Starting on the model.h, but need to make layer structs and structs for loss and optimizers

include/random/detail/normal_serial.h

@@ -0,0 +1,57 @@
+#pragma once
+
+#include "random/engine.h"
+
+#include <random>
+//#include <type_traits>
+
+#include "utils/matrix.h"
+#include "utils/vector.h"
+
+namespace rng::detail {
+
+	//
+	// Base functions int
+	//
+    template <typename T>
+    typename std::enable_if<std::is_integral<T>::value, T>::type
+    normal_serial(const T mean, const T stddev) {
+        std::normal_distribution<T> dist(mean, stddev);
+        return dist(rng::engine());
+    }
+
+	//
+	// Base functions float
+	//
+    template <typename T>
+    typename std::enable_if<std::is_floating_point<T>::value, T>::type
+    normal_serial(const T mean, const T stddev) {
+        std::normal_distribution<T> dist(mean, stddev);
+        return dist(rng::engine());
+    }
+
+    template <typename T>
+    utils::Vector<T> normal_serial(const uint64_t size, const T mean, const T stddev){
+    	utils::Vector<T> v(size);
+    	for (uint64_t i = 0; i < size; ++i){
+    		v[i] = normal_serial(mean, stddev);
+    	}
+    	return v;
+    }
+
+    template <typename T>
+    utils::Matrix<T> normal_serial(const uint64_t rows, const uint64_t cols, const T mean, const T stddev){
+    	utils::Matrix<T> A(rows, cols);
+    	for (uint64_t i = 0; i < rows; ++i){
+    		for (uint64_t j = 0; j < cols; ++j){
+    			A(i,j) = normal_serial(mean, stddev);
+    		}
+    	}
+    	return A;
+    }
+
+
+
+
+
+}