OCR Memory Usage

[hmwildermuth]

I was trying to make an OCR neural network using the MNIST OCR image library, however my process was killed every time I ran it by a kernel process called the OOM Killer. It kills processes which use too much memory. I am not sure whether this is because of my code, or something about the backpropagation code. Either way, any help would be appreciated.

also, just to note, when I run the program with the learning sample size cut down to only 250 images, it works, but above 500 it fails.

The C++ File:

#include "ocr.h"

int main(int argc, char const *argv[]) {
    std::string lbels = "train-labels.idx1-ubyte";
    std::string imges = "train-images.idx3-ubyte";
    std::string outputFilename = (argc > 1) ? argv[1] : "ocr.txt";

    int mgicNum;
    int sizeNum;

    std::cout << "Loading images from files..." << std::endl;

    auto inputArr = read_mnist_images(imges, mgicNum, sizeNum);
    auto outputArr = read_mnist_labels(lbels, mgicNum);

    net::NeuralNet neuralNetwork = net::NeuralNet(sizeNum, 10, 1, sizeNum, "sigmoid");

    std::vector< std::vector<double> > input;
    std::vector< std::vector<double> > correctOutput;

    std::cout << "Loading into vector...\n";
    for (size_t i = 0; i < mgicNum; i++) {
        std::vector<double> imgeArr;
        for (size_t j = 0; j < sizeNum; j++) {
            imgeArr.push_back(double(inputArr[i][j])/double(255));
        }
        //std::cout << imgeArr.size() << "; " << sizeNum << "\n";
        input.push_back(imgeArr);
        correctOutput.push_back(digits(outputArr[i]));
    }

    std::cout << "Done with loading.\n";

    std::cout << "Freeing memory..." << std::endl;

    delete [] inputArr; // <- Is this how you use delete? idk
    delete [] outputArr;

    // free(inputArr);
    // free(outputArr);

    std::cout << "Done with freeing memory." << std::endl;

    std::cout << "Supposed # of samples: " << mgicNum << std::endl;
    std::cout << "Actual # of samples: " << input.size() << std::endl;
    net::Backpropagation backprop = net::Backpropagation(0.01, 0.9, 0.1, 10);
    std::cout << "Inputs: " << neuralNetwork.numberOfInputs() << std::endl;
    std::cout << "Hidden: " << neuralNetwork.numberOfHiddenNeurons() << std::endl;
    std::cout << "Outputs: " << neuralNetwork.numberOfOutputs() << std::endl;

    std::cout << "Input array: " << input[0].size() << std::endl;
    std::cout << "Correct array: " << correctOutput[0].size() << std::endl;

    if (input.size() != correctOutput.size()) {
        throw std::runtime_error("Differing sizes between two of the same thing");
    }

    /* To decrease memory usage

    #define RESIZE_Value 500

    // Works at 100, 250
    // Killed at 500 and above

    std::cout << "Resizing arrays to " << RESIZE_Value << " each..." << std::endl;

    input.resize(RESIZE_Value);
    correctOutput.resize(RESIZE_Value);

    // */

    std::cout << "Beginning training..." << std::endl;

    backprop.train(&neuralNetwork, input, correctOutput);

    std::cout << "Done training. Storing..." << std::endl;

    std::ofstream myfile;
    myfile.open(outputFilename);
    neuralNetwork.store(&myfile);
    myfile.close();

    std::cout << "Done storing to output file '" << outputFilename << "'. Testing..." << std::endl;

    #define TEST_INDEX 23 // Random test index

    std::cout << "Test: " << findTop(neuralNetwork.getOutput(input[TEST_INDEX])) << std::endl;
    std::cout << "Correct answer: " << findTop(correctOutput[TEST_INDEX]) << std::endl;

    return 0;
}

The header file which contains functions for loading test images and picking highest members of arrays: (The MNIST functions I copied from somewhere else)

#include "include/Fido.h"
#ifndef OCR
#define OCR

typedef unsigned char uchar;

uchar** read_mnist_images(std::string full_path, int& number_of_images, int& image_size) {
    auto reverseInt = [](int i) {
        unsigned char c1, c2, c3, c4;
        c1 = i & 255, c2 = (i >> 8) & 255, c3 = (i >> 16) & 255, c4 = (i >> 24) & 255;
        return ((int)c1 << 24) + ((int)c2 << 16) + ((int)c3 << 8) + c4;
    };

    std::ifstream file(full_path);

    if(file.is_open()) {
        int magic_number = 0, n_rows = 0, n_cols = 0;

        file.read((char *)&magic_number, sizeof(magic_number));
        magic_number = reverseInt(magic_number);

        if(magic_number != 2051) throw std::runtime_error("Invalid MNIST image file!");

        file.read((char *)&number_of_images, sizeof(number_of_images)), number_of_images = reverseInt(number_of_images);
        file.read((char *)&n_rows, sizeof(n_rows)), n_rows = reverseInt(n_rows);
        file.read((char *)&n_cols, sizeof(n_cols)), n_cols = reverseInt(n_cols);

        image_size = n_rows * n_cols;

        uchar** _dataset = new uchar*[number_of_images];
        for(int i = 0; i < number_of_images; i++) {
            _dataset[i] = new uchar[image_size];
            file.read((char *)_dataset[i], image_size);
        }
        return _dataset;
    } else {
        throw std::runtime_error("Cannot open file `" + full_path + "`!");
    }
}

uchar* read_mnist_labels(std::string full_path, int& number_of_labels) {
    auto reverseInt = [](int i) {
        unsigned char c1, c2, c3, c4;
        c1 = i & 255, c2 = (i >> 8) & 255, c3 = (i >> 16) & 255, c4 = (i >> 24) & 255;
        return ((int)c1 << 24) + ((int)c2 << 16) + ((int)c3 << 8) + c4;
    };

