Merge pull request #238 from ReactiveBayes/const-creates-twice

Constants increase model counter twice

Author: wouterwln

src/graph_engine.jl

@@ -1436,7 +1436,7 @@ getifcreated(model::Model, context::Context, var::Union{Tuple, AbstractArray{T}}
     map((v) -> getifcreated(model, context, v), var)
 getifcreated(model::Model, context::Context, var::ProxyLabel) = var
 getifcreated(model::Model, context::Context, var) =
-    add_variable_node!(model, context, NodeCreationOptions(value = var, kind = :constant), gensym(model, :constvar), nothing)
+    add_constant_node!(model, context, NodeCreationOptions(value = var, kind = :constant), :constvar, nothing)
 
 """
     add_variable_node!(model::Model, context::Context, options::NodeCreationOptions, name::Symbol, index)
@@ -1461,14 +1461,22 @@ function add_variable_node!(model::Model, context::Context, name::Symbol, index)
 end
 
 function add_variable_node!(model::Model, context::Context, options::NodeCreationOptions, name::Symbol, index)
+    label = __add_variable_node!(model, context, options, name, index)
+    context[name, index] = label
+end
 
+function add_constant_node!(model::Model, context::Context, options::NodeCreationOptions, name::Symbol, index)
+    label = __add_variable_node!(model, context, options, name, index)
+    context[to_symbol(label), index] = label
+end
+
+function __add_variable_node!(model::Model, context::Context, options::NodeCreationOptions, name::Symbol, index)
     # In theory plugins are able to overwrite this
     potential_label = generate_nodelabel(model, name)
     potential_nodedata = NodeData(context, convert(VariableNodeProperties, name, index, options))
     label, nodedata = preprocess_plugins(
         UnionPluginType(VariableNodePlugin(), FactorAndVariableNodesPlugin()), model, context, potential_label, potential_nodedata, options
     )
-    context[name, index] = label
     add_vertex!(model, label, nodedata)
     return label
 end

test/graph_construction_tests.jl

@@ -1678,7 +1678,6 @@ end
     include("testutils.jl")
 
     @model function neural_dot(out, in, w)
-        local c
         c[1] ~ in[1] * w[1]
         for i in 2:length(in)
             c[i] ~ c[i - 1] + in[i] * w[i]