* [WIP] Add TFWav2Vec2Model
Work in progress for adding a tensorflow version of Wav2Vec2
* feedback changes
* small fix
* Test Feedback Round 1
* Add SpecAugment and CTC Loss
* correct spec augment mask creation
* docstring and correct copyright
* correct bugs
* remove bogus file
* finish tests correction
* del unnecessary layers
* Update src/transformers/models/wav2vec2/modeling_tf_wav2vec2.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* make style
* correct final bug
* Feedback Changes
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Start working on FlaxBart
* Create modeling_flax_bart.py
* Write FlaxBartAttention
* Add FlaxBartEncoderLayer
* Add FlaxBartDecoderLayer and some typing
* Add helepr function for FlaxBart
* shift_tokens_right
* _make_causal_mask
* _expand_mask
* Add PositionalEmbedding and fix init_std naming
* Add FlaxBartPretrainedModel
* Add FlaxBartEncoder
* Add FlaxBartEncoder
* Add FlaxBartEncoder among modules to be imported
* YET WE CANNOT INITIALIZE THAT!! :(
* Make BartEncoder working
Change BartEncoder to instance of nn.Module so far
* Add FlaxBartDecoder
* Add FlaxBartModel
* TODO to make model run -> Prepapre model inputs
* Resolve padding
* Add FlaxBartModel
* Add FlaxBartModel into importable modules
* Remove FlaxBartEncoder and FlaxBartDecoder from importable modules
* make style; not properly working
* make style; make quality not pass due to some import I left
* Remove TODO for padding_idx in nn.Embed so far
* Add FlaxBartForConditionalGeneration
* Incorporate Flax model output classes, i.e. return_dict
* Add another models and incorporate use_cache arg
* Add FlaxBartForSequenceClassification and FlaxBartForQuestionAnswering
* Incorporate use_cache arg from PyTorch implementation
* Add all necessary Flax output utils
* Add FlaxBartForCausalLM; not working yet'
* Add minor improvements; still lacks some functionality
* Update docs, src and tests
* Add support of FlaxBart to docs/source
* Fix some bugs in FlaxBart souce code
* Add some neccessary tests for FlaxBart models - jit_compilation not passing
* Fix tests and add test_head_masking
* Fix tests for @jax.jit computation
* Add test_head_masking
* Migrate FlaxBart tests from jax.numpy to numpy
* Remove FlaxBartForCausalLM
* Clean repo
* fix bart model weight structure
* Fix FlaxBartForSequenceClassification
Slicing is not possible to use below jit, therefore, selecting sentence
representation from hidden_states must be changed.
* Allow FlaxBartForSequenceClassification for testing pt_flax equivalence
* Allow testing for FlaxBartForQA for pt_flax equivalence
* Add a comment to FlaxBartForSequenceClassification + change noise from 1e-3 to 1e-6
* remove past_key_values
* remove inputs_mebeds and make input_ids required
* add position ids
* re-write attention layer
* fix dataclass
* fix pos embeds and attention output
* fix pos embeds
* expose encode method
* expose decode method
* move docstring to top
* add cache for causal attn layer
* remove head masking for now
* s2s greedy search first pass
* boom boom
* fix typos
* fix greedy generate for bart
* use encoder, decoder layers instead of num_hidden_layers
* handle encoder_outputs
* cleanup
* simplify decoding
* more clean-up
* typos
* Change header + add {decoder_,}position_ids into 2 models
* add BartConfig
* fix existing tests
* add encode, decode methods
* Fix shift_tokens_right for JIT compilation + clarify one condition
* fix decode
* encoder => encode
* simplify generate
* add tests for encode and decode
* style
* add tests for cache
* fix equivalence tests
* sample generate now works with seq2seq
* generation tests
* initialize dense layers
* docstring and cleanup
* quality
* remove get/set input_embeddings
* address Patricks suggestions
* decode for every model, remove encoder_outputs from call
* update tests accordingly
* decode returns only decoder outputs and logits
* fix arguments
* doc encode, decode methods
* correct base_model_prefix
* fix test for seq classif model
* fix docs
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* adding vit for flax
* added test for Flax-vit and some bug-fixes
* overrided methods where variable changes were necessary for flax_vit test
* added FlaxViTForImageClassification for test
* Update src/transformers/models/vit/modeling_flax_vit.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* made changes suggested in PR
* Adding jax-vit models for autoimport
* swapping num_channels and height,width dimension
* fixing the docstring for torch-like inputs for VIT
* add model to main init
* add docs
* doc, fix-copies
* docstrings
* small test fixes
* fix docs
* fix docstr
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* style
Co-authored-by: jayendra <jayendra@infocusp.in>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Squash all commits of modeling_detr_v7 branch into one
* Improve docs
* Fix tests
* Style
* Improve docs some more and fix most tests
* Fix slow tests of ViT, DeiT and DETR
* Improve replacement of batch norm
* Restructure timm backbone forward
* Make DetrForSegmentation support any timm backbone
* Fix name of output
* Address most comments by @LysandreJik
* Give better names for variables
* Conditional imports + timm in setup.py
* Address additional comments by @sgugger
* Make style, add require_timm and require_vision to testsé
* Remove train_backbone attribute of DetrConfig, add methods to freeze/unfreeze backbone
* Add png files to fixtures
* Fix type hint
* Add timm to workflows
* Add `BatchNorm2d` to the weight initialization
* Fix retain_grad test
* Replace model checkpoints by Facebook namespace
* Fix name of checkpoint in test
* Add user-friendly message when scipy is not available
