* Documentation about loading a fast tokenizer within Transformers
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* style
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Squash all commits into one
* Update ViTFeatureExtractor to use image_utils instead of torchvision
* Remove torchvision and add Pillow
* Small docs improvement
* Address most comments by @sgugger
* Fix tests
* Clean up conversion script
* Pooler first draft
* Fix quality
* Improve conversion script
* Make style and quality
* Make fix-copies
* Minor docs improvements
* Should use fix-copies instead of manual handling
* Revert "Should use fix-copies instead of manual handling"
This reverts commit fd4e591bce.
* Place ViT in alphabetical order
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Added embeddings layer
* Added layoutlm layers, main model, maskedlm and token classification classes
* Added model classes to tf auto models
* Added model to PT to TF conversion script
* Added model to doc README
* Added tests
* Removed unused imports
* Added layoutlm model, test, and doc for sequence classification, and fix imports in __init__.py
* Made tests pass!
* Fixed typos in imports and docs
* Fixed a typo in embeddings layer
* Removed imports
* Fixed formatting issues, imports, tests
* Added layoutlm layers, main model, maskedlm and token classification classes
* Added model classes to tf auto models
* Added model to PT to TF conversion script
* Removed unused imports
* Added layoutlm model, test, and doc for sequence classification, and fix imports in __init__.py
* Made tests pass!
* Fixed typos in imports and docs
* Removed imports
* Fixed small formatting issues
* Removed duplicates import from main __init__.py
* Chnaged deafult arg to true for adding pooling layer to tf layoutlm
* Fixed formatting issues
* Style
* Added copied from to classes copied from bert
* Fixed doc strings examples to work with layoutlm inputs
* Removed PyTorch reference in doc strings example
* Added integration tests
* Cleaned up initialization file
* Updated model checkpoint identifiers
* Fixed imports
Co-authored-by: Amir Tahmasbi <amir@ehsai.ca>
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
* [doc] [testing] extend -k section
This PR adds more examples on using `pytest -k` - I always forget that I want to use `-k A OR B` when I want several tests - I keep trying AND and it doesn't match any.
* style
* pass hf optimizer and scheduler to deepspeed if not specified in ds config
* pass hf optimizer and scheduler to deepspeed if not specified in ds config
* update
* make init_deepspeed support config dict
* fix docstring formatting
* clean up trainer's comments
* add new tests
* fix type
* composit argparse doesn't work
* style
* add a new test, rename others
* document new functionality
* complete tests, add docs
* style
* correct level
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* add new methods to the doc
* must tell DS we are using a non-native optimizer
* add protection against cpu_offload + HF optimizer combo
* fix the cli overrides
* sync docs + tests
* restore AdamW
* better docs
* need new version
* no longer needed
* remove outdate information
* refactor duplicated code
Co-authored-by: Stas Bekman <stas@stason.org>
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* [WIP] Adding new parameter to `generate`: `max_time`.
Generation by tokens number is sometimes a bit clunky because we don't
know how many tokens are good enough or even how many tokens are in
the payload (for pipelines users for instance). This leads to hard
to understand behavior.
This PR proposes a new argument `max_time` which is a float of seconds
for the allowed time for `generate` to run on.
Ideally combinations of `max_tokens=None`, `max_time=2` could be used to
generate as many tokens as possible within time budget.
NB: Another possible approach consists of passing a callback to `generate`
putting the caller in charge of the actual decision of when to stop
generating tokens. It opens the door to 'which args should we pass'
to this callback. It's hard to imagine other use-cases for this
early stopping behavior than time (that are not already covered by
parameters of generate)
* Revamp with StoppingCriteria
* Removing deprecated mentions.
* Forgot arguments to stopping criteria.
* Readding max_length it's not just used as a stopping criteria.
* Default value for `stopping_criteria`.
* Address @patrickvonplaten comments.
- More docstrings
- Actual doc
- Include in global namespace
- Remove TF work.
* Put back `max_length` (deprecation different PR).
* Doc quality.
* Fixing old behavior without `stopping_criteria` but with `max_length`.
Making sure we don't break that in the future.
