* first draft adding Flax-t5-encoder and Flax-mt5-encoder
* imports
* after make fixup
* flax t5 encoder test
* black on test
* make fix-copies
* clean
* all_model_classes -> tuple
* clean test
* is_encoder_decoder=False in t5-enc tester
* remove file docstring before FlaxT5Encoder
* black
* isort
* commit suggestions on src/transformers/models/t5/modeling_flax_t5.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* commit suggestions on src/transformers/models/t5/modeling_flax_t5.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* remove _get_encoder_module
* self.decoder_seq_length -> self.encoder_seq_length as t5-enc does not have decoder
* bugfix - self.module_class is class itself, not instance;
* docs for mt5 and t5
* call -> __call__ in t5 doc
* FlaxMT5EncoderModel to TYPE_HINT
* run doc-builder to allow change the files
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* chore: initial commit
Copied the torch implementation of regnets and porting the code to tf step by step. Also introduced an output layer which was needed for regnets.
* chore: porting the rest of the modules to tensorflow
did not change the documentation yet, yet to try the playground on the model
* Fix initilizations (#1)
* fix: code structure in few cases.
* fix: code structure to align tf models.
* fix: layer naming, bn layer still remains.
* chore: change default epsilon and momentum in bn.
* chore: styling nits.
* fix: cross-loading bn params.
* fix: regnet tf model, integration passing.
* add: tests for TF regnet.
* fix: code quality related issues.
* chore: added rest of the files.
* minor additions..
* fix: repo consistency.
* fix: regnet tf tests.
* chore: reorganize dummy_tf_objects for regnet.
* chore: remove checkpoint var.
* chore: remov unnecessary files.
* chore: run make style.
* Update docs/source/en/model_doc/regnet.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* chore: PR feedback I.
* fix: pt test. thanks to @ydshieh.
* New adaptive pooler (#3)
* feat: new adaptive pooler
Co-authored-by: @Rocketknight1
* chore: remove image_size argument.
Co-authored-by: matt <rocketknight1@gmail.com>
Co-authored-by: matt <rocketknight1@gmail.com>
* Empty-Commit
* chore: remove image_size comment.
* chore: remove playground_tf.py
* chore: minor changes related to spacing.
* chore: make style.
* Update src/transformers/models/regnet/modeling_tf_regnet.py
Co-authored-by: amyeroberts <aeroberts4444@gmail.com>
* Update src/transformers/models/regnet/modeling_tf_regnet.py
Co-authored-by: amyeroberts <aeroberts4444@gmail.com>
* chore: refactored __init__.
* chore: copied from -> taken from./g
* adaptive pool -> global avg pool, channel check.
* chore: move channel check to stem.
* pr comments - minor refactor and add regnets to doc tests.
* Update src/transformers/models/regnet/modeling_tf_regnet.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* minor fix in the xlayer.
* Empty-Commit
* chore: removed from_pt=True.
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: matt <rocketknight1@gmail.com>
Co-authored-by: amyeroberts <aeroberts4444@gmail.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Fixing a regression with `return_all_scores` introduced in #17606
- The legacy test actually tested `return_all_scores=False` (the actual
default) instead of `return_all_scores=True` (the actual weird case).
This commit adds the correct legacy test and fixes it.
Tmp legacy tests.
Actually fix the regression (also contains lists)
Less diffed code.
* Add a TF in-graph tokenizer for BERT
* Add from_pretrained
* Add proper truncation, option handling to match other tokenizers
* Add proper imports and guards
* Add test, fix all the bugs exposed by said test
* Fix truncation of paired texts in graph mode, more test updates
* Small fixes, add a (very careful) test for savedmodel
* Add tensorflow-text dependency, make fixup
* Update documentation
* Update documentation
* make fixup
* Slight changes to tests
* Add some docstring examples
* Update tests
* Update tests and add proper lowercasing/normalization
* make fixup
* Add docstring for padding!
