DoubleFlow

DoubleFlow is an automatic differentiation library. It is highly inspired by TensorFlow, but it only works with usual double variables, not tensors :(

It implements 14 mathematical operations:

• add
• sub
• mul
• div
• log
• exp
• pow
• sqrt
• sin
• cos
• tan
• asin
• acos
• atan

Example

// you first need to declare a Graph variable
Graph g;

auto x1 = g.variable(3);  // creates a variable with initial value 3
auto x2 = g.variable(2);

auto y = g.mul(x1, x2); // creates a variable such that y = x1 * x2

g.run(y); // runs the graph with y as the output

cout << y->result << endl; // prints 6
cout << x1->grad << endl; // prints dy/dx1, which is equal to x2

// you can update the variables and run the graph again

x1->set(4);
x2->set(0.5);

g.run(y);

cout << y->result << endl;
cout << x1->grad << endl; 

There is also a demo which trains a basic logistic regression model.