enabled. (Default:0)boundDigitsPrecision used for calculating the execution time. It must be specified when capping is enabled. (Default:
0)boundParPenalization constant for timed out executions (executions that reach
boundMaxexecution time). (Default:1)boundAsTimeoutReplace the configuration cost of bounded executions with
boundMax. (Default:1)
Recovery:
recoveryFilePreviously saved log file to recover the execution of
irace, either absolute path or relative to the current directory. If empty orNULL, recovery is not performed. (Default:"")
Testing:
testInstancesDirDirectory where testing instances are located, either absolute or relative to current directory. (Default:
"")testInstancesFileFile containing a list of test instances and optionally additional parameters for them. (Default:
"")testInstancesCharacter vector of the instances to be used in the
targetRunnerwhen executing the testing. (Default:"")testNbElitesNumber of elite configurations returned by irace that will be tested if test instances are provided. (Default:
1)testIterationElitesEnable/disable testing the elite configurations found at each iteration. (Default:
0)
Author(s)
Manuel López-Ibáñez and Jérémie Dubois-Lacoste
See Also
readScenario()for reading a configuration scenario from a file.
printScenario()prints the given scenario.
defaultScenario()returns the default scenario settings of irace.
checkScenario()to check that the scenario is valid.