simplest form of rprop update rule

rprop.py

for t in range(num_interations):
    dw[t] = compute_gradient(x, y)
    
    if dw[t] * dw[t - 1] > 0:
        step_size = min(step_size * incFactor, step_size_max)
    elif dw[t] * dw[t - 1] < 0:
        step_size = max(step_size * decFactor, step_size_min)
    
    w[t] = w[t - 1] - sign(dw[t]) * step_size