added nn config

MSc-Thesis-Samy · Apr 27, 2024 · 600bc13 · 600bc13
1 parent b1f0c53
commit 600bc13
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Showing 6 changed files with 42 additions and 14 deletions.
diff --git a/nn_cmaes_xor.toml b/nn_cmaes_xor.toml
@@ -5,9 +5,9 @@ bias_id = 3
 [[neurons]]
 id = 4
 inputs = [1, 2, 3]
-activation = "SIGMOID"
+activation = "sigmoid"
 
 [[neurons]]
 id = 5
 inputs = [1, 2, 3, 4]
-activation = "SIGMOID"
+activation = "sigmoid"
diff --git a/src/bin/main.rs b/src/bin/main.rs
@@ -71,8 +71,9 @@ fn main() {
             network_config_file.read_to_string(&mut toml_config).unwrap();
 
             let network_config: NeuralNetworkConfig = toml::from_str(&toml_config).unwrap();
-            println!("{:?}", network_config);
-            panic!("Not implemented");
+
+            let network = network_config.to_neural_network();
+            alg = Algorithm::NeuralNetwork(network);
         }
     }
 

diff --git a/src/bin/neural_network_cmaes.rs b/src/bin/neural_network_cmaes.rs
@@ -15,7 +15,7 @@ fn main() {
     );
 
     let problem = Benchmark::new(Problem::Xor);
-    let mut alg = Algorithm::NeuralNetworek(network);
+    let mut alg = Algorithm::NeuralNetwork(network);
     alg.optimize_cmaes(&problem);
     println!("Fitness: {:.2}", problem.evaluate(&alg));
 }
diff --git a/src/gui.rs b/src/gui.rs
@@ -202,7 +202,7 @@ impl State {
                 self.get_bend_decision_mesh(mesh, bias, angle, 0.1, 1., bend)?;
             }
 
-            Algorithm::Neat(_) | Algorithm::NeuralNetworek(_) => {
+            Algorithm::Neat(_) | Algorithm::NeuralNetwork(_) => {
                 match &self.problem {
                     Benchmark::Classification(points) | Benchmark::SphereClassification(points) => {
                     // for now, draw outputs

diff --git a/src/neural_network.rs b/src/neural_network.rs
@@ -73,6 +73,33 @@ impl Neuron {
     }
 }
 
+impl NeuralNetworkConfig {
+    pub fn to_neural_network(&self) -> NeuralNetwork {
+        let mut neurons = Vec::new();
+        for neuron_config in self.neurons.iter() {
+            let activation = match neuron_config.activation.as_str() {
+                "sigmoid" => SIGMOID,
+                "identity" => IDENTITY,
+                _ => panic!("Unknown activation function"),
+            };
+
+            let mut inputs = Vec::new();
+            for input in neuron_config.inputs.iter() {
+                inputs.push(NeuronInput::new(*input, None));
+            }
+
+            neurons.push(Neuron::new(neuron_config.id, inputs, activation));
+        }
+
+        NeuralNetwork {
+            input_ids: self.input_ids.clone(),
+            output_ids: self.output_ids.clone(),
+            bias_id: self.bias_id,
+            neurons,
+        }
+    }
+}
+
 impl NeuralNetwork {
     pub fn new(input_ids: Vec<u32>, output_ids: Vec<u32>, bias_id: Option<u32>, neurons: Vec<Neuron>) -> NeuralNetwork {
         NeuralNetwork {
@@ -146,13 +173,13 @@ impl NeuralNetwork {
 
 impl NeuroevolutionAlgorithm for NeuralNetwork {
     fn optimization_step(&mut self, _problem: &crate::benchmarks::Benchmark) {
-        unimplemented!()
+        unimplemented!("Optimization step not implemented for NeuralNetwork");
     }
 
