layers.py 文件源码

def get_output_for(self,input, **kwargs):
        if input.ndim > 2:
            input = input.flatten(2)
        activation = T.dot(input, self.W*self.weights_mask)
        if self.b is not None:
            activation = activation + self.b.dimshuffle('x', 0)
        return self.nonlinearity(activation)


# Stripped-Down Direct Input masked layer: Combine this with ESL and a masked layer to get a true DIML.
# Consider making this a simultaneous subclass of MaskedLayer and elemwise sum layer for cleanliness
#  adopted from M.Germain