gan.py 文件源码

def generator(self, opts, noise, is_training, reuse=False):

        with tf.variable_scope("GENERATOR", reuse=reuse):

            h0 = ops.linear(opts, noise, 100, scope='h0_lin')
            h0 = ops.batch_norm(opts, h0, is_training, reuse, scope='bn_layer1', scale=False)
            h0 = tf.nn.softplus(h0)
            h1 = ops.linear(opts, h0, 100, scope='h1_lin')
            h1 = ops.batch_norm(opts, h1, is_training, reuse, scope='bn_layer2', scale=False)
            h1 = tf.nn.softplus(h1)
            h2 = ops.linear(opts, h1, 28 * 28, scope='h2_lin')
            # h2 = ops.batch_norm(opts, h2, is_training, reuse, scope='bn_layer3')
            h2 = tf.reshape(h2, [-1, 28, 28, 1])

        if opts['input_normalize_sym']:
            return tf.nn.tanh(h2)
        else:
            return tf.nn.sigmoid(h2)