* Adding more tests for possible inconsistencies between
`max_length` and `stopping_criteria`.
* Fixing the torch imports.
* Create modeling_tf_dpr.py
* Add TFDPR
* Add back TFPegasus, TFMarian, TFMBart, TFBlenderBot
last commit accidentally deleted these 4 lines, so I recover them back
* Add TFDPR
* Add TFDPR
* clean up some comments, add TF input-style doc string
* Add TFDPR
* Make return_dict=False as default
* Fix return_dict bug (in .from_pretrained)
* Add get_input_embeddings()
* Create test_modeling_tf_dpr.py
The current version is already passed all 27 tests!
Please see the test run at :
https://colab.research.google.com/drive/1czS_m9zy5k-iSJbzA_DP1k1xAAC_sdkf?usp=sharing
* fix quality
* delete init weights
* run fix copies
* fix repo consis
* del config_class, load_tf_weights
They shoud be 'pytorch only'
* add config_class back
after removing it, test failed ... so totally only removing "use_tf_weights = None" on Lysandre suggestion
* newline after .. note::
* import tf, np (Necessary for ModelIntegrationTest)
* slow_test from_pretrained with from_pt=True
At the moment we don't have TF weights (since we don't have official official TF model)
Previously, I did not run slow test, so I missed this bug
* Add simple TFDPRModelIntegrationTest
Note that this is just a test that TF and Pytorch gives approx. the same output.
However, I could not test with the official DPR repo's output yet
* upload correct tf model
* remove position_ids as missing keys
* create modeling_tf_rag
* add tests for tf
* add tf tests
* revert wrong pt commit
* further refactor
* further refactor
* refactor
* Update modeling_tf_rag.py
- input_processing
- fix prepare_input_for_generation (mostly fix generate bug)
- bring back from_pretrained hack in order to test generate
* delete colab pieces of code
* Show case of greedy "generate"
Temporarily change from beam_search test to greedy_search test to show case that TF and PT do get equivalent output.
* cosmetic update
* correct typos
* update
* push some progress
* make easy check
* fix rag save from pretrained
* Update src/transformers/modeling_tf_utils.py
* remove commented out lines
* delete unnecessary lines
* add simple test case for nq_checkpoint
Add nq_checkpoint test to show that current version without hack still fails
* temporarily put ugly hack back again
* Add TFRagSequenceForGeneration!!
* __init__.py , import TFRagSequenceForGeneration
* Add TFRagSequence tests!
* rag init.py - add TFRagSequenceForGeneration
* fix from_pretrained
* fix prepare_inputs_for_generation
* Beam search for RagToken!
* minor clean up
* add tf.cast in TFRagModel
* More tf.cast
* Add all remaining tests (still have issues)
* delete all T5 related
* make style
* fix load weight prefix
* fix bart
* fix return_dict for tf_rag
make all tests pass .. Hooray
* fix some tests
* fix code quality
* fix qualtiy check
* finish tests tf rag
* add tf rag to docs
* remove TFT5 from docstring
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* remove TFT5 from docstring
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Delete outdated comments
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* improve doc strings
* add generative model classes
* fix adjust token logic
* refactor generate for TFRag
* using shape_list, not _get_shape
Co-authored-by: Julien Plu <plu.julien@gmail.com>
* axis=[1]->axis=1
* delete NEED_HELP comment
* improve readability
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* improve readability
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* improve readability
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Indicating model is in a developing state in docstrings
As suggested by Julien
* small last changes
* apply sylvains suggestions
* finish tf rag
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: patrickvonplaten <patrick@huggingface.co>
Co-authored-by: Julien Plu <plu.julien@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* offline mode start
* add specific values
* fix fallback
* add test
* better values check and range
* test that actually works
* document the offline mode
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* more strict check
* cleaner test
* pt-only test
* style
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* feat: Adds three definitions to glossary from @cronoik
Needed a definition for transformer which in turn needed 2 more definitions
To do with issue https://github.com/huggingface/transformers/issues/9078
* fix: Adjusts definition of neural network to make it easier to read
* Introduce save_strategy training argument
* deprecate EvaluationStrategy
* collapse EvaluationStrategy and LoggingStrategy into a single
IntervalStrategy enum
* modify tests to use modified enum
* Fix None in add_token_positions - issue #10210
Fix None in add_token_positions related to the issue #10210
* add_token_positions fix None values in end_positions vector
add_token_positions fix None in end_positions vector as proposed by @joeddav
* expand install instructions
* fix
* white space
* rewrite as discussed in the PR
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* change the wording to encourage issue report
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Add LayoutLMForSequenceClassification and integration tests
Improve docs
Add LayoutLM notebook to list of community notebooks
* Make style & quality
* Address comments by @sgugger, @patrickvonplaten and @LysandreJik
* Fix rebase with master
* Reformat in one line
* Improve code examples as requested by @patrickvonplaten
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Define new output dataclasses for greedy generation
* Add output_[...] flags in greedy generation methods
Added output_attentions, output_hidden_states, output_scores flags in
generate and greedy_search methods in GenerationMixin.
