mnist_model.py 文件源码

def generator_graph(fake_imgs, units_size, out_size, alpha=0.01):
        # ????????????? ????scope
        with tf.variable_scope('generator'):
            # ????????
            layer = tf.layers.dense(fake_imgs, units_size)
            # leaky ReLU ????
            relu = tf.maximum(alpha * layer, layer)
            # dropout ?????
            drop = tf.layers.dropout(relu, rate=0.2)
            # logits
            # out_size??????size??
            logits = tf.layers.dense(drop, out_size)
            # ???? ??????????? ? ????????
            # ??tanh????sigmoid???
            # ????(-1, 1) ??sigmoid??[0, 1]
            outputs = tf.tanh(logits)
            return logits, outputs