Tensorflow 在tensorboard中显示python变量

我想在tensorboard中显示一些python变量，但我没有完成

到目前为止，我的代码在tensorboard中只显示一行静态编号的行，如果我使用未注释的行，它会不起作用吗？然后打印： ValueError:形状（）和（？）不兼容

有人有主意吗

import tensorflow as tf

step = 0
session = tf.Session()

tensorboardVar = tf.Variable(0, "tensorboardVar")

pythonVar = tf.placeholder("int32", [None])

#update_tensorboardVar = tensorboardVar.assign(pythonVar)
update_tensorboardVar = tensorboardVar.assign(4)
tf.scalar_summary("myVar", update_tensorboardVar)

merged = tf.merge_all_summaries()

sum_writer = tf.train.SummaryWriter('/tmp/train/c/', session.graph)

session.run(tf.initialize_all_variables())


for i in range(100):
        _, result = session.run([update_tensorboardVar, merged])
        #_, result = session.run([update_tensorboardVar, merged], feed_dict={pythonVar: i})
        sum_writer.add_summary(result, step)
        step += 1

这是有效的：

import tensorflow as tf
import numpy as np

step = 0
session = tf.Session()

tensorboardVar = tf.Variable(0, "tensorboardVar")

pythonVar = tf.placeholder("int32", [])

update_tensorboardVar = tensorboardVar.assign(pythonVar)
tf.scalar_summary("myVar", update_tensorboardVar)

merged = tf.merge_all_summaries()

sum_writer = tf.train.SummaryWriter('/tmp/train/c/', session.graph)

session.run(tf.initialize_all_variables())


for i in range(100):
        #_, result = session.run([update_tensorboardVar, merged])
        j = np.array(i)
        _, result = session.run([update_tensorboardVar, merged], feed_dict={pythonVar: j})
        sum_writer.add_summary(result, step)
        step += 1

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另一种方法可以在第二个答案中找到。这里展示了如何创建自定义摘要