diff --git a/docs/src/tutorials/chaotic_ode.md b/docs/src/tutorials/chaotic_ode.md
index 11bbb417f..d8213c4e8 100644
--- a/docs/src/tutorials/chaotic_ode.md
+++ b/docs/src/tutorials/chaotic_ode.md
@@ -35,7 +35,7 @@ u0 = [1.0, 0.0, 0.0]
 prob = ODEProblem(lorenz!, u0, tspan, p)
 sol = solve(prob, Vern9(), abstol = 1e-14, reltol = 1e-14)
 sol2 = solve(prob, Vern9(), abstol = 1e-14 + eps(Float64), reltol = 1e-14)
-pl1 = plot(sol, vars = (1, 2, 3), legend = true,
+pl1 = plot(sol, idxs = (1, 2, 3), legend = true,
     label = "sol",
     labelfontsize = 20,
     lw = 2,
@@ -122,7 +122,7 @@ g(u, p, t) = u[end]
 
 function G(p)
     _prob = remake(prob_attractor, p = p)
-    _sol = solve(_prob, Vern9(), abstol = 1e-14, reltol = 1e-14, saveat = 0.01,
+    _sol = solve(_prob, Vern9(), abstol = 1e-8, reltol = 1e-8, saveat = 0.01,
         sensealg = ForwardLSS(g = g))
     sum(getindex.(_sol.u, 3))
 end
@@ -133,7 +133,7 @@ Alternatively, we can define the `ForwardLSSProblem` and solve it
 via `shadow_forward` as follows:
 
 ```@example chaosode
-sol_attractor = solve(prob_attractor, Vern9(), abstol = 1e-14, reltol = 1e-14)
+sol_attractor = solve(prob_attractor, Vern9(), abstol = 1e-8, reltol = 1e-8)
 lss_problem = ForwardLSSProblem(sol_attractor, ForwardLSS(g = g))
 resfw = shadow_forward(lss_problem)
 ```
diff --git a/test/gpu/diffeqflux_standard_gpu.jl b/test/gpu/diffeqflux_standard_gpu.jl
index c49c24f70..35bf6c57f 100644
--- a/test/gpu/diffeqflux_standard_gpu.jl
+++ b/test/gpu/diffeqflux_standard_gpu.jl
@@ -30,7 +30,7 @@ function predict_neuralode(p)
 end
 function loss_neuralode(p)
     pred = predict_neuralode(p)
-    loss = sum(abs2, ode_data .- pred)
+    loss = sum(abs2, ode_data .- gdev(pred))
     return loss
 end