Add multithreaded assume

ad.py

@@ -78,7 +78,7 @@ def run_ad(args):
 
     results = {}
 
-    if model_key == "multithreaded":
+    if model_key.startswith("threaded_"):
         RUN_JULIA_COMMAND = ["julia", "--threads=4", *JULIA_COMMAND[1:]]
     else:
         RUN_JULIA_COMMAND = JULIA_COMMAND

main.jl

@@ -80,7 +80,8 @@ end
 #    x, y, z, ... are observed variables
 # although it's hardly a big deal.
 @include_model "Base Julia features" "control_flow"
-@include_model "Base Julia features" "multithreaded"
+@include_model "Base Julia features" "threaded_assume"
+@include_model "Base Julia features" "threaded_observe"
 @include_model "Core Turing syntax" "assume_submodel"
 @include_model "Core Turing syntax" "broadcast_macro"
 @include_model "Core Turing syntax" "dot_assume"

models/threaded_assume.jl

@@ -0,0 +1,14 @@
+#=
+Note: this example is run with 4 threads
+=#
+
+@model function threaded_assume(x)
+    a = Vector{Float64}(undef, length(x))
+    Threads.@threads for i in eachindex(x)
+        a[i] ~ Normal()
+        x[i] ~ Normal(a[i])
+    end
+end
+
+x = randn(50)
+model = setthreadsafe(threaded_assume(x), true)

models/threaded_observe.jl

@@ -0,0 +1,13 @@
+#=
+Note: this model is run with 4 threads
+=#
+
+@model function threaded_observe(x)
+    a ~ Normal()
+    Threads.@threads for i in eachindex(x)
+        x[i] ~ Normal(a)
+    end
+end
+
+x = randn(100)
+model = setthreadsafe(threaded_observe(x), true)