"nan" error in tensorflow

Days ago, I met the error, training loss goes to be “nan” in tensorflow. Payed some effort, I found the cause of this error. In my case, It was I fed the wrong label to the network caused that error. In the wrong labeled scenario, no matter the direction the network going in training, there are wrongs and maybe more wrongs in prediction.
If you come across the “nan” error in tensorflow, you may need to check the training date you fed in the network first. If there is nothing wrong, go for other investigations.