python - In Tensorflow for serving a model, what does the serving input function supposed to do exactly

Question

So, I've been struggling to understand what the main task of a serving_input_fn() is when a trained model is exported in Tensorflow for serving purposes. There are some examples online that explain it but I'm having problems defining it for myself.

The problem I'm trying to solve is a regression problem where I have 29 inputs and one output. Is there a template for creating a corresponding serving input function for that? What if I use a one-class classification problem? Would my serving input function need to change or can I use the same function?

And finally, do I always need serving input functions or is it only when I use tf.estimator to export my model?

Answer 1

Waitting for answers