* Mark slow tests
* make fixup
* Fall back to BertTokenizerFast if BertTokenizer is unavailable
* Fall back to BertTokenizerFast if BertTokenizer is unavailable
* make fixup
* Properly handle tensorflow-text dummies
* Add CodeGen model
* Add missing key and switch order of super()
* Fix torch.ones init with uint8 instead of bool
* Address comments: copy statements and doc
* update tests
* remove old model parallel
* fix batch gen tests
* fix batch gen test
* update test_gpt2_sample_max_time
* fix codgen test and revert gpt2 test change
* Fix incorrect tie_word_embedding value, typo, URL
* Fix model order in README and styling
* Reorder model list alphabetically
* Set tie_word_embedding to False by default
* Apply suggestions from code review
* Better attn mask name & remove attn masked_bias
* add tokenizer for codegen
* quality
* doc tokenizer
* fix-copies
* add CodeGenTokenizer in converter
* make truncation optional
* add test for truncation
* add copyright
* fix-copies
* fix fast tokenizer decode
* Update src/transformers/models/codegen/tokenization_codegen.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* increase vocab_size in tests
Co-authored-by: patil-suraj <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Fix tests that broke when models used batchnorm
* Initializing the model twice does not actually...
...give you the same weights each time.
I am good at machine learning.
* Fix speed regression
* few fixes:
- hardcode tokenizer padding side
- remove unused args
* few fixes:
- added new attribute on TokenizerTesterMixin
- added new slow test
- remove unused arg on tokenizer class
* make style
* Update src/transformers/models/bloom/tokenization_bloom_fast.py
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>
* make quality
* apply changes
- remove new attribute
- redefine test on the class
* add comments
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>
- Fix `top_k_top_p_filtering` not passing `filter_value` to
`TopPLogitsWarper` causing any top-p filtered logits to be -inf
instead of specified value
- Add corresponding test
* Add final_layer_norm to OPT model
* Add JAX and TF version
* Fix Keras name
* Woops
* Allow for non breaking change
* Apply suggestions from code review
* add tests
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* rename to check_pt_flax_outputs
* update check_pt_flax_outputs
* use 5e-5 for BigBird PT/Flax test
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Prepare CI for v0.8.0
* pin hfh (revert before merge)
* Revert "pin hfh (revert before merge)"
This reverts commit a0103140e1.
* Test rc3
* Test latest rc
* Unpin to the RC
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>
* Fix docstrings and variable names
* Rename x to something better
* Improve messages
* Fix docstrings and add test for greyscale images
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
* Use torch.finfo(self.dtype).min
* for GPTNeoX
* for Albert
* For Splinter
* Update src/transformers/models/data2vec/modeling_data2vec_audio.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix -inf used in Bart-like models
* Fix a few remaining -inf
* more fix
* clean up
* For CLIP
* For FSMT
* clean up
* fix test
* Add dtype argument and use it for LayoutLMv3
* update FlaxLongT5Attention
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add new bloom classes
* (feat) add bloom classification tests; make style
* style: change import in test
* add some typehints to bloom classes
* merge main into branch
* fix: input checking in bloom seq classification
* fix tests
* change model class tests
* fix few tests
- more tests should pass
- one test left
* make token classifier return hidden states
* style: make BLOOM typehints consistent
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
* Initial commit
* Make some fixes
* Make PT model full forward pass
* Drop TF & Flax implementation, fix copies etc
* Add Flax model and update some corresponding stuff
* Drop some TF things
* Update config and flax local attn
* Add encoder_attention_type to config
* .
* Update docs
* Do some cleansing
* Fix some issues -> make style; add some docs
* Fix position_bias + mask addition + Update tests
* Fix repo consistency
* Fix model consistency by removing flax operation over attn_mask
* [WIP] Add PT TGlobal LongT5
* .
