Dropout Layer

Implemented rng::uniform and rng::binomial for single values, vectors and matrices. implemeted dropout layers and tested it. Also fixed the validation code. Before it used y one place, now it uses y_test as it should.

include/modules/neural_networks/layers/Dropout_Layer.h

@@ -0,0 +1,58 @@
+#pragma once
+
+#include "core/omp_config.h"
+
+#include "utils/vector.h"
+#include "utils/matrix.h"
+#include "random/random.h"
+
+
+namespace neural_networks{
+
+	template <typename T>
+	struct Dropout_Layer{
+
+		// Store rate, we invert it as for example for dropout
+		// of 0.1 we need a success rate of 0.9
+		T rate = T{0};
+		utils::Matrix<T> binary_mask;
+		
+		utils::Matrix<T> _inputs;
+		utils::Matrix<T> outputs;
+
+		utils::Matrix<T> dinputs;
+
+		
+		
+		// Default Constructor
+		Dropout_Layer() = default;
+
+		// Constructor
+    	Dropout_Layer(const T rate){
+    		this->rate = T{1} - rate;
+        	
+        }
+
+        void forward(const utils::Matrix<T>& inputs){
+        	// Save input values
+        	_inputs = inputs;
+
+        	// Generate binary_mask
+        	binary_mask = rng::binomial<T>(inputs.rows(), inputs.cols(), 1, rate);
+        	// Scale binary_mask
+        	binary_mask = numerics::div(binary_mask, rate);
+
+        	// Apply binary mask to output values
+        	outputs = numerics::mul(binary_mask, inputs);
+
+        }
+
+        void backward(const utils::Matrix<T>& dvalues){
+        	dinputs = numerics::mul(dvalues, binary_mask);
+        }
+
+	};
+
+
+
+} // end namespace neural_networks

include/modules/neural_networks/neural_networks.h

@@ -6,6 +6,7 @@
 
 
 #include "layers/Dense_Layer.h"
+#include "layers/Dropout_Layer.h"
 
 
 #include "activation_functions/Activation_ReLU.h"