anchor.diff:          elif a.shape = b.shape then
               let inline fRaw(a:RawTensor,b) = a.DivTT(b)
               let inline fTensor(a,b) = a / b
  -            let inline dfTensorFwdTT(cp:Tensor,ap:Tensor,ad:Tensor,bp:Tensor,bd:Tensor) = (ad - bd * cp) / bp
  -            let inline dfTensorFwdTC(cp:Tensor,ap:Tensor,ad:Tensor) = ad / b
  -            let inline dfTensorFwdCT(cp:Tensor,bp:Tensor,bd:Tensor) = -bd * cp / bp
  +            let inline dfTensorFwdTT(ap:Tensor,ad:Tensor,bp:Tensor,bd:Tensor,cp:Tensor) = (ad - bd * cp) / bp
  +            let inline dfTensorFwdTC(ap:Tensor,ad:Tensor,cp:Tensor) = ad / b
  +            let inline dfTensorFwdCT(bp:Tensor,bd:Tensor,cp:Tensor) = -bd * cp / bp
               let inline dfTensorRevTT(a,b) = DivTT(a,b)
               let inline dfTensorRevTC(a,b) = DivTTConst(a,b)
               let inline dfTensorRevCT(a,b) = DivTConstT(a,b)
  
positive.code:     member a.round() =
          let inline fRaw(a:RawTensor) = a.RoundT()
          let inline fTensor(a:Tensor) = a.round()
          let inline dfTensorFwd(cp:Tensor,ap,ad) = cp.zerosLike()
          let inline dfTensorRev(a) = RoundT(a)
          Tensor.OpUnary(a, fRaw, fTensor, dfTensorFwd, dfTensorRev)
  
  
negative.code:     member a.log() =
          let inline fRaw(a:RawTensor) = a.LogT()
          let inline fTensor(a:Tensor) = a.log()
          let inline dfTensorFwd(ap,ad,cp) = ad / ap
          let inline dfTensorRev(a) = LogT(a)
          Tensor.OpUnary(a, fRaw, fTensor, dfTensorFwd, dfTensorRev)
  
  