* [WIP] Add flax tglobal model
* [WIP] Update flax model to use the right attention type in the encoder
* Fix flax tglobal model forward pass
* Make the use of global_relative_attention_bias
* Add test suites for TGlobal model
* Fix minor bugs, clean code
* Fix pt-flax equivalence though not convinced with correctness
* Fix LocalAttn implementation to match the original impl. + update READMEs
* Few updates
* Update: [Flax] improve large model init and loading #16148
* Add ckpt conversion script accoring to #16853 + handle torch device placement
* Minor updates to conversion script.
* Typo: AutoModelForSeq2SeqLM -> FlaxAutoModelForSeq2SeqLM
* gpu support + dtype fix
* Apply some 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>
* * Remove (de)parallelize stuff
* Edit shape comments
* Update README.md
* make fix-copies
* Remove caching logic for local & tglobal attention
* Apply another batch of suggestions from code review
* Add missing checkpoints
* Format converting scripts
* Drop (de)parallelize links from longT5 mdx
* Fix converting script + revert config file change
* Revert "Remove caching logic for local & tglobal attention"
This reverts commit 2a619828f6ddc3e65bd9bb1725a12b77fa883a46.
* Stash caching logic in Flax model
* Make side relative bias used always
* Drop caching logic in PT model
* Return side bias as it was
* Drop all remaining model parallel logic
* Remove clamp statements
* Move test files to the proper place
* Update docs with new version of hf-doc-builder
* Fix test imports
* Make some minor improvements
* Add missing checkpoints to docs
* Make TGlobal model compatible with torch.onnx.export
* Replace some np.ndarray with jnp.ndarray
* Fix TGlobal for ONNX conversion + update docs
* fix _make_global_fixed_block_ids and masked neg value
* update flax model
* style and quality
* fix imports
* remove load_tf_weights_in_longt5 from init and fix copies
* add slow test for TGlobal model
* typo fix
* Drop obsolete is_parallelizable and one warning
* Update __init__ files to fix repo-consistency
* fix pipeline test
* Fix some device placements
* [wip]: Update tests -- need to generate summaries to update expected_summary
* Fix quality
* Update LongT5 model card
* Update (slow) summarization tests
* make style
* rename checkpoitns
* finish
* fix flax tests
Co-authored-by: phungvanduy <pvduy23@gmail.com>
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: patil-suraj <surajp815@gmail.com>
* Raise RepoNotFoundError in case of 401
* Include changes from revert-17646-skip_repo_not_found
* Add a comment
* 💄 Code quality
* 💚 Update `get_from_cache` test
* 💚 Code quality & skip failing test
When we're preparing the tensors for CPU for postprocessing, we need
to upgrade the `float16` to `float32` since CPUs don't have instructions
for `[b]float16`.
* Adding `top_k` and `sort` arguments to `text-classification` pipeline.
- Deprecate `return_all_scores` as `top_k` is more uniform with other
pipelines, and a superset of what `return_all_scores` can do.
BC is maintained though.
`return_all_scores=True` -> `top_k=None`
`return_all_scores=False` -> `top_k=1`
- Using `top_k` will imply sorting the results, but using no argument
will keep the results unsorted for backward compatibility.
* Remove `sort`.
* Fixing the test.
* Remove bad doc.
