omaraflak

#include <stdio.h>
#include <stdlib.h>
#include <termios.h>
#include <time.h>
#include <stdbool.h>

const char BOMB = 'X';
const char EMPTY = 'E';
const char DISCOVERED = '0';
const char FLAG = 'F';

omaraflak

from keras.models import Sequential
from keras.layers.core import Dense
from keras.optimizers import SGD

import numpy as np

def main():
    X = np.array([[0,0],[0,1],[1,0],[1,1]])
    Y = np.array([[0],[1],[1],[0]])

omaraflak

#ifndef DEF_MATRIX
#define DEF_MATRIX

#include <vector>
#include <iostream>

/**
    Every method ends with "const" keyword which means that the object on which the method is called is never modified.
    Instead it will return a new Matrix.

omaraflak

#include "Matrix.h"
#include <assert.h>
#include <sstream>

Matrix::Matrix(){}

Matrix::Matrix(int height, int width)
{
    this->height = height;
    this->width = width;

omaraflak

#include <iostream>
#include <fstream>

void loadTraining(const char *filename, vector<vector<double> > &input, vector<vector<double> > &output)
{
    int trainingSize = 946;
    input.resize(trainingSize);
    output.resize(trainingSize);

    ifstream file(filename);

omaraflak

#include "Matrix.h"

Matrix X, W1, H, W2, Y, B1, B2, Y2, dJdB1, dJdB2, dJdW1, dJdW2;
double learningRate;

omaraflak

void init(int inputNeuron, int hiddenNeuron, int outputNeuron, double rate)
{
    learningRate = rate;

    W1 = Matrix(inputNeuron, hiddenNeuron);
    W2 = Matrix(hiddenNeuron, outputNeuron);
    B1 = Matrix(1, hiddenNeuron);
    B2 = Matrix(1, outputNeuron);

    W1 = W1.applyFunction(random);

omaraflak

#include <stdlib.h>
#include <time.h>

double random(double x)
{
    return (double)(rand() % 10000 + 1)/10000-0.5;
}

omaraflak

Matrix computeOutput(vector<double> input)
{
    X = Matrix({input}); // row matrix
    H = X.dot(W1).add(B1).applyFunction(sigmoid);
    Y = H.dot(W2).add(B2).applyFunction(sigmoid);
    return Y;
}

omaraflak

#include <cmath>
 
double sigmoid(double x)
{
    return 1/(1+exp(-x));
}