fix

CSharp/Neural.cs

@@ -141,12 +141,12 @@ public void Train (double[] input, double[] y, double lr)
             }
         }
 
-        for (int c = 0; c < GradOutput.Length; c++)
+        for (int c = 0; c < Network.OutputCount; c++)
         {
             Network.BiasesOutput[c] -= lr * GradOutput[c];
         }
 
-        for (int c = 0; c < GradHidden.Length; c++)
+        for (int c = 0; c < Network.HiddenCount; c++)
         {
             Network.BiasesHidden[c] -= lr * GradHidden[c];
         }

Cpp/neural.cpp

@@ -135,11 +135,11 @@ void Trainer::Train(const Vector& input, const Vector& y, double lr) {
         }
     }
 
-    for (size_t c = 0; c < gradOutput.size(); c++) {
+    for (size_t c = 0; c < network.outputCount; c++) {
         network.biasesOutput[c] -= lr * gradOutput[c];
     }
 
-    for (size_t c = 0; c < gradHidden.size(); c++) {
+    for (size_t c = 0; c < network.hiddenCount; c++) {
         network.biasesHidden[c] -= lr * gradHidden[c];
     }
 }

FSharp/Neural.fs

@@ -100,8 +100,8 @@ type Trainer(network, n_inputs, n_hidden, n_outputs) =
       for c = 0 to n_hidden - 1 do
         network.WeightsHidden[r * n_hidden + c] <- network.WeightsHidden[r * n_hidden + c] - lr * grad_hidden[c] * input[r]
 
-    for c = 0 to grad_output.Length - 1 do
+    for c = 0 to n_outputs - 1 do
       network.BiasesOutput[c] <- network.BiasesOutput[c] - lr * grad_output[c]
 
-    for c = 0 to grad_hidden.Length - 1 do
+    for c = 0 to n_hidden - 1 do
       network.BiasesHidden[c] <- network.BiasesHidden[c] - lr * grad_hidden[c]

Rust/src/neural.rs

@@ -160,11 +160,11 @@ impl Trainer {
             }
         }
 
-        for c in 0..self.grad_output.len() {
+        for c in 0..self.network.n_outputs {
             self.network.biases_output[c] -= lr * self.grad_output[c];
         }
 
-        for c in 0..self.grad_hidden.len() {
+        for c in 0..self.network.n_hidden {
             self.network.biases_hidden[c] -= lr * self.grad_hidden[c];
         }
     }