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* README

* Update README.md

* Created using Colaboratory

* [examples] reorganize files

* remove run_tpu_glue.py as superseded by TPU support in Trainer

* Bugfix: int, not tuple

* move files around

* first copy & past commit from Bert and morgans LSH code

* add easy way to compare to trax original code

* translate most of function

* make trax lsh self attention deterministic with numpy seed + copy paste code

* add same config

* add same config

* make layer init work

* implemented hash_vectors function for lsh attention

* continue reformer translation

* hf LSHSelfAttentionLayer gives same output as trax layer

* refactor code

* refactor code

* refactor code

* refactor

* refactor + add reformer config

* delete bogus file

* split reformer attention layer into two layers

* save intermediate step

* save intermediate step

* make test work

* add complete reformer block layer

* finish reformer layer

* implement causal and self mask

* clean reformer test and refactor code

* fix merge conflicts

* fix merge conflicts

* update init

* fix device for GPU

* fix chunk length init for tests

* include morgans optimization

* improve memory a bit

* improve comment

* factorize num_buckets

* better testing parameters

* make whole model work

* make lm model work

* add t5 copy paste tokenizer

* add chunking feed forward

* clean config

* add improved assert statements

* make tokenizer work

* improve test

* correct typo

* extend config

* add complexer test

* add new axial position embeddings

* add local block attention layer

* clean tests

* refactor

* better testing

* save intermediate progress

* clean test file

* make shorter input length work for model

* allow variable input length

* refactor

* make forward pass for pretrained model work

* add generation possibility

* finish dropout and init

* make style

* refactor

* add first version of RevNet Layers

* make forward pass work and add convert file

* make uploaded model forward pass work

* make uploaded model forward pass work

* refactor code

* add namedtuples and cache buckets

* correct head masks

* refactor

* made reformer more flexible

* make style

* remove set max length

* add attention masks

* fix up tests

* fix lsh attention mask

* make random seed optional for the moment

* improve memory in reformer

* add tests

* make style

* make sure masks work correctly

* detach gradients

* save intermediate

* correct backprob through gather

* make style

* change back num hashes

* rename to labels

* fix rotation shape

* fix detach

* update

* fix trainer

* fix backward dropout

* make reformer more flexible

* fix conflict

* fix

* fix

* add tests for fixed seed in reformer layer

* fix trainer typo

* fix typo in activations

* add fp16 tests

* add fp16 training

* support fp16

* correct gradient bug in reformer

* add fast gelu

* re-add dropout for embedding dropout

* better naming

* better naming

* renaming

* finalize test branch

* finalize tests

* add more tests

* finish tests

* fix

* fix type trainer

* fix fp16 tests

* fix tests

* fix tests

* fix tests

* fix issue with dropout

* fix dropout seeds

* correct random seed on gpu

* finalize random seed for dropout

* finalize random seed for dropout

* remove duplicate line

* correct half precision bug

* make style

* refactor

* refactor

* docstring

* remove sinusoidal position encodings for reformer

* move chunking to modeling_utils

* make style

* clean config

* make style

* fix tests

* fix auto tests

* pretrained models

* fix docstring

* update conversion file

* Update pretrained_models.rst

* fix rst

* fix rst

* update copyright

* fix test path

* fix test path

* fix small issue in test

* include reformer in generation tests

* add docs for axial position encoding

* finish docs

* Update convert_reformer_trax_checkpoint_to_pytorch.py

* remove isort

* include sams comments

* remove wrong comment in utils

* correct typos

* fix typo

* Update reformer.rst

* applied morgans optimization

* make style

* make gpu compatible

* remove bogus file

* big test refactor

* add example for chunking

* fix typo

* add to README

* change encoder decoder style to bart & t5 style

* make encoder decoder generation dummy work for bert

