utilize activations registry in neural network topology

src/topology/activation.rs

@@ -5,6 +5,8 @@ use std::{collections::HashMap, fmt, sync::{Arc, RwLock}};
 use lazy_static::lazy_static;
 use bitflags::bitflags;
 
+use crate::NeuronLocation;
+
 /// Creates an [`ActivationFn`] object from a function
 #[macro_export]
 macro_rules! activation_fn {
@@ -119,6 +121,16 @@ impl Default for ActivationScope {
     }
 }
 
+impl From<&NeuronLocation> for ActivationScope {
+    fn from(value: &NeuronLocation) -> Self {
+        match value {
+            NeuronLocation::Input(_) => Self::INPUT,
+            NeuronLocation::Hidden(_) => Self::HIDDEN,
+            NeuronLocation::Output(_) => Self::OUTPUT,
+        }
+    }
+}
+
 /// A trait that represents an activation method.
 pub trait Activation {
     /// The activation function.

src/topology/mod.rs

@@ -290,7 +290,7 @@ impl<const I: usize, const O: usize> RandomlyMutable for NeuralNetworkTopology<I
 
                 let loc3 = NeuronLocation::Hidden(self.hidden_layers.len());
 
-                let n3 = NeuronTopology::new(vec![loc], rng);
+                let n3 = NeuronTopology::new(vec![loc],  ActivationScope::HIDDEN, rng);
 
                 self.hidden_layers.push(Arc::new(RwLock::new(n3)));
 
@@ -344,11 +344,8 @@ impl<const I: usize, const O: usize> RandomlyMutable for NeuralNetworkTopology<I
 
             if rng.gen::<f32>() <= rate && !self.hidden_layers.is_empty() {
                 // mutate activation function
-                let activations = activation_fn! {
-                    sigmoid,
-                    relu,
-                    f32::tanh
-                };
+                let reg = ACTIVATION_REGISTRY.read().unwrap();
+                let activations = reg.activations_in_scope(ActivationScope::HIDDEN);
 
                 let (mut n, mut loc) = self.rand_neuron(rng);
 
@@ -543,12 +540,9 @@ pub struct NeuronTopology {
 
 impl NeuronTopology {
     /// Creates a new neuron with the given input locations.
-    pub fn new(inputs: Vec<NeuronLocation>, rng: &mut impl Rng) -> Self {
-        let activations = activation_fn! {
-            sigmoid,
-            relu,
-            f32::tanh
-        };
+    pub fn new(inputs: Vec<NeuronLocation>, current_scope: ActivationScope, rng: &mut impl Rng) -> Self {
+        let reg = ACTIVATION_REGISTRY.read().unwrap();
+        let activations = reg.activations_in_scope(current_scope);
 
         Self::new_with_activations(inputs, activations, rng)
     }
@@ -625,4 +619,4 @@ impl NeuronLocation {
             Self::Output(i) => *i,
         }
     }
-}
+}