def test():
appList = []
for line in open('filelist.txt'):
appList.append(str(line.rsplit('\n')[0]))
for app in appList:
globalvars.appName = "app" + str(appList.index(app) + 69)
globalvars.pinballLoc = str(app)
globalvars.outputDirBase = "/home/gangwan2/workdir1/cs446/outputs/"+globalvars.appName+"/"
baseConfig = tuple([96, 64, 256, 4, 512])
featureGeneration.extract([baseConfig], [featureNames],
globalvars.outputDirBase, True)
def parallelDetailed(appName, pinballLoc, outputDirBase):
# log the output of the process to a specific file
sys.stdout = open(outputDirBase+"plog.out", "w")
appfeatures = list(list())
#append the names of the features
appfeatures.append(featureNames)
goodConfigs = goodConfigDict[appName]
# now that we have the good configs, we need to launch sniper runs again for
# these configs with detailed stat (counter-data) collection enabled
#print('++Detailed-Run++')
launcher.run(goodConfigs, parameterNames, True, False, pinballLoc, outputDirBase)
# from the detailed runs, we now extract the feature vectors - this forms the
# training data. Feature vectors are logged to a file
#print('++Extraction++')
featureGeneration.extract(goodConfigs, appfeatures, outputDirBase)