ToyGrad

A toy implementation of automatic differentiation, inspired by A. Karparthy's https://github.com/karpathy/micrograd

Basic Concepts

See more about Autograd's basic concpets, architecture, and implementation at the basic concept of automatic differentiation.

Demo

See demo in Jupyter notebook how to use ToyGrad.

class Model(Module):
    def __init__(self, input_features, output_features):
        super().__init__()

        self.layer1 = Linear(input_features, 8)
        self.layer2 = Linear(8, 4)
        self.output = Linear(4, output_features)

    def forward(self, X):
        X = self.layer1(X)
        X = [xi.relu() for xi in X]
        X = self.layer2(X)
        X = [xi.relu() for xi in X]
        output = self.output(X)
        return output