just remove staticdudt tests

We already deprecated it, and it throws some things, and it wasn't really documented in the first place, so the best thing to do is just to drop it from the tests.

Author: ChrisRackauckas

test/neural_de.jl

@@ -7,7 +7,6 @@ tspan = (0.0f0,1.0f0)
 dudt = Flux.Chain(Flux.Dense(2,50,tanh),Flux.Dense(50,2))
 fastdudt = FastChain(FastDense(2,50,tanh),FastDense(50,2))
 fastcdudt = FastChain(FastDense(2,50,tanh,precache=true,numcols=size(xs)[2]),FastDense(50,2,precache=true,numcols=size(xs)[2]))
-staticdudt = FastChain(StaticDense(2,50,tanh),StaticDense(50,2))
 
 NeuralODE(dudt,tspan,Tsit5(),save_everystep=false,save_start=false)(x)
 NeuralODE(dudt,tspan,Tsit5(),saveat=0.1)(x)
@@ -139,20 +138,10 @@ grads = Zygote.gradient(()->sum(node(xs)),Flux.params(xs,node))
 goodgrad2 = grads[node.p]
 @test goodgradc ≈ goodgrad2 rtol=1e-6
 
-node = NeuralODE(staticdudt,tspan,Tsit5(),save_everystep=false,save_start=false,sensealg=BacksolveAdjoint(autojacvec=false),p=p)
-grads = Zygote.gradient(()->sum(node(x)),Flux.params(x,node))
-@test ! iszero(grads[x])
-@test ! iszero(grads[node.p])
-
 grads = Zygote.gradient(()->sum(node(xs)),Flux.params(xs,node))
 goodgrad2 = grads[node.p]
 @test goodgrad ≈ goodgrad2 rtol = 1e-6
 
-node = NeuralODE(staticdudt,tspan,Tsit5(),save_everystep=false,save_start=false,sensealg=BacksolveAdjoint(autojacvec=ZygoteVJP()),p=p)
-grads = Zygote.gradient(()->sum(node(x)),Flux.params(x,node))
-@test !iszero(grads[x])
-@test !iszero(grads[node.p])
-
 @test_throws ErrorException grads = Zygote.gradient(()->sum(node(xs)),Flux.params(xs,node))
 
 @info "Test some adjoints"