Question

我编写了代码，我试图让它在几周内完成，问题在于输入更新无法正常工作。

     with tf.Session() as sess:
        sess.run(tf.global_variables_initializer())
    ### END CODE HERE ###

    # Run the noisy input image (initial generated image) through the    model. Use assign().
    ### START CODE HERE ### (1 line)
    init_fn(sess)
    sess.run(input_img.assign(inputo))

    ### END CODE HERE ###

    for i in range(num_iterations):

        generated_image,_ = sess.run([input_img,train_step])

        if i%20 == 0:
            Jt, Jc, Js = sess.run([Jolo, content_loss, style_losss])

模型定义在本节中完成，我已经定义了共享变量，并从tf.slim加载了初始v1模型

  with tf.variable_scope('input') as scope:
 input_img = tf.get_variable('in_img',shape=([1, img_height, img_width, 3]),dtype=tf.float32,initializer=tf.zeros_initializer())


 with slim.arg_scope(inception.inception_v1_arg_scope()):
 _, end_points = inception.inception_v1(input_img, num_classes=1001, is_training=False)

    # Create an operation that loads the pre-trained model from the checkpoint
  init_fn = slim.assign_from_checkpoint_fn(
os.path.join('home/n/models/inception_/', '/home/n/data/inception_v1.ckpt'),
slim.get_model_variables('InceptionV1')
    )

我做错了，因为它更新永远不会发生。谢谢

使用张量流进行模型开始的样式转换？

0 个答案: