# Feed forward
out = conv.forward((image / 255) - 0.5)
out = pool.forward(out)
out = softmax.forward(out)

# Calculate initial gradient
gradient = np.zeros(10)
# ...

# Backprop
gradient = softmax.backprop(gradient)
gradient = pool.backprop(gradient)
gradient = conv.backprop(gradient)