* make style

* clean init config in encoder decoder

* add tests for encoder decoder models

* refactor and add last tests

* refactor and add last tests

* fix attn masks for bert encoder decoder

* make style

* refactor prepare inputs for Bert

* refactor

* finish encoder decoder

* correct typo

* add docstring to config

* finish

* add tests

* better naming

* make style

* fix flake8

* clean docstring

* make style

* rename

* Fix tpo in into and add line under

* Add missing blank line under

* Correct types under

* Add GenerationPipeline

* Fix parameter names

* Correct parameter __call__ parameters

* Add model type attribute and correct function calls for prepare_input

* Take out trailing commas from init attributes

* Remove unnecessary tokenization line

* Implement support for multiple text inputs

* Apply generation support for multiple input text prompts

* Take out tensor coersion

* Take out batch index

* Add text prompt to return sequence

* Squeeze token tensore before decoding

* Return only a single list of sequences if only one prompt was used

* Correct results variable name

* Add GenerationPipeline to SUPPORTED_TASKS with the alias , initalized w GPT2

* Registedred AutoModelWithLMHead for both pt and t

* Update docstring for GenerationPipeline

* Add kwargs parameter to mode.generate

* Take out kwargs parameter after all

* Add generation pipeline example in pipeline docstring

* Fix max length by squeezing tokens tensor

* Apply ensure_tensor_on_device to pytorch tensor

* Include generation step in torch.no_grad

* Take out input from prepare_xlm_input and set 'en' as default xlm_language

* Apply framework specific encoding during prepare_input

* Format w make style

* Move GenerationPipeline import to follow proper import sorting

* Take out training comma from generation dict

* Apply requested changes

* Change name to TextGenerationPipeline

* Apply TextGenerationPipeline rename to __init___

* Changing alias to

* Set input mapping as input to ensure_tensor_on_device

* Fix assertion placement

* Add test_text_generation

* Add TextGenerationPipeline to PipelineCommonTests

* Take out whitespace

* Format __init__ w black

* Fix __init__ style

* Forman __init___

* Add line to end of __init__

* Correct model tokenizer set for test_text_generation

* Ensure to return list of list, not list of string (to pass test)

* Limit test models to only 3 to limit runtime to address circleCI timeout error

* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>

* Update tests/test_pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>

* Remove argument docstring, __init__, add additional __call__ arguments, and reformat results to list of dict

* Fix blank result list

* Add TextGenerationPipeline to pipelines.rst

* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>

* Fix typos from adding PADDING_TEXT_TOKEN_LENGTH

* Fix incorrectly moved result list

* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/pipelines.py

* Update src/transformers/pipelines.py

* Update src/transformers/pipelines.py

* Update src/transformers/pipelines.py

* Update src/transformers/pipelines.py

* Update src/transformers/pipelines.py

* Update src/transformers/pipelines.py

* Update src/transformers/pipelines.py

* Update src/transformers/pipelines.py

* Update src/transformers/pipelines.py

* Update src/transformers/pipelines.py

* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>

* Add back generation line and make style

* Take out blank whitespace

* Apply new alis, text-generation, to test_pipelines

* Fix text generation alias in test

* Update src/transformers/pipelines.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* First pass on utility classes and python tokenizers

* finishing cleanup pass

* style and quality

* Fix tests

* Updating following @mfuntowicz comment

* style and quality

* Fix Roberta

* fix batch_size/seq_length inBatchEncoding

* add alignement methods + tests

* Fix OpenAI and Transfo-XL tokenizers

* adding trim_offsets=True default for GPT2 et RoBERTa

* style and quality

* fix tests

* add_prefix_space in roberta

* bump up tokenizers to rc7

* style

* unfortunately tensorfow does like these - removing shape/seq_len for now

* Update src/transformers/tokenization_utils.py
Co-Authored-By: Stefan Schweter <stefan@schweter.it>

