February 2017
Intermediate to advanced
370 pages
8h 11m
English
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Chapter 10. Taking TensorFlow to Production
In this chapter, we will cover the following topics:
- Implementing Unit Tests
- Using Multiple Executors
- Parallelizing TensorFlow
- Taking TensorFlow to Production
- Productionalizing TensorFlow – An Example
Introduction
Up to this point, we have covered how to train and evaluate various models in TensorFlow. In this chapter, we will show how to write code that is ready for production usage. There are various definitions of production-ready code but, for us, production code will be defined as code that has unit tests, separates the training and evaluation code, and efficiently saves and loads various needed parts of the data pipeline and created graph session.
Note
The Python scripts provided in this chapter should ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.