* Address most comments by @patrickvonplaten
* Remove return_intermediate_layers attribute of DetrConfig and simplify Joiner
* Better initialization
* Scipy is necessary to get sklearn metrics
* Rename TimmBackbone to DetrTimmConvEncoder and rename DetrJoiner to DetrConvModel
* Make style
* Improve docs and add 2 community notebooks
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
* Added Big Bird Fast Tokenizer initial file
* style fixes
* flake fixes
* Added big bird fast tokenizer to init files
* Added big bird fast to Auto tokenization
* fix styles
* minor quality fixes
* Added initial test code
* Fix SpmConverter when precompiled_charsmap doesn't exist
* fixed post processor
* minor style fix
* minor fix input names
* Actually fix identity normalization
* style
* Added token type ids to fast tokenizer
* style
* flake fix
* fix copies
Co-authored-by: Anthony MOI <m.anthony.moi@gmail.com>
* Add the ImageClassificationPipeline
* Code review
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>
* Have `load_image` at the module level
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>
* add electra model to flax
* Remove Electra Next Sentence Prediction model added by mistake
* fix parameter sharing and loosen equality threshold
* fix styling issues
* add mistaken removen imports
* fix electra table
* Add FlaxElectra to automodels and fixe docs
* fix issues pointed out the PR
* fix flax electra to comply with latest changes
* remove stale class
* add copied from
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add flax roberta
* make style
* correct initialiazation
* modify model to save weights
* fix copied from
* fix copied from
* correct some more code
* add more roberta models
* Apply suggestions from code review
* merge from master
* finish
* finish docs
Co-authored-by: Patrick von Platen <patrick@huggingface.co>
* Rebase with master
* Minor bug fix in docs
* Copy files from adding_luke_v2 and improve docs
* change the default value of use_entity_aware_attention to True
* remove word_hidden_states
* fix head models
* fix tests
* fix the conversion script
* add integration tests for the pretrained large model
* improve docstring
* Improve docs, make style
* fix _init_weights for pytorch 1.8
* improve docs
* fix tokenizer to construct entity sequence with [MASK] entity when entities=None
* Make fix-copies
* Make style & quality
* Bug fixes
* Add LukeTokenizer to init
* Address most comments by @patil-suraj and @LysandreJik
* rename _compute_extended_attention_mask to get_extended_attention_mask
* add comments to LukeSelfAttention
* fix the documentation of the tokenizer
* address comments by @patil-suraj, @LysandreJik, and @sgugger
* improve docs
* Make style, quality and fix-copies
* Improve docs
* fix docs
* add "entity_span_classification" task
* update example code for LukeForEntitySpanClassification
* improve docs
* improve docs
* improve the code example in luke.rst
* rename the classification layer in LukeForEntityClassification from typing to classifier
* add bias to the classifier in LukeForEntitySpanClassification
* update docs to use fine-tuned hub models in code examples of the head models
* update the example sentences
* Make style & quality
* Add require_torch to tokenizer tests
* Add require_torch to tokenizer tests
* Address comments by @sgugger and add community notebooks
* Make fix-copies
Co-authored-by: Ikuya Yamada <ikuya@ikuya.net>
* Base move
* Examples reorganization
* Update references
* Put back test data
* Move conftest
* More fixes
* Move test data to test fixtures
* Update path
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Address review comments and clean
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Start writing BERT-Japanese doc
* Fix typo, Update toctree
* Modify model file to use comment for document, Add examples
* Clean bert_japanese by make style
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Split a big code block into two
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Add prefix >>> to all lines in code blocks
* Clean bert_japanese by make fixup
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* First draft of deit
* More improvements
* Remove DeiTTokenizerFast from init
* Conversion script works
* Add DeiT to ViT conversion script
* Add tests, add head model, add support for deit in vit conversion script
* Update model checkpoint names
* Update image_mean and image_std, set resample to bicubic
* Improve docs
* Docs improvements
* Add DeiTForImageClassificationWithTeacher to init
* Address comments by @sgugger
* Improve feature extractors
* Make fix-copies
* Minor fixes
* Address comments by @patil-suraj
* All models uploaded
* Fix tests
* Remove labels argument from DeiTForImageClassificationWithTeacher
* Fix-copies, style and quality
* Fix tests
* Fix typo
* Multiple docs improvements
* More docs fixes
* Add a special tokenizer for CPM model
* make style
* fix
* Add docs
* styles
* cpm doc
* fix ci
* fix the overview
* add test
* make style
* typo
* Custom tokenizer flag
* Add REAMDE.md
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
* AutoFeatureExtractor
* Init and first tests
* Tests
* Damn you gitignore
* Quality
* Defensive test for when not all backends are here
* Use pattern for Speech2Text models
* 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>
* 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>
* 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>
* 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>
* 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>
* 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
* 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
