feat: Updated the tests to include the full evidential regression loss.

test/runtests.jl

@@ -39,16 +39,15 @@ using Test
  # y = 1 * sin.(x[1, :]) .- 3 * sin.(x[2, :]) .+ 2 * cos.(x[3, :]) .+ randn(Float32, 91)
  y = 1 * x[1, :] .- 3 * x[2, :] .+ 2 * x[3, :] .+ randn(Float32, 91)
  #scatterplot(x[1, :], y, width = 90, height = 30)
- #loss(y, ŷ) = sum(abs, y - ŷ)
  pars = Flux.params(m)
  opt = ADAMW(0.005)
  trnlosses = zeros(Float32, 1000)
  for i in 1:1000
  local trnloss
  grads = Flux.gradient(pars) do
  ŷ = m(x)
- γ = ŷ[1, :]
- trnloss = loss(y, γ)
+ γ, ν, α, β = ŷ[1, :], ŷ[2, :], ŷ[3, :], ŷ[4, :]
+ trnloss = sum(nignll(y, γ, ν, α, β, 0.1, 1e-4))
  end
  trnlosses[i] = trnloss
  # Test that we can update the weights based on gradients