* [WIP] Implement logic and tests for output flags in generation
* Update GreedySearchOutput classes & docstring
* Implement greedy search output accumulation logic
Update greedy_search unittests
Fix generate method return value docstring
Properly init flags with the default config
* Update configuration to add output_scores flag
* Fix test_generation_utils
Sort imports and fix isinstance tests for GreedySearchOutputs
* Fix typo in generation_utils
* Add return_dict_in_generate for backwards compatibility
* Add return_dict_in_generate flag in config
* Fix tyPo in configuration
* Fix handling of attentions and hidden_states flags
* Make style & quality
* first attempt attentions
* some corrections
* improve tests
* special models requires special test
* disable xlm test for now
* clean tests
* fix for tf
* isort
* Add output dataclasses for other generation methods
* Add logic to return dict in sample generation
* Complete test for sample generation
- Pass output_attentions and output_hidden_states flags to encoder in
encoder-decoder models
- Fix import satements order in test_generation_utils file
* Add logic to return dict in sample generation
- Refactor tests to avoid using self.assertTrue, which provides
scarce information when the test fails
- Add tests for the three beam_search methods: vanilla, sample and
grouped
* Style doc
* Fix copy-paste error in generation tests
* Rename logits to scores and refactor
* Refactor group_beam_search for consistency
* make style
* add sequences_scores
* fix all tests
* add docs
* fix beam search finalize test
* correct docstring
* clean some files
* Made suggested changes to the documentation
* Style doc ?
* Style doc using the Python util
* Update src/transformers/generation_utils.py
* fix empty lines
* fix all test
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* first commit
* change phobert to phoBERT as per author in overview
* v3 and v4 both runs on same code hence there is no need to differentiate them
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* create model
* add integration
* save current state
* make integration tests pass
* add one more test
* add explanation to tests
* remove from bart
* add padding
* remove unnecessary test
* make all tests pass
* re-add cookie cutter tests
* finish PyTorch
* fix attention test
* Update tests/test_modeling_common.py
* revert change
* remove unused file
* add string to doc
* save intermediate
* make tf integration tests pass
* finish tf
* fix doc
* fix docs again
* add led to doctree
* add to auto tokenizer
* added tips for led
* make style
* apply jplus statements
* correct tf longformer
* apply lysandres suggestions
* apply sylvains suggestions
* Apply suggestions from code review
* Use extlinks to point hyperlink with the version of code
* Point to version on release and master until then
* Apply style
* Correct links
* Add missing backtick
* Simple missing backtick after all.
