cargo fmt

src/topology.rs

@@ -1,5 +1,7 @@
 use std::{
-    collections::HashSet, fmt, sync::{Arc, RwLock}
+    collections::HashSet,
+    fmt,
+    sync::{Arc, RwLock},
 };
 
 use genetic_rs::prelude::*;
@@ -95,17 +97,26 @@ impl<const I: usize, const O: usize> NeuralNetworkTopology<I, O> {
     /// Creates a new connection between the neurons.
     /// If the connection is cyclic, it does not add a connection and returns false.
     /// Otherwise, it returns true.
-    pub fn add_connection(&mut self, from: NeuronLocation, to: NeuronLocation, weight: f32) -> bool {
+    pub fn add_connection(
+        &mut self,
+        from: NeuronLocation,
+        to: NeuronLocation,
+        weight: f32,
+    ) -> bool {
         if self.is_connection_cyclic(from, to) {
             return false;
         }
-    
+
         // Add the connection since it is not cyclic
-        self.get_neuron(to).write().unwrap().inputs.push((from, weight));
-
+        self.get_neuron(to)
+            .write()
+            .unwrap()
+            .inputs
+            .push((from, weight));
+
         true
     }
-    
+
     fn is_connection_cyclic(&self, from: NeuronLocation, to: NeuronLocation) -> bool {
         if to.is_input() || from.is_output() {
             return true;
@@ -114,24 +125,29 @@ impl<const I: usize, const O: usize> NeuralNetworkTopology<I, O> {
         let mut visited = HashSet::new();
         self.dfs(from, to, &mut visited)
     }
-    
+
     // TODO rayon implementation
-    fn dfs(&self, current: NeuronLocation, target: NeuronLocation, visited: &mut HashSet<NeuronLocation>) -> bool {
+    fn dfs(
+        &self,
+        current: NeuronLocation,
+        target: NeuronLocation,
+        visited: &mut HashSet<NeuronLocation>,
+    ) -> bool {
         if current == target {
             return true;
         }
-    
+
         visited.insert(current);
-    
+
         let n = self.get_neuron(current);
         let nr = n.read().unwrap();
-    
+
         for &(input, _) in &nr.inputs {
             if !visited.contains(&input) && self.dfs(input, target, visited) {
                 return true;
             }
         }
-    
+
         visited.remove(&current);
         false
     }
@@ -168,14 +184,15 @@ impl<const I: usize, const O: usize> NeuralNetworkTopology<I, O> {
         if !loc.is_hidden() {
             panic!("Invalid neuron deletion");
         }
-    
+
         let index = loc.unwrap();
         let neuron = Arc::into_inner(self.hidden_layers.remove(index)).unwrap();
 
         for n in &self.hidden_layers {
             let mut nw = n.write().unwrap();
 
-            nw.inputs = nw.inputs
+            nw.inputs = nw
+                .inputs
                 .iter()
                 .filter_map(|&(input_loc, w)| {
                     if !input_loc.is_hidden() {
@@ -194,10 +211,11 @@ impl<const I: usize, const O: usize> NeuralNetworkTopology<I, O> {
                 })
                 .collect();
         }
-    
+
         for n2 in &self.output_layer {
             let mut nw = n2.write().unwrap();
-            nw.inputs = nw.inputs
+            nw.inputs = nw
+                .inputs
                 .iter()
                 .filter_map(|&(input_loc, w)| {
                     if !input_loc.is_hidden() {
@@ -216,7 +234,7 @@ impl<const I: usize, const O: usize> NeuralNetworkTopology<I, O> {
                 })
                 .collect();
         }
-    
+
         neuron.into_inner().unwrap()
     }
 }
@@ -298,7 +316,7 @@ impl<const I: usize, const O: usize> RandomlyMutable for NeuralNetworkTopology<I
                 while !loc.is_hidden() {
                     (_, loc) = self.rand_neuron(rng);
                 }
-                
+
                 // delete the neuron
                 self.delete_neuron(loc);
             }