If we want to use our machine learning scripts in a production setting, there are some points to consider for best practices. Here, we will help to point out some best practices.
In this recipe, we want to summarize and condense various tips for bringing TensorFlow to production. We will cover how to best save and load vocabularies, graphs, variables, and model checkpoints. We will also talk about how to use TensorFlow's command-line argument parser and change the logging verbosity of TensorFlow.