Co-authored-by: Raghavendra Sugeeth P S <raghav-5305@raghav-5305.csez.zohocorpin.com>
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
* add past_key_values
* add use_cache option
* make mask before cutting ids
* adjust position_ids according to past_key_values
* flatten past_key_values
* fix positional embeds
* fix _reorder_cache
* set use_cache to false when not decoder, fix attention mask init
* add test for caching
* add past_key_values for Roberta
* fix position embeds
* add caching test for roberta
* add doc
* make style
* doc, fix attention mask, test
* small fixes
* adress patrick's comments
* input_ids shouldn't start with pad token
* use_cache only when decoder
* make consistent with bert
* make copies consistent
* add use_cache to encoder
* add past_key_values to tapas attention
* apply suggestions from code review
* make coppies consistent
* add attn mask in tests
* remove copied from longformer
* apply suggestions from code review
* fix bart test
* nit
* simplify model outputs
* fix doc
* fix output ordering
* Add label smoothing in Trainer
* Add options for scheduler and Adafactor in Trainer
* Put Seq2SeqTrainer in the main lib
* Apply suggestions from code review
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Address review comments and adapt scripts
* Documentation
* Move test not using script to tests folder
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* First commit: adding all files from tapas_v3
* Fix multiple bugs including soft dependency and new structure of the library
* Improve testing by adding torch_device to inputs and adding dependency on scatter
* Use Python 3 inheritance rather than Python 2
* First draft model cards of base sized models
* Remove model cards as they are already on the hub
* Fix multiple bugs with integration tests
* All model integration tests pass
* Remove print statement
* Add test for convert_logits_to_predictions method of TapasTokenizer
* Incorporate suggestions by Google authors
* Fix remaining tests
* Change position embeddings sizes to 512 instead of 1024
* Comment out positional embedding sizes
* Update PRETRAINED_VOCAB_FILES_MAP and PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
* Added more model names
* Fix truncation when no max length is specified
* Disable torchscript test
* Make style & make quality
* Quality
* Address CI needs
* Test the Masked LM model
* Fix the masked LM model
* Truncate when overflowing
* More much needed docs improvements
* Fix some URLs
* Some more docs improvements
* Test PyTorch scatter
* Set to slow + minify
* Calm flake8 down
* First commit: adding all files from tapas_v3
* Fix multiple bugs including soft dependency and new structure of the library
* Improve testing by adding torch_device to inputs and adding dependency on scatter
* Use Python 3 inheritance rather than Python 2
* First draft model cards of base sized models
* Remove model cards as they are already on the hub
* Fix multiple bugs with integration tests
* All model integration tests pass
* Remove print statement
* Add test for convert_logits_to_predictions method of TapasTokenizer
* Incorporate suggestions by Google authors
* Fix remaining tests
* Change position embeddings sizes to 512 instead of 1024
* Comment out positional embedding sizes
* Update PRETRAINED_VOCAB_FILES_MAP and PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
* Added more model names
* Fix truncation when no max length is specified
* Disable torchscript test
* Make style & make quality
* Quality
* Address CI needs
* Test the Masked LM model
* Fix the masked LM model
* Truncate when overflowing
* More much needed docs improvements
* Fix some URLs
* Some more docs improvements
* Add add_pooling_layer argument to TapasModel
Fix comments by @sgugger and @patrickvonplaten
* Fix issue in docs + fix style and quality
* Clean up conversion script and add task parameter to TapasConfig
* Revert the task parameter of TapasConfig
Some minor fixes
* Improve conversion script and add test for absolute position embeddings
* Improve conversion script and add test for absolute position embeddings
* Fix bug with reset_position_index_per_cell arg of the conversion cli
* Add notebooks to the examples directory and fix style and quality
* Apply suggestions from code review
* Move from `nielsr/` to `google/` namespace
* Apply Sylvain's comments
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Rogge Niels <niels.rogge@howest.be>
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
* add model parallelism to T5EncoderModel
add model parallelism to T5EncoderModel
* remove decoder from T5EncoderModel parallelize
* uodate T5EncoderModel docs
* Extend T5ModelTest for T5EncoderModel
* fix T5Stask using range for get_device_map
* fix style
Co-authored-by: Ahmed Elnaggar <elnaggar@rostlab.informatik.tu-muenchen.de>
* rm all model cards
* Update the .rst
@sgugger it is still not super crystal clear/streamlined so let me know if any ideas to make it simpler
* Add a rootlevel README.md with simple instructions/context
* Update docs/source/model_sharing.rst
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* make style
* rm all model cards
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* remove make on the fly linear embedding
* start refactor
* big first refactor
* save intermediate
* save intermediat
* correct mask issue
* save tests
* refactor padding masks
* make all tests pass
* further refactor
* make pegasus test pass
* fix bool if
* fix leftover tests
* continue
* bart renaming
* delete torchscript test hack
* fix imports in tests
* correct shift
* fix docs and repo cons
* re-add fix for FSTM
* typo in test
* fix typo
* fix another typo
* continue
* hot fix 2 for tf
* small fixes
* refactor types linting
* continue
* finish refactor
* fix import in tests
* better bart names
* further refactor and add test
* delete hack
* apply sylvains and lysandres commens
* small perf improv
* further perf improv
* improv perf
* fix typo
* make style
* small perf improv
* diverse beam search
* bug fixes
* bug fixes
* bug fix
* separate out diverse_beam_search function
* separate out diverse_beam_search function
* bug fix
* improve code quality
* bug fix
* bug fix
* separate out diverse beam search scorer
* code format
* code format
* code format
* code format
* add test
* code format
* documentation changes
* code quality
* add slow integration tests
* more general name
* refactor into logits processor
* add test
* avoid too much copy paste
* refactor
* add to docs
* fix-copies
* bug fix
* Revert "bug fix"
This reverts commit c99eb5a8dc.