     fn optimize_cmaes(&mut self, problem: &crate::benchmarks::Benchmark) {
         let eval_fn = |x: &DVector<f64>| {
             let network = self.to_network(x);
-            problem.evaluate(&Algorithm::NeuralNetworek(network))
+            problem.evaluate(&Algorithm::NeuralNetwork(network))
         };
 
         let initial_connection_weights = self.to_vector();

diff --git a/src/neuroevolution_algorithm.rs b/src/neuroevolution_algorithm.rs
@@ -24,7 +24,7 @@ pub enum Algorithm {
     ContinuousBNA(VNeuron),
     Neat(Neat),
     NeatIndividual(Individual),
-    NeuralNetworek(NeuralNetwork),
+    NeuralNetwork(NeuralNetwork),
 }
 
 impl std::fmt::Display for Algorithm {
@@ -35,7 +35,7 @@ impl std::fmt::Display for Algorithm {
             Algorithm::DiscreteBNA(vneuron) => write!(f, "{}", vneuron),
             Algorithm::ContinuousBNA(vneuron) => write!(f, "{}", vneuron),
             Algorithm::Neat(neat) => write!(f, "{:?}", neat), // TODO: Implement Display for Neat
-            Algorithm::NeuralNetworek(network) => write!(f, "{:?}", network),
+            Algorithm::NeuralNetwork(network) => write!(f, "{:?}", network),
             Algorithm::NeatIndividual(individual) => write!(f, "{:?}", individual),
         }
     }
@@ -49,7 +49,7 @@ impl NeuroevolutionAlgorithm for Algorithm {
             Algorithm::DiscreteBNA(vneuron) => vneuron.optimize(problem, n_iters),
             Algorithm::ContinuousBNA(vneuron) => vneuron.optimize(problem, n_iters),
             Algorithm::Neat(neat) => neat.optimize(problem, n_iters),
-            Algorithm::NeuralNetworek(network) => network.optimize(problem, n_iters),
+            Algorithm::NeuralNetwork(network) => network.optimize(problem, n_iters),
             Algorithm::NeatIndividual(individual) => individual.optimize(problem, n_iters),
         }
     }
@@ -61,7 +61,7 @@ impl NeuroevolutionAlgorithm for Algorithm {
             Algorithm::DiscreteBNA(vneuron) => vneuron.optimize_cmaes(problem),
             Algorithm::ContinuousBNA(vneuron) => vneuron.optimize_cmaes(problem),
             Algorithm::Neat(neat) => neat.optimize_cmaes(problem),
-            Algorithm::NeuralNetworek(network) => network.optimize_cmaes(problem),
+            Algorithm::NeuralNetwork(network) => network.optimize_cmaes(problem),
             Algorithm::NeatIndividual(individual) => individual.optimize_cmaes(problem),
         }
     }
@@ -73,7 +73,7 @@ impl NeuroevolutionAlgorithm for Algorithm {
             Algorithm::DiscreteBNA(vneuron) => vneuron.evaluate(input),
             Algorithm::ContinuousBNA(vneuron) => vneuron.evaluate(input),
             Algorithm::Neat(neat) => neat.evaluate(input),
-            Algorithm::NeuralNetworek(network) => network.evaluate(input),
+            Algorithm::NeuralNetwork(network) => network.evaluate(input),
             Algorithm::NeatIndividual(individual) => individual.evaluate(input),
         }
     }
@@ -85,7 +85,7 @@ impl NeuroevolutionAlgorithm for Algorithm {
             Algorithm::DiscreteBNA(vneuron) => vneuron.optimization_step(problem),
             Algorithm::ContinuousBNA(vneuron) => vneuron.optimization_step(problem),
             Algorithm::Neat(neat) => neat.optimization_step(problem),
-            Algorithm::NeuralNetworek(network) => network.optimization_step(problem),
+            Algorithm::NeuralNetwork(network) => network.optimization_step(problem),
             Algorithm::NeatIndividual(individual) => individual.optimization_step(problem),
         }
     }