小编Kav*_*van的帖子

我正在尝试在Tensorflow中实现神经网络.我tf.train.GradientDescentOptimizer用来最小化熵.但它告诉我错误ValueError: No variables to optimize

下面是代码

import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", one_hot = True)

x = tf.placeholder(tf.float32,[None,748])
w = tf.zeros([748,10])
b = tf.zeros([10])
y = tf.matmul(x,w) + b
y_ = tf.placeholder(tf.float32,[None,10])
cross_entropy = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(labels = y_, logits = y))
train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)

sess = tf.InteractiveSessoin()
tf.global_variables_initializer().run()

for i in range(1000):
    batch_xs, batch_ys = mnist.train.next_batch(100)
    sess.run(train_step, feed_dict = {x:batch_xs, y_:batch_ys})

我收到的错误是这样的

Traceback (most recent call last):
  File "NeuralNetwork.py", line 15, in <module> …

我有matrix = [[1,2,3],[4,5,6],[7,8,9]]和matrix2=matrix。现在我想从matrix2 中删除第一行，即matrix2.remove(matrix[0])。

但我得到了这个

>>> matrix2.remove(matrix2[0])
>>> matrix2
    [[4, 5, 6], [7, 8, 9]]
>>> matrix
    [[4, 5, 6], [7, 8, 9]]

第一行matrix也被删除。谁能解释一下吗？以及如何在matrix2不改变的情况下删除第一行matrix