def __call__(self, workloadName, arguments): """ Create a workload instance for a LHE Step0 request Just pass it down to MonteCarlo """ #Override splitting arguments # Splitting arguments timePerEvent = int(arguments.get('TimePerEvent', 60)) filterEfficiency = float(arguments.get('FilterEfficiency', 1.0)) totalTime = int(arguments.get('TotalTime', 9 * 3600)) self.totalEvents = int(int(arguments['RequestNumEvents']) / filterEfficiency) if arguments.get("LheInputFiles", False) == True \ or arguments.get("LheInputFiles", False) == "True": self.lheInputFiles = True # These are mostly place holders because the job splitting algo and # parameters will be updated after the workflow has been created. eventsPerJob = int(totalTime/timePerEvent/filterEfficiency) self.prodJobSplitAlgo = arguments.setdefault("ProdJobSplitAlgo", 'EventBased') self.prodJobSplitArgs = arguments.setdefault("ProdJobSplitArgs", {"events_per_job": eventsPerJob, "events_per_lumi": arguments['EventsPerLumi']}) self.prodJobSplitArgs.setdefault("lheInputFiles", self.lheInputFiles) mcWorkload = MonteCarloWorkloadFactory.__call__(self, workloadName, arguments) mcWorkload.setBlockCloseSettings(mcWorkload.getBlockCloseMaxWaitTime(), 5, 250000000, mcWorkload.getBlockCloseMaxSize()) return mcWorkload
def __call__(self, workloadName, arguments): """ Create a workload instance for a LHE Step0 request Just pass it down to MonteCarlo """ #Override splitting arguments # Splitting arguments timePerEvent = int(arguments.get('TimePerEvent', 60)) filterEfficiency = float(arguments.get('FilterEfficiency', 1.0)) totalTime = int(arguments.get('TotalTime', 9 * 3600)) self.totalEvents = int(int(arguments['RequestNumEvents']) / filterEfficiency) # These are mostly place holders because the job splitting algo and # parameters will be updated after the workflow has been created. eventsPerJob = int(totalTime/timePerEvent/filterEfficiency) self.prodJobSplitAlgo = arguments.setdefault("ProdJobSplitAlgo", 'EventBased') self.prodJobSplitArgs = arguments.setdefault("ProdJobSplitArgs", {"events_per_job": eventsPerJob, "events_per_lumi": arguments['EventsPerLumi']}) return MonteCarloWorkloadFactory.__call__(self, workloadName, arguments)
def __call__(self, workflowName, args): workload = MonteCarloWorkloadFactory.__call__(self, workflowName, args) delattr(workload.taskIterator().next().steps().data.application.configuration, 'configCacheUrl') return workload
def __call__(self, workflowName, args): workload = MonteCarloWorkloadFactory.__call__(self, workflowName, args) #delattr(workload.taskIterator().next().steps().data.application.configuration, # 'configCacheUrl') return workload