op.py 文件源码

def sgd(lr, tparams, grads, inp, cost, extra_ups=[], extra_outs=[],
        exclude_params=set([])):
    '''Stochastic gradient descent'''
    gshared = [theano.shared(p.get_value() * 0., name='%s_grad'%k)
               for k, p in tparams.iteritems()]

    gsup = [(gs, g) for gs, g in zip(gshared, grads)]

    f_grad_shared = theano.function(
        inp, [cost]+extra_outs, updates=gsup+extra_ups, profile=profile)

    pup = [(p, p - lr * g) for p, g in zip(tools.itemlist(tparams), gshared)
        if p.name not in exclude_params]

    if not isinstance(lr, list): lr = [lr]
    f_update = theano.function(lr, [], updates=pup, profile=profile)

    return f_grad_shared, f_update