* improve comment
* implement sylvains feedback
Co-authored-by: Ayush Jain <a.jain@sprinklr.com>
Co-authored-by: ayushtiku5 <40797286+ayushtiku5@users.noreply.github.com>
* Add TFGPT2ForSequenceClassification based on DialogRPT
* Add TFGPT2ForSequenceClassification based on DialogRPT
* TFGPT2ForSequenceClassification based on DialogRPT-refactored code, implemented review comments and added input processing
* Add TFGPT2ForSequenceClassification based on DialogRPT
* TFGPT2ForSequenceClassification based on DialogRPT-refactored code, implemented review comments and added input processing
* code refactor for latest other TF PR
* code refactor
* code refactor
* Update modeling_tf_gpt2.py
* Add badge w/ number of models on the hub
* try to apease @sgugger 😇
* not sure what this `c` was about [ci skip]
* Fix script and move stuff around
* Fix doc styling error
Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>
* fix mems in xlnet
* fix use_mems
* fix use_mem_len
* fix use mems
* clean docs
* fix tf typo
* make xlnet tf for generation work
* fix tf test
* refactor use cache
* add use cache for missing models
* correct use_cache in generate
* correct use cache in tf generate
* fix tf
* correct getattr typo
* make sylvain happy
* change in docs as well
* do not apply to cookie cutter statements
* fix tf test
* make pytorch model fully backward compatible
* Add early stopping patience and minimum threshold metric must improve to prevent early stopping to pytorch trainer
* Add early stopping test
* Set patience counter to 0 if best metric not defined yet
* Make early stopping a callback. Add callback event for updating the best metric for early stopping callback to trigger on.
* Run make style
* make funciton name sensible
* Improve new argument docstring wording and hope that flakey CI test passes.
* Use on_evaluation callback instead of custom. Remove some debug printing
* Move early stopping arguments and state into early stopping callback
* Run make style
* Remove old code
* Fix docs formatting. make style went rogue on me.
* Remove copied attributes and fix variable
* Add assertions on training arguments instead of mutating them. Move comment out of public docs.
* Make separate test for early stopping callback. Add test of invalid arguments.
* Run make style... I remembered before CI this time!
* appease flake8
* Add EarlyStoppingCallback to callback docs
* Make docstring EarlyStoppingCallabck match other callbacks.
* Fix typo in docs
* working on LongformerForSequenceClassification
* add TFLongformerForMultipleChoice
* add TFLongformerForTokenClassification
* use add_start_docstrings_to_model_forward
* test TFLongformerForSequenceClassification
* test TFLongformerForMultipleChoice
* test TFLongformerForTokenClassification
* remove test from repo
* add test and doc for TFLongformerForSequenceClassification, TFLongformerForTokenClassification, TFLongformerForMultipleChoice
* add requested classes to modeling_tf_auto.py
update dummy_tf_objects
fix tests
fix bugs in requested classes
* pass all tests except test_inputs_embeds
* sync with master
* pass all tests except test_inputs_embeds
* pass all tests
* pass all tests
* work on test_inputs_embeds
* fix style and quality
* make multi choice work
* fix TFLongformerForTokenClassification signature
* fix TFLongformerForMultipleChoice, TFLongformerForSequenceClassification signature
* fix mult choice
* fix mc hint
* fix input embeds
* fix input embeds
* refactor input embeds
* fix copy issue
* apply sylvains changes and clean more
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Updated the Extractive Question Answering code snippets
The Extractive Question Answering code snippets do not work anymore since the models return task-specific output objects. This commit fixes the pytorch and tensorflow examples but adding `.values()` to the model call.
