convnet_cuda28.py 文件源码

def propagate(self, X, num_train=None, atype='relu'):
        """Propagate, return binary output of fake/real image"""     
        image_shape0=[X.shape[0], self.num_channels, self.D, self.D]
        ConX = X.reshape(image_shape0)
        H0 = self.L1.conv(ConX, atype=atype)
        H1 = self.L2.conv(H0, atype=atype)
        H1 = H1.flatten(2)

        H2 = activation_fn_th(T.dot(H1, self.W) + self.hbias, atype='tanh')
        y  = T.nnet.sigmoid(T.dot(H2, self.W_y))    

        return y