* Adding doc and docstrings

* making flake8 happy
Co-authored-by: Stefan Schweter <stefan@schweter.it>

* add dialoGPT

* update README.md

* fix conflict

* update readme

* add code links to docs

* Update README.md

* Update dialo_gpt2.rst

* Update pretrained_models.rst

* Update docs/source/model_doc/dialo_gpt2.rst
Co-Authored-By: Julien Chaumond <chaumond@gmail.com>

* change filename of dialogpt
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

- support mbart-en-ro weights
- add MBartTokenizer

* Update notebooks

* From local to global link

* from local links to *actual* global links

* Electra wip

* helpers

* Electra wip

* Electra v1

* ELECTRA may be saved/loaded

* Generator & Discriminator

* Embedding size instead of halving the hidden size

* ELECTRA Tokenizer

* Revert BERT helpers

* ELECTRA Conversion script

* Archive maps

* PyTorch tests

* Start fixing tests

* Tests pass

* Same configuration for both models

* Compatible with base + large

* Simplification + weight tying

* Archives

* Auto + Renaming to standard names

* ELECTRA is uncased

* Tests

* Slight API changes

* Update tests

* wip

* ElectraForTokenClassification

* temp

* Simpler arch + tests

Removed ElectraForPreTraining which will be in a script

* Conversion script

* Auto model

* Update links to S3

* Split ElectraForPreTraining and ElectraForTokenClassification

* Actually test PreTraining model

* Remove num_labels from configuration

* wip

* wip

* From discriminator and generator to electra

* Slight API changes

* Better naming

* TensorFlow ELECTRA tests

* Accurate conversion script

* Added to conversion script

* Fast ELECTRA tokenizer

* Style

* Add ELECTRA to README

* Modeling Pytorch Doc + Real style

* TF Docs

* Docs

* Correct links

* Correct model intialized

* random fixes

* style

* Addressing Patrick's and Sam's comments

* Correct links in docs

* Add clear description of how to train T5

* correct docstring in T5

* correct typo

* correct docstring format

* update t5 model docs

* implement collins feedback

* fix typo and add more explanation for sentinal tokens

* delete unnecessary todos

* add t5 docs basis

* improve docs

* add t5 docs

* improve t5 docstring

* add t5 tokenizer docstring

* finish docstring

* make style

* add pretrained models

* correct typo

* make examples work

* finalize docs

* passing

* Undo stupid chg

* docs

* undo rename

* delete-cruft

* only import if you have torch

* Dont rely on dict ordering

* Fix dict ordering upstream

* docstring link

* docstring link

* remove trailing comma for 3.5 compat

* new name

* delegate kwarging

* Update kwargs

* 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

Co-Authored-By: Thomas Wolf <thomwolf@users.noreply.github.com>

* improved documentation

* Pipeline doc initial commit

* pipeline abstraction

* Remove modelcard argument from pipeline

* Task-specific pipelines can be instantiated with no model or tokenizer

* All pipelines doc

`generate` code that produces 99% identical summarizations to fairseq on CNN test data, with caching.

* All Tokenizers

BertTokenizer + few fixes
RobertaTokenizer
OpenAIGPTTokenizer + Fixes
GPT2Tokenizer + fixes
TransfoXLTokenizer
Correct rst for TransformerXL
XLMTokenizer + fixes
XLNet Tokenizer + Style
DistilBERT + Fix XLNet RST
CTRLTokenizer
CamemBERT Tokenizer
FlaubertTokenizer
XLMRobertaTokenizer
cleanup

* cleanup

* Usage: Sequence Classification & Question Answering

* Pipeline example

* Language modeling

* TensorFlow code for Sequence classification

* Custom TF/PT toggler in docs

* QA + LM for TensorFlow

* Finish Usage for both PyTorch and TensorFlow

* Addressing Julien's comments

* More assertive

* cleanup

* Favicon
- added favicon option in conf.py along with the favicon image
- udpated 🤗

 logo. slightly smaller and should appear more consistent across editing programs (no more tongue on the outside of the mouth)
Co-authored-by: joshchagani <joshua@joshuachagani.com>

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

Welcome Rust Tokenizers