model_mmd.py 文件源码

def generator_mnist(self, z, is_train=True, reuse=False):
        if reuse:
            tf.get_variable_scope().reuse_variables()
        h0 = linear(z, 64, 'g_h0_lin', stddev=self.config.init)
        h1 = linear(tf.nn.relu(h0), 256, 'g_h1_lin', stddev=self.config.init)
        h2 = linear(tf.nn.relu(h1), 256, 'g_h2_lin', stddev=self.config.init)
        h3 = linear(tf.nn.relu(h2), 1024, 'g_h3_lin', stddev=self.config.init)
        h4 = linear(tf.nn.relu(h3), 28 * 28 * 1, 'g_h4_lin', stddev=self.config.init)

        return tf.reshape(tf.nn.sigmoid(h4), [self.batch_size, 28, 28, 1])