How to write mutiple graphs in a run in tensorflow

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本文探讨了在TensorFlow中使用TensorBoard记录多个图的方法。通过示例代码展示了如何定义两个不同的计算图，并尝试同时记录它们。然而，默认情况下TensorBoard只会显示最后一个被记录的图。文章还引用了Stack Overflow上的一段讨论，解释了这种行为的原因，并提供了一种可能的解决方案：通过为每个图创建独立的文件写入器来避免覆盖。

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As it's designed possible to programming with multiple graphs in tensorflow, I wonder how to write the graphs, more than one, with tensorboard. It seems not possible or not strongly supported. This problem is not my priority for now, so I did not do further search. Maybe, you're facing the same situation.

The following is a relevant question from stackoverflow.com and an anser on it.

tensorflow summary - writing multiple graphs

I have a following code using tensorflow:

 g1 = tf.Graph()
 g2 = tf.Graph()

 with g1.as_default():
     a = tf.constant(3)
     b = tf.constant(4)
     c = tf.add(a, b)

 with g2.as_default():
     x = tf.constant(5)
     y = tf.constant(2)
     z = tf.multiply(x, y)

 writer = tf.summary.FileWriter("./graphs", g1)
 writer = tf.summary.FileWriter("./graphs", g2)
 writer.close()

And on tensorboard, I get this:

But it is missing the first graph. Is there a way to draw both graphs?

asked Jul 2 at 13:18

MoneyBall

483 5 18

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1 Answer

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up vote 1 down vote

Your second call to tf.summary.FileWriter overwrites your first file.

What happens if you write to a different file, by closing the first writer before opening a second?

WARNING:tensorflow:Found more than one graph event per run, or there was a metagraph containing a graph_def, as well as one or more graph events. Overwriting the graph with the newest event.

So it seems tensorboard is not ready to handle more than one graph. Should we worry? To cite Yaroslav Bulatov,

Using more than one graph in a process is generally a terrible mistake.

EDIT

Note that a tensorflow Graph can host several, non-connected components, effectively representing several distinct graphs. For example,

import tensorflow as tf

g = tf.Graph()
with g.as_default():
     a = tf.constant(3)
     b = tf.constant(4)
     c = tf.add(a, b)

     x = tf.constant(5)
     y = tf.constant(2)
     z = tf.multiply(x, y)

writer = tf.summary.FileWriter("./graphs", g)
writer.close()

results in the following

This is one of the reasons why using several Graphs is usually not needed.

reference:

tensorboard - tensorflow summary - writing multiple graphs - Stack Overflow
https://stackoverflow.com/questions/44871237/tensorflow-summary-writing-multiple-graphs

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