Remove version bound of Turing from REQUIRE to use latest

REQUIRE

@@ -3,7 +3,7 @@ DiffEqBase 5.0.0
 #Mamba
 Stan
 Distributions
-Turing 0.5.0
+Turing
 MacroTools
 Optim
 RecursiveArrayTools

test/turing.jl

@@ -18,25 +18,25 @@ bayesian_result = turing_inference(prob1,Tsit5(),t,data,priors;num_samples=500)
 
 @show mean(bayesian_result[:_theta][50:end])
 
-@test mean(bayesian_result[:_theta1][50:end])[1] ≈ 1.5 atol=0.1
+@test mean(bayesian_result[:_theta][50:end])[1] ≈ 1.5 atol=0.1
 
 println("Four parameter case")
-f1 = @ode_def begin
+f2 = @ode_def begin
   dx = a*x - b*x*y
   dy = -c*y + d*x*y
 end a b c d
 u0 = [1.0,1.0]
 tspan = (0.0,10.0)
 p = [1.5,1.0,3.0,1.0]
-prob1 = ODEProblem(f1,u0,tspan,p)
+prob2 = ODEProblem(f2,u0,tspan,p)
 sol = solve(prob1,Tsit5())
 t = collect(range(1,stop=10,length=10))
 randomized = VectorOfArray([(sol(t[i]) + .01randn(2)) for i in 1:length(t)])
 data = convert(Array,randomized)
 priors = [Truncated(Normal(1.5,0.01),0,2),Truncated(Normal(1.0,0.01),0,1.5),
           Truncated(Normal(3.0,0.01),0,4),Truncated(Normal(1.0,0.01),0,2)]
 
-bayesian_result = turing_inference(prob1,Tsit5(),t,data,priors;num_samples=500)
+bayesian_result = turing_inference(prob2,Tsit5(),t,data,priors;num_samples=500)
 
 @show mean(bayesian_result[:_theta][50:end])