Bausager
88227a38fc
Started on implementing neural network from NNFS. I've done ReLU and stopped at p.104. Softmax is not ready.
61 lines
1.4 KiB
C++
61 lines
1.4 KiB
C++
#pragma once
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#include "./core/omp_config.h"
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#include "./utils/matrix.h"
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#include "./utils/vector.h"
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#include "./utils/random.h"
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//#include <math.h>
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namespace neural_networks{
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template <typename T>
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void create_spital_data(const uint64_t samples, const uint64_t classes, utils::Matrix<T>& X, utils::Vector<T>& y) {
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const uint64_t rows = samples*classes;
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T r, t;
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uint64_t row_idx;
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if ((rows != X.rows()) || (X.cols() != 2)){
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X.resize(samples*classes, 2);
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}
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if (rows != y.size()){
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y.resize(rows);
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}
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for (uint64_t i = 0; i < classes; ++i){
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for (uint64_t j = 0; j < samples; ++j){
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r = static_cast<T>(j)/static_cast<T>(samples);
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t = static_cast<T>(i)*4.0 + (4.0+r);
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row_idx = (i*samples) + j;
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X(row_idx, 0) = r*std::cos(t*2.5) + utils::random(T{-0.15}, T{0.15});
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X(row_idx, 1) = r*std::sin(t*2.5) + utils::random(T{-0.15}, T{0.15});
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y[row_idx] = i;
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}
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}
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/*
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utils::Matrix<T> X(static_cast<uint64_t>(samples*classes), 3, T{0});
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const uint64_t rows = A.rows();
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const uint64_t cols = A.cols();
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if (rows != x.size()) {
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throw std::runtime_error("inplace_matadd_colvec: dimension mismatch");
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}
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for (uint64_t i = 0; i < cols; ++i) {
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for (uint64_t j = 0; j < rows; ++j) {
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A(j, i) += x[j];
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}
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}*/
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}
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} // end namesoace NN
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