* GPT2 gradient checkpointing
* find_unused_parameters removed if checkpointing
* find_unused_parameters removed if checkpointing
* Update src/transformers/configuration_gpt2.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Added a test for generation with checkpointing
* Update src/transformers/configuration_gpt2.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Changed name to all no_... arguments and all references to them, inverting the boolean condition
* Change benchmark tests to use new Benchmark Args
* Update src/transformers/benchmark/benchmark_args_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/benchmark/benchmark.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Fix Style. Add --no options in help
* fix some part of tests
* Update src/transformers/benchmark/benchmark_args_utils.py
* Update src/transformers/benchmark/benchmark_args_utils.py
* Update src/transformers/benchmark/benchmark_args_utils.py
* fix all tests
* make style
* add backwards compability
* make backwards compatible
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: fmcurti <fcurti@DESKTOP-RRQURBM.localdomain>
* skip decorators: docs, tests, bugs
* another important note
* style
* bloody style
* add @pytest.mark.parametrize
* add note
* no idea what it wants :(
* added rag WIP
* path fix
* Formatting / renaming prior to actual work
* added rag WIP
* path fix
* Formatting / renaming prior to actual work
* added rag WIP
* path fix
* Formatting / renaming prior to actual work
* added rag WIP
* Formatting / renaming prior to actual work
* First commit
* improve comments
* Retrieval evaluation scripts
* refactor to include modeling outputs + MPI retriever
* Fix rag-token model + refactor
* Various fixes + finetuning logic
* use_bos fix
* Retrieval refactor
* Finetuning refactoring and cleanup
* Add documentation and cleanup
* Remove set_up_rag_env.sh file
* Fix retrieval wit HF index
* Fix import errors
* Fix quality errors
* Refactor as per suggestions in https://github.com/huggingface/transformers/pull/6813#issuecomment-687208867
* fix quality
* Fix RAG Sequence generation
* minor cleanup plus initial tests
* fix test
* fix tests 2
* Comments fix
* post-merge fixes
* Improve readme + post-rebase refactor
* Extra dependencied for tests
* Fix tests
* Fix tests 2
* Refactor test requirements
* Fix tests 3
* Post-rebase refactor
* rename nlp->datasets
* RAG integration tests
* add tokenizer to slow integration test and allow retriever to run on cpu
* add tests; fix position ids warning
* change structure
* change structure
* add from encoder generator
* save working solution
* make all integration tests pass
* add RagTokenizer.save/from_pretrained and RagRetriever.save/from_pretrained
* don't save paths
* delete unnecessary imports
* pass config to AutoTokenizer.from_pretrained for Rag tokenizers
* init wiki_dpr only once
* hardcode legacy index and passages paths (todo: add the right urls)
* finalize config
* finalize retriver api and config api
* LegacyIndex index download refactor
* add dpr to autotokenizer
* make from pretrained more flexible
* fix ragfortokengeneration
* small name changes in tokenizer
* add labels to models
* change default index name
* add retrieval tests
* finish token generate
* align test with previous version and make all tests pass
* add tests
* finalize tests
* implement thoms suggestions
* add first version of test
* make first tests work
* make retriever platform agnostic
* naming
* style
* add legacy index URL
* docstrings + simple retrieval test for distributed
* clean model api
* add doc_ids to retriever's outputs
* fix retrieval tests
* finish model outputs
* finalize model api
* fix generate problem for rag
* fix generate for other modles
* fix some tests
* save intermediate
* set generate to default
* big refactor generate
* delete rag_api
* correct pip faiss install
* fix auto tokenization test
* fix faiss install
* fix test
* move the distributed logic to examples
* model page
* docs
* finish tests
* fix dependencies
* fix import in __init__
* Refactor eval_rag and finetune scripts
* start docstring
* add psutil to test
* fix tf test
* move require torch to top
* fix retrieval test
* align naming
* finish automodel
* fix repo consistency
* test ragtokenizer save/load
* add rag model output docs
* fix ragtokenizer save/load from pretrained
* fix tokenizer dir
* remove torch in retrieval
* fix docs
* fixe finetune scripts
* finish model docs
* finish docs
* remove auto model for now
* add require torch
* remove solved todos
* integrate sylvains suggestions
* sams comments
* correct mistake on purpose
* improve README
* Add generation test cases
* fix rag token
* clean token generate
