Problem:
The python library multi-task-NLP is built on specific formatted inputs and outputs the entire way through. After training completes, the documentation for how to use the InferPipeline is incomplete. How do we format the inputs for pipe.infer() from the prepared data outputted by the data_preparation.py script? Do we really have to parse the .json files ourselves in order to use the infer() pipeline, or is that functionality already included? I suspect it is already included, but this is not documented either on the multi-task-NLP docs or the ipython notebooks for the specific task code examples.
Describe the solution you'd like
The documentation in the Jupyter notebook for the Inference section of the Sentiment Analysis is incomplete. I would like to see the exact code used in order to evaluate the sentiment analysis task in /examples/sentiment_analysis/IMDb_sentiment_analysis.ipynb.
Problem:
The python library multi-task-NLP is built on specific formatted inputs and outputs the entire way through. After training completes, the documentation for how to use the InferPipeline is incomplete. How do we format the inputs for pipe.infer() from the prepared data outputted by the data_preparation.py script? Do we really have to parse the .json files ourselves in order to use the infer() pipeline, or is that functionality already included? I suspect it is already included, but this is not documented either on the multi-task-NLP docs or the ipython notebooks for the specific task code examples.
Describe the solution you'd like
The documentation in the Jupyter notebook for the Inference section of the Sentiment Analysis is incomplete. I would like to see the exact code used in order to evaluate the sentiment analysis task in /examples/sentiment_analysis/IMDb_sentiment_analysis.ipynb.