def __init__(self, task_queue, result_queue, cfr, timeQueue, index,
outputFileParentName, num_consumers, s, metrics_variables,
metrics_objective_direction, consumerConstraints):
multiprocessing.Process.__init__(self)
self.task_queue = task_queue
self.result_queue = result_queue
self.timeQueue = timeQueue
self.cfr = cfr
self.solver = s
self.consumerConstraints = consumerConstraints
self.index = index
self.num_consumers = num_consumers
self.ParetoFront = []
self.clock = Clock()
self.GIAOptions = GuidedImprovementAlgorithmOptions(verbosity=0, \
incrementallyWriteLog=False, \
writeTotalTimeFilename="timefile.csv", \
writeRandomSeedsFilename="randomseed.csv", useCallLogs=False)
self.GIAAlgorithm = GuidedImprovementAlgorithm(self.cfr, self.solver, metrics_variables, \
metrics_objective_direction, [], options=self.GIAOptions)
def GIA(self, desired_number_of_models):
metrics_objective_direction = []
metrics_variables = []
for i in self.objectives:
(pol, var) = i
metrics_objective_direction.append(pol)
metrics_variables.append(var)
# Non-Parallel
GIAOptionsNP = GuidedImprovementAlgorithmOptions(verbosity=0, \
incrementallyWriteLog=False, \
writeTotalTimeFilename="timefile.csv", \
writeRandomSeedsFilename="randomseed.csv", useCallLogs=False, num_models=desired_number_of_models, magnifying_glass=Options.MAGNIFYING_GLASS)
if Options.CORES == 1:
GIAAlgorithmNP = GuidedImprovementAlgorithm(self, self.solver, metrics_variables, \
metrics_objective_direction, [], options=GIAOptionsNP)
'''featurevars instead of []'''
outfilename = str("giaoutput").strip()
ParetoFront = GIAAlgorithmNP.ExecuteGuidedImprovementAlgorithm(outfilename)
if not Options.SUPPRESS_MODELS:
if not ParetoFront:
standard_print("UNSAT")
for i in ParetoFront:
self.printVars(i)
return ParetoFront
else:
parSolver = ParSolver.ParSolver(self, self.module, self.solver, metrics_variables, metrics_objective_direction)
ParetoFront = parSolver.run()
for i in ParetoFront:
self.printStartDelimeter()
standard_print(i)
standard_print("")
self.printEndDelimeter()
return ParetoFront
def __init__(self, task_queue, result_queue, cfr, timeQueue, index, outputFileParentName, num_consumers, s, metrics_variables, metrics_objective_direction, consumerConstraints):
multiprocessing.Process.__init__(self)
self.task_queue = task_queue
self.result_queue = result_queue
self.timeQueue = timeQueue
self.cfr = cfr
self.solver = s
self.consumerConstraints = consumerConstraints
self.index = index
self.num_consumers = num_consumers
self.ParetoFront = []
self.clock = Clock()
self.GIAOptions = GuidedImprovementAlgorithmOptions(verbosity=0, \
incrementallyWriteLog=False, \
writeTotalTimeFilename="timefile.csv", \
writeRandomSeedsFilename="randomseed.csv", useCallLogs=False)
self.GIAAlgorithm = GuidedImprovementAlgorithm(self.cfr, self.solver, metrics_variables, \
metrics_objective_direction, [], options=self.GIAOptions)
class GIAConsumer(multiprocessing.Process):
def __init__(self, task_queue, result_queue, cfr, timeQueue, index,
outputFileParentName, num_consumers, s, metrics_variables,
metrics_objective_direction, consumerConstraints):
multiprocessing.Process.__init__(self)
self.task_queue = task_queue
self.result_queue = result_queue
self.timeQueue = timeQueue
self.cfr = cfr
self.solver = s
self.consumerConstraints = consumerConstraints
self.index = index
self.num_consumers = num_consumers
self.ParetoFront = []
self.clock = Clock()
self.GIAOptions = GuidedImprovementAlgorithmOptions(verbosity=0, \
incrementallyWriteLog=False, \
writeTotalTimeFilename="timefile.csv", \
writeRandomSeedsFilename="randomseed.csv", useCallLogs=False)
self.GIAAlgorithm = GuidedImprovementAlgorithm(self.cfr, self.solver, metrics_variables, \
metrics_objective_direction, [], options=self.GIAOptions)
def addParetoPoints(self, point):