* fix test
* add note to test
* fix attention mask
* add t5 test for rag
* Fix handling prefix in finetune.py
* don't overwrite index_name
Co-authored-by: Patrick Lewis <plewis@fb.com>
Co-authored-by: Aleksandra Piktus <piktus@devfair0141.h2.fair>
Co-authored-by: Aleksandra Piktus <piktus@learnfair5102.h2.fair>
Co-authored-by: Aleksandra Piktus <piktus@learnfair5067.h2.fair>
Co-authored-by: Your Name <you@example.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Quentin Lhoest <lhoest.q@gmail.com>
* Copy code from Bert to Roberta and add safeguard script
* Fix docstring
* Comment code
* Formatting
* Update src/transformers/modeling_roberta.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Add test and fix bugs
* Fix style and make new comand
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* fix USE_CUDA, add pipeline
* USE_CUDA fix
* recode SinusoidalPositionalEmbedding into nn.Embedding subclass
was needed for torchscript to work - this is now part of the state_dict, so will have to remove these keys during save_pretrained
* back out (ci debug)
* restore
* slow last?
* facilitate not saving certain keys and test
* remove no longer used keys
* style
* fix logging import
* cleanup
* Update src/transformers/modeling_utils.py
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
* fix bug in max_positional_embeddings
* rename keys to keys_to_never_save per suggestion, improve the setup
* Update src/transformers/modeling_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Add BERTweet and PhoBERT models
* Update modeling_auto.py
Re-add `bart` to LM_MAPPING
* Update tokenization_auto.py
Re-add `from .configuration_mobilebert import MobileBertConfig`
not sure why it's replaced by `from transformers.configuration_mobilebert import MobileBertConfig`
* Add BERTweet and PhoBERT to pretrained_models.rst
* Update tokenization_auto.py
Remove BertweetTokenizer and PhobertTokenizer out of tokenization_auto.py (they are currently not supported by AutoTokenizer.
* Update BertweetTokenizer - without nltk
* Update model card for BERTweet
* PhoBERT - with Auto mode - without import fastBPE
* PhoBERT - with Auto mode - without import fastBPE
* BERTweet - with Auto mode - without import fastBPE
* Add PhoBERT and BERTweet to TF modeling auto
* Improve Docstrings for PhobertTokenizer and BertweetTokenizer
* Update PhoBERT and BERTweet model cards
* Fixed a merge conflict in tokenization_auto
* Used black to reformat BERTweet- and PhoBERT-related files
* Used isort to reformat BERTweet- and PhoBERT-related files
* Reformatted BERTweet- and PhoBERT-related files based on flake8
* Updated test files
* Updated test files
* Updated tf test files
* Updated tf test files
* Updated tf test files
* Updated tf test files
* Update commits from huggingface
* Delete unnecessary files
* Add tokenizers to auto and init files
* Add test files for tokenizers
* Revised model cards
* Update save_vocabulary function in BertweetTokenizer and PhobertTokenizer and test files
* Revised test files
* Update orders of Phobert and Bertweet tokenizers in auto tokenization file
* ready for PR
* cleanup
* correct FSMT_PRETRAINED_MODEL_ARCHIVE_LIST
* fix
* perfectionism
* revert change from another PR
* odd, already committed this one
* non-interactive upload workaround
* backup the failed experiment
* store langs in config
* workaround for localizing model path
* doc clean up as in https://github.com/huggingface/transformers/pull/6956
* style
* back out debug mode
* document: run_eval.py --num_beams 10
* remove unneeded constant
* typo
* re-use bart's Attention
* re-use EncoderLayer, DecoderLayer from bart
* refactor
* send to cuda and fp16
* cleanup
* revert (moved to another PR)
* better error message
* document run_eval --num_beams
* solve the problem of tokenizer finding the right files when model is local
* polish, remove hardcoded config
* add a note that the file is autogenerated to avoid losing changes
* prep for org change, remove unneeded code
* switch to model4.pt, update scores
* s/python/bash/
* missing init (but doesn't impact the finetuned model)
* cleanup
* major refactor (reuse-bart)
* new model, new expected weights
* cleanup
* cleanup
* full link
* fix model type
* merge porting notes
* style
* cleanup
* have to create a DecoderConfig object to handle vocab_size properly
* doc fix
* add note (not a public class)
* parametrize
* - add bleu scores integration tests
* skip test if sacrebleu is not installed
* cache heavy models/tokenizers
* some tweaks
* remove tokens that aren't used
* more purging
* simplify code
* switch to using decoder_start_token_id
* add doc
* Revert "major refactor (reuse-bart)"
This reverts commit 226dad15ca.
