Typestable use of scaledloss about sparseregression.jl HOT 3 CLOSED

julia> typealias LeastSquaresLoss LossFunctions.ScaledDistanceLoss{L2DistLoss,0.5}
LossFunctions.ScaledDistanceLoss{LossFunctions.LPDistLoss{2},0.5}

julia> value(LeastSquaresLoss(), -1., 3.)
8.0

julia> @code_llvm value(LeastSquaresLoss(), -1., 3.)

define double @julia_value_70896(double, double) #0 {
top:
  %2 = fsub double %1, %0
  %3 = fmul double %2, %2
  %4 = fmul double %3, 5.000000e-01
  ret double %4
}

julia> @code_llvm deriv(L2DistLoss(),-1.,3.)

define double @julia_deriv_70946(double, double) #0 {
top:
  %2 = fsub double %1, %0
  %3 = fmul double %2, 2.000000e+00
  ret double %3
}

julia> @code_llvm deriv(LeastSquaresLoss(),-1.,3.)

define double @julia_deriv_70944(double, double) #0 {
top:
  %2 = fsub double %1, %0
  ret double %2
}

const LinearRegression      = LossFunctions.ScaledDistanceLoss{L2DistLoss,0.5}