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Plain NN code setup
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@kubershahi
kubershahi committed Nov 15, 2021
1 parent 88101c0 commit bcc3ef1
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136 changes: 67 additions & 69 deletions nn.cpp
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Expand Up @@ -12,85 +12,83 @@ using namespace Eigen;

int main()
{
cout<<"Select Dataset (enter corresponding digit):"<<endl;
cout<<"\t [1] MNIST"<<endl;

int selection = 0;
cout<<"Enter selection: ";
cin>>selection;

int N_train; // Number of Training Samples
int N_test; // Number of Testing Samples
int d; // Number of Features
int m; // Number of classes
int B; // Batch Size
int NUM_EPOCHS; // Number of Epochs

IOFormat CleanFmt(4, 0, ", ", "\n", "[", "]"); // formatting option while printing Eigen Matrices

MatrixXd X_train,Y_train,Y_train_onehot, X_test,Y_test, Y_test_onehot;

if (selection==1)
{
N_train = 10000;
N_test = 1000;
d = 784;
m = 10;
B = 128;
NUM_EPOCHS = 1;

cout<<"Reading Data:"<<endl;
vector<vector<double> > X_train_load; // dim: 60000 x 784, 60000 training samples with 784 features
vector<double> Y_train_load; // dim: 60000 x 1 , the true label of each training sample

read_data("datasets/mnist/mnist_train.csv", X_train_load, Y_train_load);

MatrixXd X_train_1(N_train, d);
MatrixXd Y_train_1(N_train, 1);

for (int i = 0; i < N_train; i++)
{
X_train_1.row(i) = Map<RowVectorXd>(&X_train_load[i][0], d)/256.0;
Y_train_1.row(i) = Map<RowVectorXd>(&Y_train_load[i],1)/10.0;
}
cout<<"Select Dataset (enter corresponding digit):"<<endl;
cout<<"\t [1] MNIST"<<endl;

int selection = 0;
cout<<"Enter selection: ";
cin>>selection;

vector<vector<double> > X_test_load; // dim: 10000 x 784, 10000 testing samples with 784 features
vector<double> Y_test_load; // dim: 10000 x 1 , the true label of each testing sample
int N_train; // Number of Training Samples
int N_test; // Number of Testing Samples
int d; // Number of Features
int m; // Number of classes
int B; // Batch Size
int NUM_EPOCHS; // Number of Epochs

read_data("datasets/mnist/mnist_test.csv", X_test_load, Y_test_load); // for MNIST dataset
IOFormat CleanFmt(4, 0, ", ", "\n", "[", "]"); // formatting option while printing Eigen Matrices

MatrixXd X_test_1(N_test, d); // 1000, 784
MatrixXd Y_test_1(N_test, 1); // 1000, 1
MatrixXd X_train,Y_train,Y_train_onehot, X_test,Y_test, Y_test_onehot;

for (int i = 0; i < N_test; i++)
if (selection==1)
{
X_test_1.row(i) = Map<RowVectorXd>(&X_test_load[i][0], d)/256.0;
Y_test_1.row(i) = Map<RowVectorXd>(&Y_test_load[i],1)/10.0;
}
X_train = X_train_1;
Y_train = Y_train_1;
X_test = X_test_1;
Y_test = Y_test_1;
N_train = 10000;
N_test = 1000;
d = 784;
m = 10;
B = 128;
NUM_EPOCHS = 1;

cout<<"Reading Data:"<<endl;
vector<vector<double> > X_train_load; // dim: 60000 x 784, 60000 training samples with 784 features
vector<double> Y_train_load; // dim: 60000 x 1 , the true label of each training sample

read_data("datasets/mnist/mnist_train.csv", X_train_load, Y_train_load);

Y_train_onehot = onehot_Encoding(Y_train_1,m);
Y_test_onehot = onehot_Encoding(Y_test_1,m);
MatrixXd X_train_1(N_train, d);
MatrixXd Y_train_1(N_train, 1);

}
for (int i = 0; i < N_train; i++)
{
X_train_1.row(i) = Map<RowVectorXd>(&X_train_load[i][0], d)/256.0;
Y_train_1.row(i) = Map<RowVectorXd>(&Y_train_load[i],1)/10.0;
}


vector<vector<double> > X_test_load; // dim: 10000 x 784, 10000 testing samples with 784 features
vector<double> Y_test_load; // dim: 10000 x 1 , the true label of each testing sample

read_data("datasets/mnist/mnist_test.csv", X_test_load, Y_test_load); // for MNIST dataset

MatrixXd X_test_1(N_test, d); // 1000, 784
MatrixXd Y_test_1(N_test, 1); // 1000, 1

for (int i = 0; i < N_test; i++)
{
X_test_1.row(i) = Map<RowVectorXd>(&X_test_load[i][0], d)/256.0;
Y_test_1.row(i) = Map<RowVectorXd>(&Y_test_load[i],1)/10.0;
}
X_train = X_train_1;
Y_train = Y_train_1;
X_test = X_test_1;
Y_test = Y_test_1;

Y_train_onehot = onehot_Encoding(Y_train_1,m);
Y_test_onehot = onehot_Encoding(Y_test_1,m);

