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

include/numerics/detail/standard_deviation_serial.h

@@ -0,0 +1,61 @@
+#pragma once
+
+#include <cstdint> //uint64_t
+#include <cmath> // std::abs
+
+#include "utils/vector.h"
+#include "utils/matrix.h"
+
+#include "numerics/mean.h"
+
+namespace numerics::detail{
+	
+		
+	template <typename T>
+	inline T standard_deviation_serial(const utils::Vector<T>& v) {
+		const uint64_t n = v.size();
+
+		if (n == 0){
+			throw std::runtime_error("std_serial: empty vector");
+		}
+
+		const T mean_value = numerics::mean(v);
+
+		T sum_squared_diff = T{0};
+
+
+		for (uint64_t i = 0; i < n; ++i){
+			const T diff = v[i] - mean_value;
+			sum_squared_diff += diff * diff;
+		}
+
+		const T variance = sum_squared_diff / static_cast<T>(n);
+
+		return numerics::sqrt(variance); 
+	}
+
+
+	template <typename T>
+	inline T standard_deviation_serial(const utils::Matrix<T>& A) {
+	    const uint64_t rows = A.rows();
+	    const uint64_t cols = A.cols();
+
+	    const T mean_value = numerics::mean(A);
+
+	    T sum_squared_diff =  T{0};
+
+
+		for (uint64_t i = 0; i < rows; ++i){
+			for (uint64_t j = 0; j < cols; ++j){
+				const T diff = A(i,j) - mean_value;
+				sum_squared_diff += diff * diff;
+			}
+		}
+		const T variance = sum_squared_diff / static_cast<T>(rows*cols);
+
+		return numerics::sqrt(variance);
+	}
+
+
+} // namespace numerics
+