#include "main.h"
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <err.h>

// Function prototypes
void getvalues(char filename[], double **HiddenWeights, double *HiddenBiases, double **FinalOutputWeights, double *FinalOutputBiases);
double sigmoid(double x);
double sigmoid_derivative(double x);

int main(int argc, char *argv[]) {
    // Allocate memory for weights and biases
    double **HiddenWeights = (double **)malloc(2 * sizeof(double *));
    for (int i = 0; i < 2; i++) {
        HiddenWeights[i] = (double *)malloc(2 * sizeof(double));
    }
    double *HiddenBiases = (double *)malloc(2 * sizeof(double));
    double **FinalOutputWeights = (double **)malloc(2 * sizeof(double *));
    for (int i = 0; i < 2; i++) {
        FinalOutputWeights[i] = (double *)malloc(1 * sizeof(double));
    }
    double *FinalOutputBiases = (double *)malloc(1 * sizeof(double));

    // Load weights and biases from CSV file
    getvalues("weights.csv", HiddenWeights, HiddenBiases, FinalOutputWeights, FinalOutputBiases);
    if (argc < 2) {
        errx(0, "No arguments provided. Usage: %s <input1> <input2>", argv[0]);
        return EXIT_FAILURE;
    }
    if (argc != 3) {
        errx(0, "Usage: %s <input1> <input2>", argv[0]);
        return EXIT_FAILURE;
    }

    double input1 = atof(argv[1]);
    double input2 = atof(argv[2]);
    // Prompt user for input values
    // double input1, input2;
    // printf("Enter two values to compute XOR: ");
    // scanf("%lf %lf", &input1, &input2);

    // Perform forward pass
    double hiddenLayer[2];
    double outputLayer[1];

    // Compute hidden layer activation
    for (int j = 0; j < 2; j++) {
        double activation = HiddenBiases[j];
        activation += input1 * HiddenWeights[0][j];
        activation += input2 * HiddenWeights[1][j];
        hiddenLayer[j] = sigmoid(activation);
    }

    // Compute output layer activation
    for (int j = 0; j < 1; j++) {
        double activation = FinalOutputBiases[j];
        activation += hiddenLayer[0] * FinalOutputWeights[0][j];
        activation += hiddenLayer[1] * FinalOutputWeights[1][j];
        outputLayer[j] = sigmoid(activation);
    }

    // Print the result
    printf("Input: %g %g    Predicted Output: %g     Output round: %g\n", input1, input2, outputLayer[0], round(outputLayer[0]));

    // Free allocated memory
    for (int i = 0; i < 2; i++) {
        free(HiddenWeights[i]);
        free(FinalOutputWeights[i]);
    }
    free(HiddenWeights);
    free(HiddenBiases);
    free(FinalOutputWeights);
    free(FinalOutputBiases);

    return 0;
}

void getvalues(char filename[], double **HiddenWeights, double *HiddenBiases, double **FinalOutputWeights, double *FinalOutputBiases) {
    FILE *fp = fopen(filename, "r");
    if (fp == NULL) {
        errx(EXIT_FAILURE, "Could not open file %s. Train the model first by executing ./main", filename);
    }
    for (int i = 0; i < 2; i++) {
        for (int j = 0; j < 2; j++) {
            fscanf(fp, "%lf,", &HiddenWeights[i][j]);
        }
    }
    for (int i = 0; i < 2; i++) {
        fscanf(fp, "%lf,", &HiddenBiases[i]);
    }
    for (int i = 0; i < 2; i++) {
        for (int j = 0; j < 1; j++) {
            fscanf(fp, "%lf,", &FinalOutputWeights[i][j]);
        }
    }
    for (int i = 0; i < 1; i++) {
        fscanf(fp, "%lf,", &FinalOutputBiases[i]);
    }
    fclose(fp);
}

double sigmoid(double x) {
    return 1.0 / (1.0 + exp(-x));
}

double sigmoid_derivative(double x) {
    return x * (1.0 - x);
}