return_tensors and return_text in TextGenerationPipeline don't work or partially work

System Info

• transformers version: 4.24.0
• python version: 3.8.11

Who can help?

Library:

• Text generation: @patrickvonplaten, @Narsil, @gante
• Pipelines: @Narsil

Documentation: @sgugger, @stevhliu

Information

• The official example scripts
• My own modified scripts

Tasks

• An officially supported task in the examples folder (such as GLUE/SQuAD, …)
• My own task or dataset (give details below)

Reproduction

1. initialize TextGenerationPipeline, assume we call it pipeline below
2. run the following code snips:

results = pipeline(text_input, return_text=True, return_full_text=False, return_tensors=False)[0]

results = pipeline(text_input, return_text=True, return_full_text=False, return_tensors=True)[0]

results = pipeline(text_input, return_text=False, return_full_text=False, return_tensors=True)[0]

results = pipeline(text_input, return_text=False, return_full_text=False, return_tensors=False)[0]

1. all the four code snips return the same dict with only one key generated_text

Expected behavior

1. when return_text=True and return_tensors=False, return a dict contains only one key generated_text
2. when return_text=False and return_tensors=True, return a dict contains only one key generated_token_ids
3. when return_text=True and return_tensors=True, return a dict contains both generated_text and generated_token_ids

[Narsil]

Yes the docs could use some polish here, maybe even soft deprecate return_text & co in favor of return_type. Soft deprecate meaning we don’t ever have to actually remove them, just don’t make them as prominent since they are indeed confusing.

[PanQiWei]

I may be wrong, but I think return_type is an internal parameter, but you can still decide what to return with the other three parameters.

As far as I can tell, you can’t return a combination of generated_text and generated_token_ids. You can only return one or the other, which I guess is why some of those combinations don’t do anything. Would it help if there was a note in the docs about this?

@stevhliu thanks for the replying! Now I’m clear with the functionality and relationship between return_text and return_tensors, and I think it would be clear to more people if the documentation also target this out. 😄