Productionalizing TensorFlow – An Example
A good practice for productionalizing machine learning models is to separate the training and evaluation programs. Here, we illustrate an evaluation script expanded to include a unit test, model saving and loading, and evaluation.
Getting ready
For this recipe, we will show how to implement an evaluation script, using the above production criteria. The code actually consists of a training script and an evaluation script, but for this recipe, we will only show the evaluation script. As a reminder, both scripts can been seen in the online GitHub repository, https://github.com/nfmcclure/tensorflow_cookbook/.
For the example, we will implement the first RNN example from Chapter 9, Recurrent Neural Networks, which attempts to predict if a text message is spam or ham. We will assume the RNN model is trained and saved, along with the vocabulary.
How to do it…
- We start by loading the necessary libraries and declaring the TensorFlow application...
