GitLab

* Align TF NER example over the PT one

* Fix Dataset call

* Fix gradient accumulation training

* Apply style

* Address Sylvain's comments

* Address Sylvain's comments

* Apply style

* AdaFactor optimizer ported from fairseq. Tested for T5 finetuning and MLM -- reduced memory consumption compared to ADAM.

* update PR fixes, add basic test

* bug -- incorrect params in test

* bugfix -- import Adafactor into test

* bugfix -- removed accidental T5 include

* resetting T5 to master

* bugfix -- include Adafactor in __init__

* longer loop for adafactor test

* remove double error class declare

* lint

* black

* isort

* Update src/transformers/optimization.py
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* single docstring

* Cleanup docstring
Co-authored-by: Nikolai Y <nikolai.yakovenko@point72.com>
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* Create README.md

* Update README.md

* Create README.md

* Update README.md

* Create README.md

* Update README.md

* added model card for codeswitch-spaeng-sentiment-analysis-lince model also update other model card

* fixed typo

* fixed typo

* fixed typo

* fixed typo

* fixed typo

* fixed typo

* fixed typo

* Update README.md

* Added model cards for 4 models

Added model cards for:
- roberta-base-bulgarian
- roberta-base-bulgarian-pos
- roberta-small-bulgarian
- roberta-small-bulgarian-pos

* fixed link text

* Update README.md

* Create README.md

* removed trailing bracket

* Add language metadata
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* add xlm-roberta-large-xnli model card

* update pt example

* typo

* add tf graph compile tests

* fix conflict

* remove more tf transpose statements

* fix conflicts

* fix comment typos

* move function to class function

* fix black

* fix black

* make style

* Logging

* Style

* hf_logging > utils.logging

* Address @thomwolf's comments

* Update test

* Update src/transformers/benchmark/benchmark_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Revert bad change
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* add tie_word_embeddings

* correct word embeddings in modeling utils

* make style

* make config param only relevant for torch

* make style

* correct typo

* delete deprecated arg in transo-xl

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* [squad] make examples and dataset accessible from SquadDataset object

* [squad] add support for legacy cache files

add model card for singbert large

Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>

* More tests to Trainer

* Add warning in the doc

* Allow tests in examples to use cuda or fp16,if they are available

The tests in examples didn't use the cuda or fp16 even if they where available.
- The text classification example (`run_glue.py`) didn't use the fp16 even if it was available but
  the device was take based on the availablity(cuda/cpu).
- The language-modeling example (`run_language_modeling.py`) was having `--no_cuda` argument
  which made the test to work without cuda. This example is having issue when running with fp16
  thus it not enabled (got an assertion error for perplexity due to it higher value).
- The cuda and fp16 is not enabled for question-answering example (`run_squad.py`) as it is having a
  difference in the f1 score.
- The text-generation example (`run_generation.py`) will take the cuda or fp16 whenever it is available.

Resolves some of: #5057

* Unwanted import of is_apex_available was removed

* Made changes to test examples file to have the pass --fp16 only if cuda and apex is avaliable
- run_glue.py: Removed the check for cuda and fp16.
- run_generation.py: Removed the check for cuda and fp16 also removed unwanted flag creation.

* Incorrectly sorted imports fixed

* The model needs to be converted to half precision

* Formatted single line if condition statement to multiline

* The torch_device also needed to be checked before running the test on examples
- The tests in examples which uses cuda should also depend from the USE_CUDA flag,
  similarly to the rest of the test suite. Even if we decide to set USE_CUDA to
  True by default, setting USE_CUDA to False should result in the examples not using CUDA

* Format some of the code in test_examples file

* The improper import of is_apex_available was sorted

* Formatted the code to keep the style standards

* The comma at the end of list giving a flake8 issue was fixed

* Import sort was fixed

* Removed the clean_test_dir function as its not used right now

* add overload for type checker

* black

* add dpr to models summary

* minor

* minor

* Update docs/source/model_summary.rst

qa -> question answering
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update docs/source/model_summary.rst

qa -> question ansering (cont'd)
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>