如何在这段代码中添加一些摘要，例如偏差和权重，以便可以在张量板上看到直方图？

Question

我想添加一些代码行来收集以下python代码中的摘要（直方图和标量）。我尝试从一些教程中学习，但是每个教程都有一个特定的应用程序。其实我不知道把线放在哪里

x = tf.placeholder(tf.float32, [None, 784], name='Input')
W = tf.Variable(tf.zeros([784, 10]), name='Weight')
b = tf.Variable(tf.zeros([10]), name='Bias')
y = tf.nn.softmax(tf.matmul(x, W) + b)
y_ = tf.placeholder(tf.float32, [None, 10])
cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y), reduction_indices=[1]))
train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)

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

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

correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
print(sess.run(accuracy, feed_dict={x: mnist.test.images, y_: mnist.test.labels}))