* AutoFeatureExtractor
* Init and first tests
* Tests
* Damn you gitignore
* Quality
* Defensive test for when not all backends are here
* Use pattern for Speech2Text models
* better names
* add attention mixin
* all slow tests in one class
* make helper methods static so we can test
* add local attention tests
* better names
* doc
* apply review suggestions
* Replace pkg_resources with importlib_metadata
Fixes#10964. The other reason for this change is that pkg_resources has been [deprecated](8fe85c22ce) in favor of importlib_metadata.
* Reduce to a single importlib_metadata import switch
* Trigger CI
Co-authored-by: Stas Bekman <stas@stason.org>
* 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>
* closes#10258
* typo
* reworked deberta test
* implemented the comments from BigBird01 regarding sequence pair encoding of deberta
* Update style
* VOCAB_FILES_NAMES is now a oneliner as suggested by @sgugger
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* added #fmt: on as requested by @sgugger
* Style
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* 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>
* Replace is_sagemaker_distributed_available
* Merge SageMakerTrainer into Trainer
* Test with shorter condition
* Put back deleted line
* Deprecate SageMakerTrainer and SageMakerTrainingArguments
* Apply suggestions from code review
Co-authored-by: Philipp Schmid <32632186+philschmid@users.noreply.github.com>
Co-authored-by: Philipp Schmid <32632186+philschmid@users.noreply.github.com>
* init
* first working test
* added todo for setup.py
* working test for single node multi node ddp and smd
* added tensorflow single node test
* added directory for pytorch and tensorflow due to different requirements.txt
* added directory for pytorch and tensorflow
* added comment for run_glue until it is available
* added output_dir to it
* smaller dataset to make test running faster
* adjust HP and script
* adjusted parameter for tensorflow
* refactored test scripts
* adjusted make file
* init
* first working test
* added todo for setup.py
* working test for single node multi node ddp and smd
* added tensorflow single node test
* added directory for pytorch and tensorflow due to different requirements.txt
* added directory for pytorch and tensorflow
* added comment for run_glue until it is available
* added output_dir to it
* smaller dataset to make test running faster
* adjust HP and script
* adjusted parameter for tensorflow
* refactored test scripts
* adjusted make file
* updated dlc container
* commented in all tests
* added both ecr images
* added new master branches
* debug
* added new datasets version
* init
* strange rebase bug
* removed changes
* changed min version for tests to work
* updated DLC
* added model parallel test
* removed test files
* removed test files
* tested with ned dlc
* added correct sagemaker sdk version
* adjust DLCs for official one
* reworked tests
* quality
* removed default profile added documentation to it
* added step in release for sagemaker tests
* reverted version for example script removed duplicated script and added install from master to requirements.txt
* removed mistaken .DS_Stores from mac
* fixed tests
* added Sylvains feedback
* make style
* added lysandre's feedback
* 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>
* fix backend tokenizer args override: key mismatch
* no touching the docs
* fix mpnet
* add mpnet to test
* fix test
Co-authored-by: theo <theo@matussie.re>
* Added check to ensure model name passed to from_pretrained and model are the same
* Added test to check from_pretrained throws assert error when passed an incompatiable model name
* Modified assert in from_pretrained with f-strings. Modified test to ensure desired assert message is being generated
* Added check to ensure config and model has model_type
* Fix FlauBERT heads
Co-authored-by: vimarsh chaturvedi <vimarsh chaturvedi>
Co-authored-by: Stas Bekman <stas@stason.org>
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
* Create modeling_flax_eletra with code copied from modeling_flax_bert
* Add ElectraForMaskedLM and ElectraForPretraining
* Add modeling test for Flax electra and fix naming and arg in Flax Electra model
* Add documentation
* Fix code style
* Create modeling_flax_eletra with code copied from modeling_flax_bert
* Add ElectraForMaskedLM and ElectraForPretraining
* Add modeling test for Flax electra and fix naming and arg in Flax Electra model
* Add documentation
* Fix code style
* Fix code quality
* Adjust tol in assert_almost_equal due to very small difference between model output, ranging 0.0010 - 0.0016
* Remove redundant ElectraPooler
* save intermediate
* adapt
* correct bert flax design
* adapt roberta as well
* finish roberta flax
* finish
* apply suggestions
* apply suggestions
Co-authored-by: Chris Nguyen <anhtu2687@gmail.com>
* Added debug prints
* Added config
* Added prints
* Added prints
* Added extra samples to SequentialDistributedSampler
* Added extra samples to SequentialDistributedSampler
Updated SequentialDistributedSampler call
* Added deubg prints
* Removed extra prints
* Making predicitons and labels multiple of batchsize
* updated number of microbatches
* Removed extra prints
* Made start_remainder similar to DistributedSamplerWithLoop
* Minor spacing update
* Added debug prints
Added config
Added prints
Added prints
* Added extra samples to SequentialDistributedSampler
Updated SequentialDistributedSampler call
Added extra samples to SequentialDistributedSampler
Added deubg prints
Removed extra prints
Making predicitons and labels multiple of batchsize
updated number of microbatches
Removed extra prints
Squashing redundant commits
* Made start_remainder similar to DistributedSamplerWithLoop
Minor spacing update
Made start_remainder similar to DistributedSamplerWithLoop
* Test and styling
* Rename test
Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>
* Apply black before checking copies
* Fix for class methods
* Deal with lonely brackets
* Remove debug and add forward changes
* Separate copies and fix test
* Add black as a test dependency
* Tests run on Docker
Co-authored-by: Morgan <funtowiczmo@gmail.com>
* Comments from code review
* Reply to itself
* Dependencies
Co-authored-by: Morgan <funtowiczmo@gmail.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.
* Allow to pass kwargs to model's from_pretrained when using pipeline.
* Disable the use of past_keys_values for GPT2 when exporting to ONNX.
* style
* Remove comment.
* Appease the documentation gods
* Fix style
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Stas Bekman