refactor: default activation to tanh

Author: SebastianM-C

Project.toml

@@ -9,7 +9,6 @@ Lux = "b2108857-7c20-44ae-9111-449ecde12c47"
 LuxCore = "bb33d45b-7691-41d6-9220-0943567d0623"
 ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
 ModelingToolkitStandardLibrary = "16a59e39-deab-5bd0-87e4-056b12336739"
-NNlib = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Symbolics = "0c5d862f-8b57-4792-8d23-62f2024744c7"
 
@@ -22,7 +21,6 @@ Lux = "0.5.32"
 LuxCore = "0.1.14"
 ModelingToolkit = "9.9.0"
 ModelingToolkitStandardLibrary = "2.6"
-NNlib = "0.9"
 Optimization = "3.22"
 OptimizationOptimisers = "0.2"
 OrdinaryDiffEq = "6.74"

src/UDEComponents.jl

@@ -6,7 +6,6 @@ using Symbolics: Symbolics, @register_array_symbolic, @wrapped
 using LuxCore: stateless_apply
 using Lux: Lux
 using Random: Xoshiro
-using NNlib: softplus
 using ComponentArrays: ComponentArray
 
 export create_ude_component, multi_layer_feed_forward

src/utils.jl

@@ -1,5 +1,5 @@
 function multi_layer_feed_forward(input_length, output_length; width::Int = 5,
-        depth::Int = 1, activation = softplus, disable_optimizations = false)
+        depth::Int = 1, activation = tanh, disable_optimizations = false)
     Lux.Chain(Lux.Dense(input_length, width, activation),
         [Lux.Dense(width, width, activation) for _ in 1:(depth)]...,
         Lux.Dense(width, output_length); disable_optimizations)