* First pass
* Make conversion script work
* Improve conversion script
* Fix bug, conversion script working
* Improve conversion script, implement BEiTFeatureExtractor
* Make conversion script work based on URL
* Improve conversion script
* Add tests, add documentation
* Fix bug in conversion script
* Fix another bug
* Add support for converting masked image modeling model
* Add support for converting masked image modeling
* Fix bug
* Add print statement for debugging
* Fix another bug
* Make conversion script finally work for masked image modeling models
* Move id2label for datasets to JSON files on the hub
* Make sure id's are read in as integers
* Add integration tests
* Make style & quality
* Fix test, add BEiT to README
* Apply suggestions from @sgugger's review
* Apply suggestions from code review
* Make quality
* Replace nielsr by microsoft in tests, add docs
* Rename BEiT to Beit
* Minor fix
* Fix docs of BeitForMaskedImageModeling
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* [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>
* 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>
* Make quality scripts work when one backend is missing.
* Check env variable is properly set
* Add default
* With print statements
* Fix typo
* Set env variable
* Remove debug code
* 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>
* 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>
* Main init work
* Add version
* Change from absolute to relative imports
* Fix imports
* One more typo
* More typos
* Styling
* Make quality script pass
* Add necessary replace in template
* Fix typos
* Spaces are ignored in replace for some reason
* Forgot one models.
* Fixes for import
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>
* Add documentation
* Styling
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>
* 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
* 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
* 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
* 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>