}

cout << X_train.rows() << "," << X_train.cols() << endl;
cout << X_test.rows() << "," << X_test.cols() << endl;
cout << Y_train.rows() << "," << Y_train.cols() << endl;
cout << Y_train_onehot.rows() << "," << Y_train_onehot.cols() << endl;
cout << Y_test.rows() << "," << Y_test.cols() << endl;
cout << Y_test_onehot.rows() << "," << Y_test_onehot.cols() << endl;
cout << X_train.rows() << "," << X_train.cols() << endl;
cout << X_test.rows() << "," << X_test.cols() << endl;
cout << Y_train.rows() << "," << Y_train.cols() << endl;
cout << Y_train_onehot.rows() << "," << Y_train_onehot.cols() << endl;
cout << Y_test.rows() << "," << Y_test.cols() << endl;
cout << Y_test_onehot.rows() << "," << Y_test_onehot.cols() << endl;


cout << Y_train.block(0,0,10,1) << endl;
cout << Y_train_onehot.block(0,0,10,10) << endl;
cout << Y_train.block(0,0,10,1) << endl;
cout << Y_train_onehot.block(0,0,10,10) << endl;

// cout << X_train.row(2).format(CleanFmt) <<endl;

return 0;
// cout << X_train.row(2).format(CleanFmt) <<endl;
return 0;
}
76 changes: 39 additions & 37 deletions read_data.cpp
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Expand Up @@ -20,48 +20,50 @@ using namespace std;
//function to read any dataset with all numerical values like MNIST dataset.
void read_data(string inputfile, vector<vector<double> > &X, vector<double> &Y) {

ifstream fin; // declaring the input file stream
fin.open(inputfile); // opening the inputfile
ifstream fin; // declaring the input file stream
fin.open(inputfile); // opening the inputfile

int l = 0; // declaring a integer to track the number of line
string line; // declaring a string to hold the read line of the input file
int l = 0; // declaring a integer to track the number of line
string line; // declaring a string to hold the read line of the input file

if (fin.is_open()) { // if the input file is open
cout << "File opened successfully " << endl;
if (fin.is_open()) // if the input file is open
{
cout << "File opened successfully " << endl;

while (getline(fin, line)){ // storing the line of input file on the variable line
l++; // increasing the line read counter
istringstream linestream(line); // converting the read line into an string stream
vector <double> row; // declaring a vector to store the current row
while (getline(fin, line)) // storing the line of input file on the variable line
{
l++; // increasing the line read counter
istringstream linestream(line); // converting the read line into an string stream
vector <double> row; // declaring a vector to store the current row

int val = 0; // declaring a variable to track the number of values in a row
while (linestream) { // while the string stream is not null
string row_value; // declaring a string to hold the row values
int val = 0; // declaring a variable to track the number of values in a row
while (linestream) { // while the string stream is not null
string row_value; // declaring a string to hold the row values

if (!getline(linestream, row_value, ',')) // storing the values from stream into row_value one by one
break; // at the end of row break the while loop
try {
if (val < 784) {
row.push_back(stod(row_value)); // pushing the current value into the row for X values
val++;
}
else if (val == 784) // pushing the current value into the Y for y values
{
Y.push_back(stod(row_value));
}
}
catch (const invalid_argument err) { // if there is a error catch the error and display it
cout << "Invalid value found in the file: " << inputfile << " line: " << l << " value: " << val << endl;
err.what();
}
}
if (!getline(linestream, row_value, ',')) // storing the values from stream into row_value one by one
break; // at the end of row break the while loop
try {
if (val < 784) {
row.push_back(stod(row_value)); // pushing the current value into the row for X values
val++;
}
else if (val == 784) // pushing the current value into the Y for y values
{
Y.push_back(stod(row_value));
}
}
catch (const invalid_argument err) { // if there is a error catch the error and display it
cout << "Invalid value found in the file: " << inputfile << " line: " << l << " value: " << val << endl;
err.what();
}
}

X.push_back(row); // pushing the row into the dataset
row.clear(); // clearing the row vector to store the next row
X.push_back(row); // pushing the row into the dataset
row.clear(); // clearing the row vector to store the next row
}
cout << "Lines read successfully: " << l << endl; // displaying the number or lines reads from the input file
}
else{
cout << "Unable to open the specified file " << endl; // output if file can't be opened
}
cout << "Lines read successfully: " << l << endl; // displaying the number or lines reads from the input file
}
else{
cout << "Unable to open the specified file " << endl; // output if file can't be opened
}
}
14 changes: 7 additions & 7 deletions utils.cpp
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Expand Up @@ -8,13 +8,13 @@ using namespace Eigen;

MatrixXd onehot_Encoding(MatrixXd X, int m)
{
MatrixXd res = MatrixXd::Zero(X.rows(),m);
MatrixXd res = MatrixXd::Zero(X.rows(),m);

for(int i =0; i < X.rows(); i++)
{
int index = X(i,0) * 10;
res(i,index) = (double) 1;
}
for(int i =0; i < X.rows(); i++)
{
int index = X(i,0) * 10;
res(i,index) = (double) 1;
}

return res;
return res;
}

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