anchor.diff:  
   module Program =
       
  -    let classificationMLMGP()=
  +    let classificationMLMGP dev=
           printfn "Training 2Layer MLMGP on abalone dataset gender classification"
   
           printfn "Training 2 Layer MLP on abalone dataset gender classification"
           ///Load the ablone dataset, classify gender from data
           let fullDataset = (DataParser.loadSingleDataset "abalone.data.txt" [0] ',')
  -        let data = (TrnValTst.Of(fullDataset)).ToCuda() 
  +        
  +        let data = TrnValTst.Of(fullDataset)
  +        if dev = DevCuda then
  +            let data = (TrnValTst.Of(fullDataset)).ToCuda()
  +            ()
           ///classified the dataset using a MLP with one hidden layer
           ///(analogous to Lern Mnist Project)
           let mb = ModelBuilder<single> "MultiGPModel"
  
positive.code:         mb.SetSize nInput (fullDataset.[0].InputS |> ArrayND.nElems)
          mb.SetSize nClass (fullDataset.[0].TargetS |> ArrayND.nElems)
          mb.SetSize nHidden 10
          let mi = mb.Instantiate DevCuda
          
          // loss expression
          let loss = MLP.loss mlp input.T target.T
  
          // optimizer
          let opt = Adam (loss, mi.ParameterVector, DevCuda)
          let optCfg = opt.DefaultCfg
  
          let smplVarEnv (smpl: singleSample) =
  
negative.code:         mb.SetSize nHidden 10
          mb.SetSize nTrn 20
  
          let mi = mb.Instantiate dev
  
          // loss expression
          let loss = MLGPT.loss mlmgp input.T target.T
  
          // optimizer
          let opt = Adam (loss, mi.ParameterVector, dev)
          let optCfg = opt.DefaultCfg
  
          let smplVarEnv (smpl: singleSample) =
  