* Examples version update
* Refactor a bit
* All version updates
* Fixes
* README cleanup
* Post-release/patch
* Fixes
* More fixes
* Tests
* More fixes
* Moar fixes
* Make commands and update setup
* Replace spaces with weird tabs
* Fix test
* Style
* Tests run on Docker
Co-authored-by: Morgan <funtowiczmo@gmail.com>
* Comments from code review
* Reply to itself
* Dependencies
Co-authored-by: Morgan <funtowiczmo@gmail.com>
* Update super class reference
* Update default value reference
* Update src/transformers/models/wav2vec2/feature_extraction_wav2vec2.py
* Fix format style
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* [WIP] Adding new parameter to `generate`: `max_time`.
Generation by tokens number is sometimes a bit clunky because we don't
know how many tokens are good enough or even how many tokens are in
the payload (for pipelines users for instance). This leads to hard
to understand behavior.
This PR proposes a new argument `max_time` which is a float of seconds
for the allowed time for `generate` to run on.
Ideally combinations of `max_tokens=None`, `max_time=2` could be used to
generate as many tokens as possible within time budget.
NB: Another possible approach consists of passing a callback to `generate`
putting the caller in charge of the actual decision of when to stop
generating tokens. It opens the door to 'which args should we pass'
to this callback. It's hard to imagine other use-cases for this
early stopping behavior than time (that are not already covered by
parameters of generate)
* Revamp with StoppingCriteria
* Removing deprecated mentions.
* Forgot arguments to stopping criteria.
* Readding max_length it's not just used as a stopping criteria.
* Default value for `stopping_criteria`.
* Address @patrickvonplaten comments.
- More docstrings
- Actual doc
- Include in global namespace
- Remove TF work.
* Put back `max_length` (deprecation different PR).
* Doc quality.
* Fixing old behavior without `stopping_criteria` but with `max_length`.
Making sure we don't break that in the future.
* Adding more tests for possible inconsistencies between
`max_length` and `stopping_criteria`.
* Fixing the torch imports.
* Allow to pass kwargs to model's from_pretrained when using pipeline.
* Disable the use of past_keys_values for GPT2 when exporting to ONNX.
* style
* Remove comment.
* Appease the documentation gods
* Fix style
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
* Remove special path for custom vocab files
* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Expand error message
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* renamed logging to hf_logging
* changed logging from hf_logging to logging and loggin to native_logging
* removed everything trying to fix import Trainer error
* adding imports again
* added custom add_handler function to logging.py
* make style
* added remove_handler
* added another conditional to assert
