refactor: use RealInputArray and RealOutputArray

Author: Sathvik Bhagavan

src/ModelingToolkitNeuralNets.jl

@@ -2,7 +2,7 @@ module ModelingToolkitNeuralNets
 
 using ModelingToolkit: @parameters, @named, ODESystem, t_nounits, @connector, @variables,
                        Equation
-using ModelingToolkitStandardLibrary.Blocks: RealInput, RealOutput
+using ModelingToolkitStandardLibrary.Blocks: RealInputArray, RealOutputArray
 using Symbolics: Symbolics, @register_array_symbolic, @wrapped
 using LuxCore: stateless_apply
 using Lux: Lux
@@ -13,24 +13,6 @@ export NeuralNetworkBlock, multi_layer_feed_forward
 
 include("utils.jl")
 
-@connector function RealInput2(; name, nin = 1, u_start = zeros(nin))
-    @variables u(t_nounits)[1:nin]=u_start [
-        input = true,
-        description = "Inner variable in RealInput $name"
-    ]
-    u = collect(u)
-    ODESystem(Equation[], t_nounits, [u...], []; name = name)
-end
-
-@connector function RealOutput2(; name, nout = 1, u_start = zeros(nout))
-    @variables u(t_nounits)[1:nout]=u_start [
-        output = true,
-        description = "Inner variable in RealOutput $name"
-    ]
-    u = collect(u)
-    ODESystem(Equation[], t_nounits, [u...], []; name = name)
-end
-
 """
     NeuralNetworkBlock(n_input = 1, n_output = 1;
         chain = multi_layer_feed_forward(n_input, n_output),
@@ -49,17 +31,17 @@ function NeuralNetworkBlock(n_input = 1,
     ca = ComponentArray{eltype}(init_params)
 
     @parameters p[1:length(ca)] = Vector(ca)
-    @parameters T::typeof(typeof(p))=typeof(p) [tunable = false]
+    # @parameters T::typeof(typeof(p))=typeof(p) [tunable = false]
 
-    @named input = RealInput2(nin = n_input)
-    @named output = RealOutput2(nout = n_output)
+    @named input = RealInputArray(nin = n_input)
+    @named output = RealOutputArray(nout = n_output)
 
     out = stateless_apply(chain, input.u, lazyconvert(typeof(ca), p))
 
     eqs = [output.u ~ out]
 
     @named ude_comp = ODESystem(
-        eqs, t_nounits, [], [p, T], systems = [input, output])
+        eqs, t_nounits, [], [p], systems = [input, output])
     return ude_comp
 end