    typedef unsigned char uchar;

    std::ifstream file(full_path);

    if(file.is_open()) {
        int magic_number = 0;
        file.read((char *)&magic_number, sizeof(magic_number));
        magic_number = reverseInt(magic_number);

        if(magic_number != 2049) throw std::runtime_error("Invalid MNIST label file!");

        file.read((char *)&number_of_labels, sizeof(number_of_labels)), number_of_labels = reverseInt(number_of_labels);

        uchar* _dataset = new uchar[number_of_labels];
        for(int i = 0; i < number_of_labels; i++) {
            file.read((char*)&_dataset[i], 1);
        }
        return _dataset;
    } else {
        throw std::runtime_error("Unable to open file `" + full_path + "`!");
    }
}

std::vector<double> digits(uchar j) {
    std::vector<double> v;
    for (size_t i = 0; i < 10; i++) {
        if (j == i) {
            v.push_back(1);
        } else {
            v.push_back(0);
        }
    }
    return v;
}

int findTop(std::vector<double> v) {
    int best = -1;
    double top = -1.0;
    for (size_t i = 0; i < 10; i++) {
        if (v[i] > top) {
            best = i;
            top = v[i];
        }
    }
    return best;
}

#endif

[hmwildermuth]

Here is also some code I wrote to run tests on the outputted network: (Uses the same ocr.h)

#include "ocr.h"

void printUsage(char const * firstarg) {
    std::cout << "Usage:" << std::endl;
    std::cout << "\t" << firstarg << " [-v] [-c NUMBER] <filename>" << std::endl;
    std::cout << "Possible arguments:" << std::endl;
    std::cout << "\t-v: Verbose mode" << std::endl;
    std::cout << "\t\tIf not specified, defaults to off" << std::endl;
    std::cout << "\t-c: Count (number of tests run)" << std::endl;
    std::cout << "\t\tIf not specified, defaults to all tests (10,000)" << std::endl;
}

void printScore(int right, int wrong) {
    std::cout << "Final Results:" << std::endl;
    std::cout << "\tCorrect: " << right << std::endl;
    std::cout << "\tWrong: " << wrong << std::endl;
    std::cout << "\tTests: " << right+wrong << std::endl;
    std::cout << "\tPercent Correct: " << double(right)/double(right+wrong)*100.0 << "%" << std::endl;
}

int main(int argc, char const *argv[]) {
    std::string inputFilename = "ocr.txt";
    bool verbose = false;
    bool setFilename = false;
    int checkSize = -100;
    if (argc > 1) {
        for (size_t i = 1; i < argc; i++) {
            if (!strcmp(argv[i], "-v")) {
                verbose = true;
            } else if (!strcmp(argv[i], "-c")) {
                i++;
                checkSize = atoi(argv[i]);
            } else {
                setFilename = true;
                inputFilename = argv[i];
            }
        }
    }
    if (!setFilename) {
        printUsage(argv[0]);
        return -1;
    }

    std::ifstream myfile;
    myfile.open(inputFilename);
    net::NeuralNet network = net::NeuralNet(&myfile);
    myfile.close();

    std::string lbels = "t10k-labels.idx1-ubyte";
    std::string imges = "t10k-images.idx3-ubyte";

    int mgicNum;
    int sizeNum;

    std::cout << (verbose ? "Loading images from files...\n" : "");

    auto inputArr = read_mnist_images(imges, mgicNum, sizeNum);
    auto outputArr = read_mnist_labels(lbels, mgicNum);

    net::NeuralNet neuralNetwork = net::NeuralNet(sizeNum, 10, 1, sizeNum, "sigmoid");

    std::vector< std::vector<double> > input;
    std::vector< std::vector<double> > correctOutput;

    std::cout << (verbose ? "Loading into vector...\n" : "");
    for (size_t i = 0; i < mgicNum; i++) {
        std::vector<double> imgeArr;
        for (size_t j = 0; j < sizeNum; j++) {
            imgeArr.push_back(double(inputArr[i][j])/double(255));
        }
        //std::cout << imgeArr.size() << "; " << sizeNum << "\n";
        input.push_back(imgeArr);
        correctOutput.push_back(digits(outputArr[i]));
    }

    std::cout << (verbose ? "Done with loading.\n" : "");

    std::cout << (verbose ? "Freeing memory...\n" : "");

    delete [] inputArr; // <- Is this how you use delete? idk
    delete [] outputArr;

    // free(inputArr);
    // free(outputArr);

    std::cout << (verbose ? "Done with freeing memory.\n\n" : "");

    if (checkSize == -100) {
        checkSize = correctOutput.size();
    } else if (checkSize > correctOutput.size()) {
        throw std::runtime_error("Number of tests wanted is larger than actual number of tests: " + std::to_string(checkSize));
    } else if (checkSize < 1) {
        throw std::runtime_error("Invalid number for count: " + std::to_string(checkSize));
    }

    int wrong = 0;
    int right = 0;
    for (size_t i = 0; i < checkSize; i++) {
        int out = findTop(neuralNetwork.getOutput(input[i]));
        int real = findTop(correctOutput[i]);
        if ( out != real ) {
            if (verbose) {
                std::cout << "Failed test #" << i << ":"<< std::endl;
                std::cout << "\tTest answer: " << out << std::endl;
                std::cout << "\tCorrect answer: " << real << std::endl;
            }
            wrong++;
        } else {
            right++;
        }
    }

    printScore(right, wrong);

    return 0;
}

[renatosc]

Did you solve it? I am having the same issue... My program keeps getting killed by the system.