Update GLOBAL_RNG to Random.default_rng()

src/AdvancedHMC.jl

@@ -6,8 +6,7 @@ using Statistics: mean, var, middle
 using LinearAlgebra:
     Symmetric, UpperTriangular, mul!, ldiv!, dot, I, diag, cholesky, UniformScaling
 using StatsFuns: logaddexp, logsumexp
-import Random
-using Random: GLOBAL_RNG, AbstractRNG
+import Random: Random, AbstractRNG
 using ProgressMeter: ProgressMeter
 using SimpleUnPack: @unpack
 

src/abstractmcmc.jl

@@ -55,7 +55,7 @@ A convenient wrapper around `AbstractMCMC.sample` avoiding explicit construction
 """
 
 function AbstractMCMC.sample(
-    rng::Random.AbstractRNG,
+    rng::AbstractRNG,
     model::AbstractMCMC.LogDensityModel,
     sampler::AbstractHMCSampler,
     N::Integer;
@@ -92,7 +92,7 @@ function AbstractMCMC.sample(
 end
 
 function AbstractMCMC.sample(
-    rng::Random.AbstractRNG,
+    rng::AbstractRNG,
     model::AbstractMCMC.LogDensityModel,
     sampler::AbstractHMCSampler,
     parallel::AbstractMCMC.AbstractMCMCEnsemble,
@@ -318,7 +318,7 @@ end
 #########
 
 function make_step_size(
-    rng::Random.AbstractRNG,
+    rng::AbstractRNG,
     spl::HMCSampler,
     hamiltonian::Hamiltonian,
     initial_params,
@@ -329,7 +329,7 @@ function make_step_size(
 end
 
 function make_step_size(
-    rng::Random.AbstractRNG,
+    rng::AbstractRNG,
     spl::AbstractHMCSampler,
     hamiltonian::Hamiltonian,
     initial_params,
@@ -340,7 +340,7 @@ function make_step_size(
 end
 
 function make_step_size(
-    rng::Random.AbstractRNG,
+    rng::AbstractRNG,
     integrator::AbstractIntegrator,
     T::Type,
     hamiltonian::Hamiltonian,
@@ -356,7 +356,7 @@ function make_step_size(
 end
 
 function make_step_size(
-    rng::Random.AbstractRNG,
+    rng::AbstractRNG,
     integrator::Symbol,
     T::Type,
     hamiltonian::Hamiltonian,

src/metric.jl

@@ -138,7 +138,7 @@ Base.rand(
     kinetic::AbstractKinetic,
 ) = _rand(rng, metric, kinetic)
 Base.rand(metric::AbstractMetric, kinetic::AbstractKinetic) =
-    rand(GLOBAL_RNG, metric, kinetic)
+    rand(Random.default_rng(), metric, kinetic)
 
 # ignore θ by default unless defined by the specific kinetic (i.e. not position-dependent)
 Base.rand(
@@ -154,4 +154,4 @@ Base.rand(
     θ::AbstractVecOrMat,
 ) = rand(rng, metric, kinetic)
 Base.rand(metric::AbstractMetric, kinetic::AbstractKinetic, θ::AbstractVecOrMat) =
-    rand(metric, kinetic)
+    rand(Random.default_rng(), metric, kinetic)

src/sampler.jl

@@ -118,7 +118,7 @@ sample(
     progress::Bool = false,
     (pm_next!)::Function = pm_next!,
 ) = sample(
-    GLOBAL_RNG,
+    Random.default_rng(),
     h,
     κ,
     θ,
@@ -146,7 +146,7 @@ sample(
     )
 Sample `n_samples` samples using the proposal `κ` under Hamiltonian `h`.
 - The randomness is controlled by `rng`. 
-    - If `rng` is not provided, `GLOBAL_RNG` will be used.
+    - If `rng` is not provided, `Random.default_rng()` will be used.
 - The initial point is given by `θ`.
 - The adaptor is set by `adaptor`, for which the default is no adaptation.
     - It will perform `n_adapts` steps of adaptation, for which the default is the minimum of `1_000` and 10% of `n_samples`
@@ -181,6 +181,7 @@ function sample(
         nothing
     time = @elapsed for i = 1:n_samples
         # Make a transition
+        # i == 2 && error(κ.τ.integrator)
         t = transition(rng, h, κ, t.z)
         # Adapt h and κ; what mutable is the adaptor
         tstat = stat(t)

src/trajectory.jl

@@ -3,7 +3,7 @@
 ####
 #### Developers' Notes
 ####
-#### Not all functions that use `rng` require a fallback function with `GLOBAL_RNG`
+#### Not all functions that use `rng` require a fallback function with `Random.default_rng()`
 #### as default. In short, only those exported to other libries need such a fallback
 #### function. Internal uses shall always use the explict `rng` version. (Kai Xu 6/Jul/19)
 
@@ -241,10 +241,10 @@ $(SIGNATURES)
 
 Make a MCMC transition from phase point `z` using the trajectory `τ` under Hamiltonian `h`.
 
-NOTE: This is a RNG-implicit fallback function for `transition(GLOBAL_RNG, τ, h, z)`
+NOTE: This is a RNG-implicit fallback function for `transition(Random.default_rng(), τ, h, z)`
 """
 function transition(τ::Trajectory, h::Hamiltonian, z::PhasePoint)
-    return transition(GLOBAL_RNG, τ, h, z)
+    return transition(Random.default_rng(), τ, h, z)
 end
 
 ###
@@ -834,7 +834,7 @@ function find_good_stepsize(
     θ::AbstractVector{<:AbstractFloat};
     max_n_iters::Int = 100,
 )
-    return find_good_stepsize(GLOBAL_RNG, h, θ; max_n_iters = max_n_iters)
+    return find_good_stepsize(Random.default_rng(), h, θ; max_n_iters = max_n_iters)
 end
 
 "Perform MH acceptance based on energy, i.e. negative log probability."