Python vs C++ Tensorflow inferencing
Write in the language that you are familiar with, in a way that you can maintain. 
If it takes you a day longer to write it in the "faster" language, but only saves a minute of runtime, then it'll have to run 24*60 times to have caught up, and multiple times more than that to have been economical.
Is it really worth it to implement a C++ code for loading an already trained model and then fetch it instead of using Python?. 
I was wondering this because as far as I understand, Tensorflow for python is C++ behind the scenes (as it is for numpy). So if one ends up basically having a Python program fetching the model loaded with a Python module it would perform pretty similar than using a module in C++ right?
Is there any benchmark? I wasn't able to find anything supporting this theory.
Thanks!