* Update task_summary.rst
* Tokenizers should be framework agnostic
* Run the slow tests
* Not testing
* Fix documentation
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* <small>tiny typo</small>
* Tokenizers: ability to load from model subfolder
* use subfolder for local files as well
* Uniformize model shortcut name => model id
* from s3 => from huggingface.co
Co-authored-by: Quentin Lhoest <lhoest.q@gmail.com>
* Put models in subfolders
* Styling
* Fix imports in tests
* More fixes in test imports
* Sneaky hidden imports
* Fix imports in doc files
* More sneaky imports
* Finish fixing tests
* Fix examples
* Fix path for copies
* More fixes for examples
* Fix dummy files
* More fixes for example
* More model import fixes
* Is this why you're unhappy GitHub?
* Fix imports in conver command
* Use the CI to identify failing tests
* Remove from all examples and tests
* More default switch
* Fixes
* More test fixes
* More fixes
* Last fixes hopefully
* Use the CI to identify failing tests
* Remove from all examples and tests
* More default switch
* Fixes
* More test fixes
* More fixes
* Last fixes hopefully
* Run on the real suite
* Fix slow tests
* First addition of Flax/Jax documentation
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* make style
* Ensure input order match between Bert & Roberta
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Install dependencies "all" when building doc
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* wraps build_doc deps with ""
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Addressing @sgugger comments.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Use list to highlight JAX features.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Make style.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Let's not look to much into the future for now.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Style
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
* Create modeling_tf_dpr.py
* Add TFDPR
* Add back TFPegasus, TFMarian, TFMBart, TFBlenderBot
last commit accidentally deleted these 4 lines, so I recover them back
* Add TFDPR
* Add TFDPR
* clean up some comments, add TF input-style doc string
* Add TFDPR
* Make return_dict=False as default
* Fix return_dict bug (in .from_pretrained)
* Add get_input_embeddings()
* Create test_modeling_tf_dpr.py
The current version is already passed all 27 tests!
Please see the test run at :
https://colab.research.google.com/drive/1czS_m9zy5k-iSJbzA_DP1k1xAAC_sdkf?usp=sharing
* fix quality
* delete init weights
* run fix copies
* fix repo consis
* del config_class, load_tf_weights
They shoud be 'pytorch only'
* add config_class back
after removing it, test failed ... so totally only removing "use_tf_weights = None" on Lysandre suggestion
* newline after .. note::
* import tf, np (Necessary for ModelIntegrationTest)
* slow_test from_pretrained with from_pt=True
At the moment we don't have TF weights (since we don't have official official TF model)
Previously, I did not run slow test, so I missed this bug
* Add simple TFDPRModelIntegrationTest
Note that this is just a test that TF and Pytorch gives approx. the same output.
However, I could not test with the official DPR repo's output yet
* upload correct tf model
* remove position_ids as missing keys
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: patrickvonplaten <patrick@huggingface.co>
* [testing utils] get_auto_remove_tmp_dir default change
Now that I have been using `get_auto_remove_tmp_dir default change` for a while, I realized that the defaults aren't most optimal.
99% of the time we want the tmp dir to be empty at the beginning of the test - so changing the default to `before=True` - this shouldn't impact any tests since this feature is used only during debug.
