Not that I am aware of. However, due to its dynamic nature, it is much easier to debug a network in pytorch than tensorflow.
As one commenter on Reddit 634 opines:
“Debugging is easier because a specific line in your specific code (not something deep under your sess.run() that worked with a large/generated Graph object) fails. Your stack traces don’t fill up three screens and make you play the “spot the actual error!” scrolling game.”
I’ve found it fairly simple to just instrument the code as needed when things don’t go as planned.