How to deploy ML Designer pipeline as real-time inference pipeline using N-Gram

Question

Hi,
i deployed a real-time inference pipeline using ML Designer. Training and deploying works fine. But when I'm consuming/testing my API it doesn't work. Postman gives me Errorcode 500 and "Internal Server Error. Run: Server internal error is from Module Extract N-Gram Features from Text".

This is my training pipeline:

I read this: https://github.com/MicrosoftDocs/azure-docs/blob/master/articles/machine-learning/algorithm-module-reference/extract-n-gram-features-from-text.md#score-or-publish-a-model-that-uses-n-grams

But I don't know how to achieve this.

Thanks in advance.

Answer 1

Once you create a real-time inference pipeline, please make the further modifications below:

1. Find the output Result_vocabulary dataset from Extract N-Gram Features from Text module.
   
2. Register the dataset as with a name
   
3. Update real-time inference pipeline like below:
   

We will improve the documentation accordingly. Thanks for reporting the issue!

Answer 2

Hi @Lu Zhang (MSFT) do not see Output datasets to select for registering them. How should I proceed? I have also attached screenshot.

Input datasets
None

Output datasets
None