text: import FWCore.ParameterSet.Config as cms
  
  #from RecoEgamma.EgammaTools.PhotonConversionMVAComputer_cfi import *
  #
  #  configuration for producer of converted photons
  #  
  #
  conversions = cms.EDProducer("ConvertedPhotonProducer",
      scHybridBarrelProducer = cms.InputTag('particleFlowSuperClusterECAL:particleFlowSuperClusterECALBarrel'),
      scIslandEndcapProducer = cms.InputTag('particleFlowSuperClusterECAL:particleFlowSuperClusterECALEndcapWithPreshower'),
      bcEndcapCollection = cms.InputTag('particleFlowSuperClusterECAL:particleFlowBasicClusterECALEndcap'),
      bcBarrelCollection = cms.InputTag('particleFlowSuperClusterECAL:particleFlowBasicClusterECALBarrel'),
      conversionIOTrackProducer = cms.string('ckfInOutTracksFromConversions'),
      outInTrackCollection = cms.string(''),
      conversionOITrackProducer = cms.string('ckfOutInTracksFromConversions'),
      inOutTrackCollection = cms.string(''),
      inOutTrackSCAssociation = cms.string('inOutTrackSCAssociationCollection'),
      outInTrackSCAssociation = cms.string('outInTrackSCAssociationCollection'),
      convertedPhotonCollection = cms.string('uncleanedConversions'),
      generalTracksSrc = cms.InputTag("generalTracks"),
      hcalTowers = cms.InputTag("towerMaker"),                         
      cleanedConvertedPhotonCollection = cms.string(''),                         
      AlgorithmName = cms.string('ecalSeeded'),
      minSCEt = cms.double(20.0),
      hOverEConeSize = cms.double(0.15),
      maxHOverE = cms.double(0.15),                         
      recoverOneTrackCase = cms.bool(True),
      dRForConversionRecovery = cms.double(0.3),                      
      deltaCotCut = cms.double(0.05),
      minApproachDisCut  = cms.double(0.),
      maxNumOfCandidates = cms.int32(3),
      risolveConversionAmbiguity = cms.bool(True),
      maxDelta = cms.double(0.01),#delta of parameters
      maxReducedChiSq = cms.double(225.),#maximum chi^2 per degree of freedom before fit is terminated
      minChiSqImprovement = cms.double(50.),#threshold for "significant improvement" in the fit termination logic
      maxNbrOfIterations = cms.int32(40), #maximum number of convergence iterations
      MVA_weights_location = cms.string('RecoEgamma/EgammaTools/data/TMVAnalysis_Likelihood.weights.txt')
  #    MVA_weights_location = cms.string('RecoEgamma/EgammaTools/data/TMVAnalysis_Likelihood.weights.xml')
  
   )
  
  