nnoptimizer.py 文件源码

def EGD(cost, params, learning_rate = 0.33, constraint = 1.0):

    updates = OrderedDict()

    grads = T.grad(cost, params)
    U = T.constant(constraint)

    #first half of params
    rw_pos = T.exp(-learning_rate * U * grads[0])
    rb_pos = T.exp(-learning_rate * U * grads[1])

    #second half
    rw_neg = 1/rw_pos
    rb_neg = 1/rb_pos

    rs = [rw_pos, rb_pos, rw_neg, rb_neg]

    partition = T.sum(params[0]*rs[0]) + T.sum(params[1]*rs[1]) + T.sum(params[2]*rs[2]) + T.sum(params[3]*rs[3])

    for param, r in zip(params, rs):
        updates[param] = U*param*r/partition

    return updates