self.ParetoFront.append(point)
def run(self):
num_solutions = 0
self.clock.tick("Consumer " + str(self.index))
while True:
next_task = self.task_queue.get()
try:
if next_task == "Poison" or (num_solutions
== Options.NUM_INSTANCES):
self.task_queue.task_done()
break
except:
pass
self.solver.push()
self.solver.add(self.consumerConstraints[int(next_task)])
self.consumerConstraints[int(next_task)]
self.clock.tick("Task " + str(next_task))
total_sat_calls = 0
total_unsat_time = 0
while True:
if self.GIAAlgorithm.s.check(
) != Common.SAT or num_solutions == Options.NUM_INSTANCES:
self.clock.tock("Task " + str(next_task))
self.task_queue.task_done()
self.solver.pop()
break
else:
prev_solution = self.GIAAlgorithm.s.model()
self.GIAAlgorithm.s.push()
NextParetoPoint, _local_count_unsat_calls, _local_count_unsat_calls = self.GIAAlgorithm.ranToParetoFront(
prev_solution)
self.addParetoPoints(NextParetoPoint)
metric_values = self.GIAAlgorithm.get_metric_values(
NextParetoPoint)
self.result_queue.put(
(model_to_string(self.cfr,
NextParetoPoint), metric_values))
self.GIAAlgorithm.s.pop()
tmpNotDominatedByNextParetoPoint = self.GIAAlgorithm.ConstraintNotDominatedByX(
NextParetoPoint)
self.GIAAlgorithm.s.add(tmpNotDominatedByNextParetoPoint)
num_solutions = num_solutions + 1
self.clock.tock("Consumer " + str(self.index))
print("Total Sat Calls: " + total_sat_calls)
print("Total Unsat Time: " + total_unsat_time)
self.timeQueue.put(self.clock)
return 0
class GIAConsumer(multiprocessing.Process):
def __init__(self, task_queue, result_queue, cfr, timeQueue, index, outputFileParentName, num_consumers, s, metrics_variables, metrics_objective_direction, consumerConstraints):
multiprocessing.Process.__init__(self)
self.task_queue = task_queue
self.result_queue = result_queue
self.timeQueue = timeQueue
self.cfr = cfr
self.solver = s
self.consumerConstraints = consumerConstraints
self.index = index
self.num_consumers = num_consumers
self.ParetoFront = []
self.clock = Clock()
self.GIAOptions = GuidedImprovementAlgorithmOptions(verbosity=0, \
incrementallyWriteLog=False, \
writeTotalTimeFilename="timefile.csv", \
writeRandomSeedsFilename="randomseed.csv", useCallLogs=False)
self.GIAAlgorithm = GuidedImprovementAlgorithm(self.cfr, self.solver, metrics_variables, \
metrics_objective_direction, [], options=self.GIAOptions)
def addParetoPoints(self, point):
self.ParetoFront.append(point)
def run(self):
num_solutions = 0
self.clock.tick("Consumer " + str(self.index))
while True:
next_task = self.task_queue.get()
try:
if next_task == "Poison" or (num_solutions == Options.NUM_INSTANCES):
self.task_queue.task_done()
break
except:
pass
self.solver.push()
self.solver.add(self.consumerConstraints[int(next_task)])
self.consumerConstraints[int(next_task)]
self.clock.tick("Task " + str(next_task))
total_sat_calls = 0
total_unsat_time = 0
while True:
if self.GIAAlgorithm.s.check() != Common.SAT or num_solutions == Options.NUM_INSTANCES:
self.clock.tock("Task " + str(next_task))
self.task_queue.task_done()
self.solver.pop()
break
else:
prev_solution = self.GIAAlgorithm.s.model()
self.GIAAlgorithm.s.push()
NextParetoPoint, _local_count_unsat_calls, _local_count_unsat_calls = self.GIAAlgorithm.ranToParetoFront(prev_solution)
self.addParetoPoints(NextParetoPoint)
metric_values = self.GIAAlgorithm.get_metric_values(NextParetoPoint)
self.result_queue.put((model_to_string(self.cfr, NextParetoPoint), metric_values))
self.GIAAlgorithm.s.pop()
tmpNotDominatedByNextParetoPoint = self.GIAAlgorithm.ConstraintNotDominatedByX(NextParetoPoint)
self.GIAAlgorithm.s.add(tmpNotDominatedByNextParetoPoint)
num_solutions = num_solutions + 1
self.clock.tock("Consumer " + str(self.index))
print("Total Sat Calls: " + total_sat_calls)
print("Total Unsat Time: " + total_unsat_time)
self.timeQueue.put(self.clock)
return 0
