micrograd_nn_demo.py

from micrograd.nn import Neuron, Layer, MLP

model = MLP(2, [16, 16, 1])  # 2-layer neural network

for k in range(100):
    # forward
    total_loss, acc = loss()
    
    # backward
    model.zero_grad()
    total_loss.backward()
    
    # update (sgd)
    learning_rate = 1.0 - 0.9*k/100
    for p in model.parameters():
        p.data -= learning_rate * p.grad