* decouple from bart
* remove unused code #1
* remove unused code #2
* remove unused code #3
* update instructions
* clean up
* move bleu eval to examples
* check import only once
* move data+gen script into files
* reuse via import
* take less space
* add prepare_seq2seq_batch (auto-tested)
* cleanup
* recode test to use json instead of yaml
* ignore keys not needed
* use the new -y in transformers-cli upload -y
* [xlm tok] config dict: fix str into int to match definition (#7034)
* [s2s] --eval_max_generate_length (#7018)
* Fix CI with change of name of nlp (#7054)
* nlp -> datasets
* More nlp -> datasets
* Woopsie
* More nlp -> datasets
* One last
* extending to support allen_nlp wmt models
- allow a specific checkpoint file to be passed
- more arg settings
- scripts for allen_nlp models
* sync with changes
* s/fsmt-wmt/wmt/ in model names
* s/fsmt-wmt/wmt/ in model names (p2)
* s/fsmt-wmt/wmt/ in model names (p3)
* switch to a better checkpoint
* typo
* make non-optional args such - adjust tests where possible or skip when there is no other choice
* consistency
* style
* adjust header
* cards moved (model rename)
* use best custom hparams
* update info
* remove old cards
* cleanup
* s/stas/facebook/
* update scores
* s/allen_nlp/allenai/
* url maps aren't needed
* typo
* move all the doc / build /eval generators to their own scripts
* cleanup
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* fix indent
* duplicated line
* style
* use the correct add_start_docstrings
* oops
* resizing can't be done with the core approach, due to 2 dicts
* check that the arg is a list
* style
* style
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* fix ZeroDivisionError and epoch counting
* Add test for num_train_epochs calculation in trainer.py
* Remove @require_non_multigpu for test_num_train_epochs_in_training
* Add tests and fix various bugs in ModelOutput
* Update tests/test_model_output.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add dataset for albert pretrain
* datacollator for albert pretrain
* naming, comprehension, file reading change
* data cleaning is no needed after this modification
* delete prints
* fix a bug
* file structure change
* add tests for albert datacollator
* remove random seed
* add back len and get item function
* sample file for testing and test code added
* format change for black
* more format change
* Style
* var assignment issue resolve
* add back wrongly deleted DataCollatorWithPadding in init file
* Style
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
* Initial model
* Fix upsampling
* Add special cls token id and test
* Formatting
* Test and fist FunnelTokenizerFast
* Common tests
* Fix the check_repo script and document Funnel
* Doc fixes
* Add all models
* Write doc
* Fix test
* Initial model
* Fix upsampling
* Add special cls token id and test
* Formatting
* Test and fist FunnelTokenizerFast
* Common tests
* Fix the check_repo script and document Funnel
* Doc fixes
* Add all models
* Write doc
* Fix test
* Fix copyright
* Forgot some layers can be repeated
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/modeling_funnel.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Address review comments
* Update src/transformers/modeling_funnel.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Address review comments
* Update src/transformers/modeling_funnel.py
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
* Slow integration test
* Make small integration test
* Formatting
* Add checkpoint and separate classification head
* Formatting
* Expand list, fix link and add in pretrained models
* Styling
* Add the model in all summaries
* Typo fixes
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
Since `generate()` does:
```
num_beams = num_beams if num_beams is not None else self.config.num_beams
```
This test fails if `model.config.num_beams > 1` (which is the case in the model I'm porting).
This fix makes the test setup unambiguous by passing an explicit `num_beams=1` to `generate()`.
Thanks.
