layers.py 文件源码

def __init__(self, input, n_in, n_out, prob_drop=0.5, verbose=False):

        self.verbose = verbose
        self.prob_drop = prob_drop
        self.prob_keep = 1.0 - prob_drop
        self.flag_on = theano.shared(np.cast[theano.config.floatX](1.0))
        self.flag_off = 1.0 - self.flag_on

        seed_this = DropoutLayer.seed_common.randint(0, 2**31-1)
        mask_rng = theano.tensor.shared_randomstreams.RandomStreams(seed_this)
        self.mask = mask_rng.binomial(n=1, p=self.prob_keep, size=input.shape)

        self.output = \
            self.flag_on * T.cast(self.mask, theano.config.floatX) * input + \
            self.flag_off * self.prob_keep * input

        DropoutLayer.layers.append(self)

        if self.verbose: 
            print 'dropout layer with P_drop: ' + str(self.prob_drop)