* Big cleanup of `glue_convert_examples_to_features`
* Use batch_encode_plus
* Cleaner wrapping of glue_convert_examples_to_features for TF
@lysandrejik
* Cleanup syntax, thanks to @mfuntowicz
* Raise explicit error in case of user error
* Fix RoBERTa/XLNet Pad Token in run_multiple_choice.py
`convert_examples_to_fes atures` sets `pad_token=0` by default, which is correct for BERT but incorrect for RoBERTa (`pad_token=1`) and XLNet (`pad_token=5`). I think the other arguments to `convert_examples_to_features` are correct, but it might be helpful if someone checked who is more familiar with this part of the codebase.
* Simplifying change to match recent commits
* Using loaded checkpoint with --do_predict
Without this fix, I'm getting near-random validation performance for a trained model, and the validation performance differs per validation run. I think this happens since the `model` variable isn't set with the loaded checkpoint, so I'm using a randomly initialized model. Looking at the model activations, they differ each time I run evaluation (but they don't with this fix).
* Update checkpoint loading
* Fixing model loading
* Update the NER TF script to remove the softmax and make the pad token label id to -1
* Reformat the quality and style
Co-authored-by: Julien Plu <julien.plu@adevinta.com>
* force bleu
* fix wrong file name
* rename file
* different filenames for each example test
* test files should clean up after themselves
* test files should clean up after themselves
* do not force bleu
* correct typo
* fix isort
* Use tokenizer.num_added_tokens to count number of added special_tokens instead of hardcoded numbers.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* run_ner.py - Do not add a label to the labels_ids if word_tokens is empty.
This can happen when using bert-base-multilingual-cased with an input containing an unique space.
In this case, the tokenizer will output just an empty word_tokens thus leading to an non-consistent behavior
over the labels_ids tokens adding one more tokens than tokens vector.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* ✨ Alter base pl transformer to use automodels
* 🐛 Add batch size env variable to function call
* 💄 Apply black code style from Makefile
* 🚚 Move lightning base out of ner directory
* ✨ Add lightning glue example
* 💄 self
* move _feature_file to base class
* ✨ Move eval logging to custom callback
* 💄 Apply black code style
* 🐛 Add parent to pythonpath, remove copy command
* 🐛 Add missing max_length kwarg
* memory benchmark rss
* have both forward pass and line-by-line mem tracing
* cleaned up tracing
* refactored and cleaning up API
* no f-strings yet...
* add GPU mem logging
* fix GPU memory monitoring
* style and quality
* clean up and doc
* update with comments
* Switching to python 3.6+
* fix quality
* Rename and improve example
* Add test
* slightly faster test
* style
* This breaks remy prolly
* shorter test string
* no slow
* newdir structure
* New tree
* Style
* shorter
* docs
* clean
* Attempt future import
* more import hax
Julien Chaumond