refactor: [temp] add RealInput/RealOutput which works for size equal to 1

Author: Sathvik Bhagavan

src/ModelingToolkitNeuralNets.jl

@@ -1,6 +1,7 @@
 module ModelingToolkitNeuralNets
 
-using ModelingToolkit: @parameters, @named, ODESystem, t_nounits
+using ModelingToolkit: @parameters, @named, ODESystem, t_nounits, @connector, @variables,
+                       Equation
 using ModelingToolkitStandardLibrary.Blocks: RealInput, RealOutput
 using Symbolics: Symbolics, @register_array_symbolic, @wrapped
 using LuxCore: stateless_apply
@@ -12,6 +13,24 @@ 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),
@@ -29,8 +48,8 @@ function NeuralNetworkBlock(n_input = 1,
     @parameters p[1:length(ca)] = Vector(ca)
     @parameters T::typeof(typeof(p))=typeof(p) [tunable = false]
 
-    @named input = RealInput(nin = n_input)
-    @named output = RealOutput(nout = n_output)
+    @named input = RealInput2(nin = n_input)
+    @named output = RealOutput2(nout = n_output)
 
     out = stateless_apply(chain, input.u, lazyconvert(typeof(ca), p))