* simplify things
* update docs
* fix doc layout
* style
* Update src/transformers/testing_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* better 3-state doc
* style
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* s/tmp/temporary/ + style
* correct the statement
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* add training tests
* correct longformer
* fix docs
* fix some tests
* fix some more train tests
* remove ipdb
* fix multiple edge case model training
* fix funnel and prophetnet
* clean gpt models
* undo renaming of albert
* Output cross-attention with decoder attention output
* Update src/transformers/modeling_bert.py
* add cross-attention for t5 and bart as well
* fix tests
* correct typo in docs
* add sylvains and sams comments
* correct typo
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Output global_attentions in Longformer models
* make style
* small refactoring
* fix tests
* make fix-copies
* add for tf as well
* remove comments in test
* make fix-copies
* make style
* add docs
* make docstring pretty
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>
* first draft
* show design proposition for new generate method
* up
* make better readable
* make first version
* gpt2 tests pass
* make beam search for gpt2 work
* add first encoder-decoder code
* delete typo
* make t5 work
* save indermediate
* make bart work with beam search
* finish beam search bart / t5
* add default kwargs
* make more tests pass
* fix no bad words sampler
* some fixes and tests for all distribution processors
* fix test
* fix rag slow tests
* merge to master
* add nograd to generate
* make all slow tests pass
* speed up generate
* fix edge case bug
* small fix
* correct typo
* add type hints and docstrings
* fix typos in tests
* add beam search tests
* add tests for beam scorer
* fix test rag
* finish beam search tests
* move generation tests in seperate file
* fix generation tests
* more tests
* add aggressive generation tests
* fix tests
* add gpt2 sample test
* add more docstring
* add more docs
* finish doc strings
* apply some more of sylvains and sams comments
* fix some typos
* make fix copies
* apply lysandres and sylvains comments
* final corrections on examples
* small fix for reformer
* move the helper code into testing_utils
* port test_trainer_distributed to work with pytest
* improve docs
* simplify notes
* doc
* doc
* style
* doc
* further improvements
* torch might not be available
* real fix
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* first attempt to add AzureML callbacks
* func arg fix
* var name fix, but still won't fix error...
* fixing as in https://discuss.huggingface.co/t/how-to-integrate-an-azuremlcallback-for-logging-in-azure/1713/2
* Avoid lint check of azureml import
* black compliance
* Make isort happy
* Fix point typo in docs
* Add AzureML to Callbacks docs
* Attempt to make sphinx happy
* Format callback docs
* Make documentation style happy
* Make docs compliant to style
Co-authored-by: Davide Fiocco <davide.fiocco@frontiersin.net>
* Important files
* Styling them all
* Revert "Styling them all"
This reverts commit 7d029395fd.
* Syling them for realsies
* Fix syntax error
* Fix benchmark_utils
* More fixes
* Fix modeling auto and script
* Remove new line
* Fixes
* More fixes
* Fix more files
* Style
* Add FSMT
* More fixes
* More fixes
* More fixes
* More fixes
* Fixes
* More fixes
* More fixes
* Last fixes
* Make sphinx happy
* Fix minor typos
Fix minor typos in the docs.
* Update docs/source/preprocessing.rst
Clearer data structure description.
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Add MLflow integration class
Add integration code for MLflow in integrations.py along with the code
that checks that MLflow is installed.
* Add MLflowCallback import
Add import of MLflowCallback in trainer.py
* Handle model argument
Allow the callback to handle model argument and store model config items as hyperparameters.
* Log parameters to MLflow in batches
MLflow cannot log more than a hundred parameters at once.
Code added to split the parameters into batches of 100 items and log the batches one by one.
* Fix style
* Add docs on MLflow callback
* Fix issue with unfinished runs
The "fluent" api used in MLflow integration allows only one run to be active at any given moment. If the Trainer is disposed off and a new one is created, but the training is not finished, it will refuse to log the results when the next trainer is created.
* Add MLflow integration class
Add integration code for MLflow in integrations.py along with the code
that checks that MLflow is installed.
* Add MLflowCallback import
Add import of MLflowCallback in trainer.py
* Handle model argument
Allow the callback to handle model argument and store model config items as hyperparameters.
* Log parameters to MLflow in batches
MLflow cannot log more than a hundred parameters at once.
Code added to split the parameters into batches of 100 items and log the batches one by one.
