layers.py 文件源码

def shared_dropout_layer(shape, use_noise, trng, value, scaled=True):
    #re-scale dropout at training time, so we don't need to at test time
    if scaled:
        proj = tensor.switch(
            use_noise,
            trng.binomial(shape, p=value, n=1,
                                        dtype='float32')/value,
            theano.shared(numpy.float32(1.)))
    else:
        proj = tensor.switch(
            use_noise,
            trng.binomial(shape, p=value, n=1,
                                        dtype='float32'),
            theano.shared(numpy.float32(value)))
    return proj


# feedforward layer: affine transformation + point-wise nonlinearity