train_mnist_feature_matching_tf.py 文件源码

def generator(input_latent):
    # input_latent = Input(batch_shape=noise_dim, dtype=im_dtype)
    with tf.variable_scope('Net_Gen') as scope:
        xx = layers.fully_connected(input_latent, num_outputs=500, activation_fn=None)
        xx = layers.batch_norm(xx)
        xx = tf.nn.relu(xx)
        xx = layers.fully_connected(xx, num_outputs=500, activation_fn=None)
        xx = layers.batch_norm(xx)
        xx = tf.nn.relu(xx)
        xx = layers.fully_connected(xx, num_outputs=28**2, activation_fn=None)
        xx = layers.batch_norm(xx)
        gen_dat = tf.nn.sigmoid(xx)

    return gen_dat

# specify discriminative model