GitLab

* solving bug where for small epochs and large gradient_accumulation_steps we never train

* black formatting

* no need to change these files

* Update examples/ner/run_ner.py to use AutoModel

* Fix missing code and apply `make style` command

* ✨ 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

* change do_samples back

* None better default as boolean

* adapt do_sample to True in test example

* make style

* 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

* Remove unused kwargs
* dont call forward in tests

Bumps [psutil](https://github.com/giampaolo/psutil) from 5.6.3 to 5.6.6.
- [Release notes](https://github.com/giampaolo/psutil/releases)
- [Changelog](https://github.com/giampaolo/psutil/blob/master/HISTORY.rst)
- [Commits](https://github.com/giampaolo/psutil/compare/release-5.6.3...release-5.6.6

)
Signed-off-by: dependabot[bot] <support@github.com>

* Update bart example docs

* 1. seqeval required by ner pl example. install from examples/requirements. 2. unrecognized arguments: save_steps

* pl checkpoint callback filenotfound error: make directory and pass

* #3159 pl checkpoint path difference

* 1. Updated Readme for pl 2. pl script now also correct displays logs 3. pass gpu ids compared to number of gpus

* Updated results in readme

* 1. updated readme 2. removing deprecated pl methods 3. finalizing scripts

* comment length check

* using deprecated validation_end for stable results

* style related changes

closes #3183

* improved documentation

* 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

That's the same fix applied in https://github.com/huggingface/transformers/issues/2258 , but for the GLUE example

* fix n_gpu count when no_cuda flag is activated

* someone was left behind

* changes to allow for tpu training

* black

* tpu

* tpu

Add preprocessing step for transfo-xl tokenization to avoid tokenizing words followed by punction to <unk> (#2987)

* add preprocessing to add space before punctuation for transfo_xl

* improve warning messages

* make style

* compile regex at instantination of tokenizer object

* Added support for Albert in NER pipeline

* Added command-line options to examples/ner/run_ner.py to better control tokenization

* Added class AlbertForTokenClassification

* Changed output for NerPipeline to use .convert_ids_to_tokens(...) instead of .decode(...) to better reflect tokens

* improving generation

* finalized special token behaviour for no_beam_search generation

* solved modeling_utils merge conflict

* solve merge conflicts in modeling_utils.py

* add run_generation improvements from PR #2749

* adapted language generation to not use hardcoded -1 if no padding token is available

* remove the -1 removal as hard coded -1`s are not necessary anymore

* add lightweight language generation testing for randomely initialized models - just checking whether no errors are thrown

* add slow language generation tests for pretrained models using hardcoded output with pytorch seed

* delete ipdb

* check that all generated tokens are valid

* renaming

* renaming Generation -> Generate

* make style

* updated so that generate_beam_search has same token behavior than generate_no_beam_search

* consistent return format for run_generation.py

* deleted pretrain lm generate tests -> will be added in another PR

* cleaning of unused if statements and renaming

* run_generate will always return an iterable

* make style

* consistent renaming

* improve naming, make sure generate function always returns the same tensor, add docstring

* add slow tests for all lmhead models

* make style and improve example comments modeling_utils

* better naming and refactoring in modeling_utils

* improving generation

* finalized special token behaviour for no_beam_search generation

* solved modeling_utils merge conflict

* solve merge conflicts in modeling_utils.py

* add run_generation improvements from PR #2749

* adapted language generation to not use hardcoded -1 if no padding token is available

* remove the -1 removal as hard coded -1`s are not necessary anymore

* add lightweight language generation testing for randomely initialized models - just checking whether no errors are thrown

* add slow language generation tests for pretrained models using hardcoded output with pytorch seed

* delete ipdb

* check that all generated tokens are valid

* renaming

* renaming Generation -> Generate

* make style

* updated so that generate_beam_search has same token behavior than generate_no_beam_search

* consistent return format for run_generation.py

* deleted pretrain lm generate tests -> will be added in another PR

* cleaning of unused if statements and renaming

* run_generate will always return an iterable

* make style

* consistent renaming

* improve naming, make sure generate function always returns the same tensor, add docstring

* add slow tests for all lmhead models

* make style and improve example comments modeling_utils

* better naming and refactoring in modeling_utils

* changed fast random lm generation testing design to more general one

* delete in old testing design in gpt2

* correct old variable name

* temporary fix for encoder_decoder lm generation tests - has to be updated when t5 is fixed

* adapted all fast random generate tests to new design

* better warning description in modeling_utils

* better comment

* better comment and error message
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>

* Added CamembertForQuestionAnswering

* fixed camembert tokenizer case

* Results same as fairseq
* Wrote a ton of tests
* Struggled with api signatures
* added some docs

* initial pytorch lightning commit

* tested multigpu

* Fix learning rate schedule

* black formatting

* fix flake8

* isort

* isort

* .
Co-authored-by: Check your git settings! <chris@chris-laptop>