* Fix style
* Add docs on MLflow callback
* Fix issue with unfinished runs
The "fluent" api used in MLflow integration allows only one run to be active at any given moment. If the Trainer is disposed off and a new one is created, but the training is not finished, it will refuse to log the results when the next trainer is created.
* slow tests should be slow
* exception note
* style
* integrate LysandreJik's notes with some expansions
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* another slow test
* fix link, and prose
* clarify.
* note from Sam
* typo
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* add CustomHFIndex
* typo in config
* update tests
* add custom dataset example
* clean script
* update test data
* minor in test
* docs
* docs
* style
* fix imports
* allow to pass the indexed dataset directly
* update tests
* use multiset DPR
* address thom and patrick's comments
* style
* update dpr tokenizer
* add output_dir flag in use_own_knowledge_dataset.py
* allow custom datasets in examples/rag/finetune.py
* add test for custom dataset in distributed rag retriever
* splitting fast and slow tokenizers [WIP]
* [WIP] splitting sentencepiece and tokenizers dependencies
* update dummy objects
* add name_or_path to models and tokenizers
* prefix added to file names
* prefix
* styling + quality
* spliting all the tokenizer files - sorting sentencepiece based ones
* update tokenizer version up to 0.9.0
* remove hard dependency on sentencepiece 🎉
* and removed hard dependency on tokenizers 🎉
* update conversion script
* update missing models
* fixing tests
* move test_tokenization_fast to main tokenization tests - fix bugs
* bump up tokenizers
* fix bert_generation
* update ad fix several tokenizers
* keep sentencepiece in deps for now
* fix funnel and deberta tests
* fix fsmt
* fix marian tests
* fix layoutlm
* fix squeezebert and gpt2
* fix T5 tokenization
* fix xlnet tests
* style
* fix mbart
* bump up tokenizers to 0.9.2
* fix model tests
* fix tf models
* fix seq2seq examples
* fix tests without sentencepiece
* fix slow => fast conversion without sentencepiece
* update auto and bert generation tests
* fix mbart tests
* fix auto and common test without tokenizers
* fix tests without tokenizers
* clean up tests lighten up when tokenizers + sentencepiece are both off
* style quality and tests fixing
* add sentencepiece to doc/examples reqs
* leave sentencepiece on for now
* style quality split hebert and fix pegasus
* WIP Herbert fast
* add sample_text_no_unicode and fix hebert tokenization
* skip FSMT example test for now
* fix style
* fix fsmt in example tests
* update following Lysandre and Sylvain's comments
* Update src/transformers/testing_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/testing_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Add Documentation for GPT-1 Classification
* Add GPT-1 with Classification head
* Add tests for GPT-1 Classification
* Add GPT-1 For Classification to auto models
* Remove authorized missing keys, change checkpoint to openai-gpt
* [WIP] SP tokenizers
* fixing tests for T5
* WIP tokenizers
* serialization
* update T5
* WIP T5 tokenization
* slow to fast conversion script
* Refactoring to move tokenzier implementations inside transformers
* Adding gpt - refactoring - quality
* WIP adding several tokenizers to the fast world
* WIP Roberta - moving implementations
* update to dev4 switch file loading to in-memory loading
* Updating and fixing
* advancing on the tokenizers - updating do_lower_case
* style and quality
* moving forward with tokenizers conversion and tests
* MBart, T5
* dumping the fast version of transformer XL
* Adding to autotokenizers + style/quality
* update init and space_between_special_tokens
* style and quality
* bump up tokenizers version
* add protobuf
* fix pickle Bert JP with Mecab
* fix newly added tokenizers
* style and quality
* fix bert japanese
* fix funnel
* limite tokenizer warning to one occurence
* clean up file
* fix new tokenizers
* fast tokenizers deep tests
* WIP adding all the special fast tests on the new fast tokenizers
* quick fix
* adding more fast tokenizers in the fast tests
* all tokenizers in fast version tested
* Adding BertGenerationFast
* bump up setup.py for CI
* remove BertGenerationFast (too early)
* bump up tokenizers version
* Clean old docstrings
* Typo
* Update following Lysandre comments
Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>
