convolution_rbm.py 文件源码

def propup(self, vis):
        """
        This function propagates the visible units activation upwards to the hidden units
        Eq.(7)
        :param vis: Variable Matrix(batch_size, in_channels, image_height, image_width)
                    - given v_sample
        :return: Variable Matrix(batch_size, out_channels, image_height_out, image_width_out)
                 - probability for each hidden units to be h_i=1
        """
        # conv.W: Matrix(out_channels, in_channels, filter height=ksize, filter width=ksize)
        # conv.b: Vec   (out_channels, )
        if self.real == 0:
            pre_sigmoid_activation = self.conv(vis)
        else:
            pre_sigmoid_activation = self.conv(vis / self.std_ch)
        # F.matmul(vis, self.conv.W, transb=True) + F.broadcast_to(self.conv.b, (vis.data.shape[0], self.n_hidden))
        return F.sigmoid(pre_sigmoid_activation)