src/nupic/swarming/permutations_runner.py
def __startSearch(self):
    """Starts HyperSearch as a worker or runs it inline for the "dryRun" action

    Parameters:
    ----------------------------------------------------------------------
    retval:         the new _HyperSearchJob instance representing the
                    HyperSearch job
    """
    # This search uses a pre-existing permutations script
    params = _ClientJobUtils.makeSearchJobParamsDict(options=self._options,
                                                     forRunning=True)

    if self._options["action"] == "dryRun":
      args = [sys.argv[0], "--params=%s" % (json.dumps(params))]

      print
      print "=================================================================="
      print "RUNNING PERMUTATIONS INLINE as \"DRY RUN\"..."
      print "=================================================================="
      jobID = hypersearch_worker.main(args)

    else:
      cmdLine = _setUpExports(self._options["exports"])
      # Begin the new search. The {JOBID} string is replaced by the actual
      # jobID returned from jobInsert.
      cmdLine += "$HYPERSEARCH"
      maxWorkers = self._options["maxWorkers"]

      jobID = self.__cjDAO.jobInsert(
        client="GRP",
        cmdLine=cmdLine,
        params=json.dumps(params),
        minimumWorkers=1,
        maximumWorkers=maxWorkers,
        jobType=self.__cjDAO.JOB_TYPE_HS)

      cmdLine = "python -m nupic.swarming.hypersearch_worker" \
                 " --jobID=%d" % (jobID)
      self._launchWorkers(cmdLine, maxWorkers)

    searchJob = _HyperSearchJob(jobID)

    # Save search ID to file (this is used for report generation)
    self.__saveHyperSearchJobID(
      permWorkDir=self._options["permWorkDir"],
      outputLabel=self._options["outputLabel"],
      hyperSearchJob=searchJob)

    if self._options["action"] == "dryRun":
      print "Successfully executed \"dry-run\" hypersearch, jobID=%d" % (jobID)
    else:
      print "Successfully submitted new HyperSearch job, jobID=%d" % (jobID)
      _emit(Verbosity.DEBUG,
            "Each worker executing the command line: %s" % (cmdLine,))

    return searchJob
def __startSearch(self):
    """Starts HyperSearch as a worker or runs it inline for the "dryRun" action

    Parameters:
    ----------------------------------------------------------------------
    retval:         the new _HyperSearchJob instance representing the
                    HyperSearch job
    """
    # This search uses a pre-existing permutations script
    params = _ClientJobUtils.makeSearchJobParamsDict(options=self._options,
                                                     forRunning=True)

    if self._options["action"] == "dryRun":
      args = [sys.argv[0], "--params=%s" % (json.dumps(params))]

      print
      print "=================================================================="
      print "RUNNING PERMUTATIONS INLINE as \"DRY RUN\"..."
      print "=================================================================="
      jobID = hypersearch_worker.main(args)

    else:
      cmdLine = _setUpExports(self._options["exports"])
      # Begin the new search. The {JOBID} string is replaced by the actual
      # jobID returned from jobInsert.
      cmdLine += "$HYPERSEARCH"
      maxWorkers = self._options["maxWorkers"]

      jobID = self.__cjDAO.jobInsert(
        client="GRP",
        cmdLine=cmdLine,
        params=json.dumps(params),
        minimumWorkers=1,
        maximumWorkers=maxWorkers,
        jobType=self.__cjDAO.JOB_TYPE_HS)

      cmdLine = "python -m nupic.swarming.hypersearch_worker" \
                 " --jobID=%d" % (jobID)
      self._launchWorkers(cmdLine, maxWorkers)

    searchJob = _HyperSearchJob(jobID)

    # Save search ID to file (this is used for report generation)
    self.__saveHyperSearchJobID(
      permWorkDir=self._options["permWorkDir"],
      outputLabel=self._options["outputLabel"],
      hyperSearchJob=searchJob)

    if self._options["action"] == "dryRun":
      print "Successfully executed \"dry-run\" hypersearch, jobID=%d" % (jobID)
    else:
      print "Successfully submitted new HyperSearch job, jobID=%d" % (jobID)
      _emit(Verbosity.DEBUG,
            "Each worker executing the command line: %s" % (cmdLine,))

    return searchJob
def __startSearch ( self ) : # This search uses a pre-existing permutations script params = _ClientJobUtils . makeSearchJobParamsDict ( options = self . _options , forRunning = True ) if self . _options [ "action" ] == "dryRun" : args = [ sys . argv [ 0 ] , "--params=%s" % ( json . dumps ( params ) ) ] print print "==================================================================" print "RUNNING PERMUTATIONS INLINE as \"DRY RUN\"..." print "==================================================================" jobID = hypersearch_worker . main ( args ) else : cmdLine = _setUpExports ( self . _options [ "exports" ] ) # Begin the new search. The {JOBID} string is replaced by the actual # jobID returned from jobInsert. cmdLine += "$HYPERSEARCH" maxWorkers = self . _options [ "maxWorkers" ] jobID = self . __cjDAO . jobInsert ( client = "GRP" , cmdLine = cmdLine , params = json . dumps ( params ) , minimumWorkers = 1 , maximumWorkers = maxWorkers , jobType = self . __cjDAO . JOB_TYPE_HS ) cmdLine = "python -m nupic.swarming.hypersearch_worker" " --jobID=%d" % ( jobID ) self . _launchWorkers ( cmdLine , maxWorkers ) searchJob = _HyperSearchJob ( jobID ) # Save search ID to file (this is used for report generation) self . __saveHyperSearchJobID ( permWorkDir = self . _options [ "permWorkDir" ] , outputLabel = self . _options [ "outputLabel" ] , hyperSearchJob = searchJob ) if self . _options [ "action" ] == "dryRun" : print "Successfully executed \"dry-run\" hypersearch, jobID=%d" % ( jobID ) else : print "Successfully submitted new HyperSearch job, jobID=%d" % ( jobID ) _emit ( Verbosity . DEBUG , "Each worker executing the command line: %s" % ( cmdLine , ) ) return searchJob
Starts HyperSearch as a worker or runs it inline for the "dryRun" action

    Parameters:
    ----------------------------------------------------------------------
    retval:         the new _HyperSearchJob instance representing the
                    HyperSearch job
Starts HyperSearch as a worker or runs it inline for the dryRun action