layers.py 文件源码

def get_output_for(self, inputs, **kwargs):
        vals, ref = inputs

        def filt(V, R):
            if self.norm_type is not None:
                o = tt.ones((1, V.shape[1], V.shape[2]), np.float32)
                norm = gaussian_filter(R, o, self.kern_std, self.ref_dim)
                norm = tt.sqrt(norm) if self.norm_type == "sym" else norm
                norm += 1e-8

            V = V / norm if self.norm_type in ["pre", "sym"] else V
            F = gaussian_filter(R, V, self.kern_std)
            return F / norm if self.norm_type in ["post", "sym"] else F

        filtered = theano.scan(fn=filt, sequences=[vals, ref],
                               outputs_info=None)[0]
        return filtered