Neural Network

Started on implementing neural network from NNFS. I've done ReLU and stopped at p.104. Softmax is not ready.

include/utils/matrix.h

@@ -2,12 +2,16 @@
 #define _matrix_n_
 
 #include "./utils/vector.h"
+#include "./utils/random.h"
 
 #ifdef _OPENMP
 	#include <omp.h>
 #endif
 
 
+#include <initializer_list>
+
+
 #include <iomanip>
 
 namespace utils{
@@ -25,6 +29,72 @@ public:
 	    : rows_(rows), cols_(cols), data_(rows * cols, value) {}
 
 
+		// Construct from list-of-lists:
+		// utils::Mf A{{1,2,3}, {4,5,6}};
+		Matrix(std::initializer_list<std::initializer_list<T>> init) {
+		    rows_ = static_cast<uint64_t>(init.size());
+		    if (rows_ > 0) {
+			    cols_ = static_cast<uint64_t>(init.begin()->size());
+			} else {
+			    cols_ = 0;
+			}
+
+		    // Validate all rows have the same length
+		    for (const auto& row : init) {
+		        if (row.size() != cols_) {
+		            throw std::runtime_error("Matrix(list of lists): ragged rows");
+		        }
+		    }
+
+		    data_.resize(rows_ * cols_);
+			uint64_t r = 0;
+			for (uint64_t i = 0; i < init.size(); ++i, ++r){
+			    const std::initializer_list<T>& row = *(init.begin() + i);
+
+			    uint64_t c = 0;
+			    for (uint64_t j = 0; j < row.size(); ++j, ++c){
+			        const T& val = *(row.begin() + j);
+			        data_[r * cols_ + c] = val;
+			    }
+			}
+		}
+
+
+		// Assign from list-of-lists after default construction:
+		// utils::Md M; M = {{1,2},{3,4}};
+		Matrix& operator=(std::initializer_list<std::initializer_list<T>> init) {
+		    // Set sizes
+		    rows_ = static_cast<uint64_t>(init.size());
+		    if (rows_ > 0) {
+		        cols_ = static_cast<uint64_t>((init.begin())->size());
+		    } else {
+		        cols_ = 0;
+		    }
+
+		    // Validate: all rows must have same length
+		    for (uint64_t i = 0; i < rows_; ++i) {
+		        const std::initializer_list<T>& row = *(init.begin() + i);
+		        if (row.size() != cols_) {
+		            throw std::runtime_error("Matrix(list of lists): ragged rows");
+		        }
+		    }
+
+		    // Allocate storage
+		    data_.resize(rows_ * cols_);
+
+		    // Copy data row by row
+		    for (uint64_t i = 0; i < rows_; ++i) {
+		        const std::initializer_list<T>& row = *(init.begin() + i);
+		        for (uint64_t j = 0; j < cols_; ++j) {
+		            const T& val = *(row.begin() + j);
+		            data_[i * cols_ + j] = val;
+		        }
+		    }
+
+		    return *this;
+		}
+
+
 		//#            MATRIX: basic properties            #
 	    uint64_t rows() const noexcept {return rows_;}
 	    uint64_t cols() const noexcept {return cols_;}
@@ -45,6 +115,20 @@ public:
 
 		}
 
+		void random(uint64_t rows, uint64_t cols, const T& lower, const T& higher){
+			rows_ = rows;
+			cols_ = cols;
+			data_.resize(rows_*cols_, 0);
+
+		    // Copy data row by row
+		    for (uint64_t i = 0; i < rows_; ++i) {
+		        for (uint64_t j = 0; j < cols_; ++j) {
+		            data_[i * cols_ + j] = utils::random(lower, higher);
+		        }
+		    }
+
+		}
+
 
 		//#            MATRIX: row helpers (copy out)            #
 		// Read whole row as an owning Vector<T>