* Use shape_list to safely get shapes
* Add relevant test
* Tidy and add metrics
* Resolve dynamic shaping issues and move test
* Tidy up and all samples in batch
* Formatting
* adding template
* update model
* model update
* update conf for debug model
* update conversion
* update conversion script
* update conversion script
* fix missing keys check
* add tests to test the tokenizer in the local machine
* Change variable name
* add tests on xnli dataset
* add more description
* add descriptions + clearer code
* clearer code
* adding new tests + skipping few tests because of env problems
* change comment
* add dtype on the configuration
* add test embeddings
* add hardcoded test
* fix dtype issue
* adding torch.float16 to config
* adding more metrics (min, max, mean)
* add sum
* now the test passes with almost equal
* add files for conversion - test passes on cpu gpu
* add final changes
* cleaning code
* add new args in the docstring
* fix one liner function
* remove macros
* remove forward attention
* clean up init funtion
* add comments on the issue
* rm scale mask softmax
* do make style
* fix dtype in init
* fixing for loop on att probs
* fix style with black
* fix style + doc error
* fix and debug CI errors (docs + style)
* some updates
- change new operations
- finally add scaled softmax
- added new args in the config
* make use cache working
* add changes
- save sharded models
- final changes on the modeling script
* add changes
- comment on alibi
- add TODO on seq length
* test commit
- added a text to test the commit
Co-authored-by: thomasw21 <24695242+thomasw21@users.noreply.github.com>
* final changes
- attention mask change
- generation works on BS176b
Co-authored-by: thomasw21 <24695242+thomasw21@users.noreply.github.com>
* changes - model + conversion
* move to correct dir
* put ,
* fex fixes
* fix tokenizer autodoc
* fix minor CI issues
* fix minor CI issues
* fix minor CI issues
* fix style issue
* fix minor import issues
* fix few issues
* remove def main on the test
* add require torch
* replace decorator with 'with'
* fix style
* change to bloom
* add quick fix tokenizer
* fix tokenizer file
* fix tokenizer
- merge tests
- small fixes
* fix import issue
* add bloom to readme
* fix consistency
* Update docs/source/en/model_doc/bloom.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Apply suggestions from code review
fix comment issues on file headers
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* fix doc issue
* small fix - modeling test
* some changes
- refactor some code
- taking into account reviews
- more tests should pass
- removed pruning tests
* remove useless division
* more tests should pass
* more tests should pass
* more tests should pass
* let's try this one
-add alibi offset
- remove all permutes to make the grad operations work
- finger crossed
* refactor
- refactor code
- style changes
- add new threshold for test
* major changes
- change BLOOM to Bloom
- add quick doc on bloom.mdx
- move embeddings test on modeling test
* modify readme
* small fixes
* small fix
- better threshold for a test
* remove old test file from fetcher
* fix small typo
* major change
- change BloomLMHead to BloomForCausalLM
* remove onnx config
* major changes
- refactor the code
- remove asserts
- change tol for test
* make style
* small change
* adding a slow test + commenting old ones for now
* make style
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* make style
* fix duplicates
* cleaning comments on config
* clean a bit conversion file
* refacor a bit modeling file
* refactor tokenizer file
* fix tokenization test issue
* fix tokenization issue #2
* fix tokenization issue second try
* fix test issue
* make style + add suggestions
* change test fetcher
* try this one
- slow tests should pass
- finger crossed
* possible final changes
* make style
* try fix padding side issue
* fix side
* fix padding issue
* fix ko-readme
* fix config auto
* cleaning modeling file
* keep bloom in caps in ko
* update config docs
* remove pretraining_pp
* remove model parallel
* update config
- add correct config files
* fix duplicates
* fix fetcher
* fix refactor issue
- remove divide function
* try to remove alibi
* small fixes
- fix alibi
- remove seq length
- refactor a bit the code
* put correct values
- fix bos and eos token ids
* fix attention mask loop
Co-authored-by: thomasw21 <24695242+thomasw21@users.noreply.github.com>
* small fixes:
- remove skip bias add
* small fixes
- fix typo in readme
- fix typos in config
* small changes
- remove a test
- add reconstruction test
- change config
* small changes
- change Scaled Softmax to BloomScaledSoftmax
* small fixes
- fix alibi dtype
* major changes
- removing explicit dtype when loading modules
- fixing test args (torch_dtype=auto)
- add dosctring
* fix readmes
* major changes
- now bloom supports alibi shifting
- refactor a bit the code
- better test tolerance now
* refactor a bit
* refactor a bit
* put correct name on test
* change docstring
* small changes
- fix docstring modeling
- fix test tolerance
* fix small nit
- take dtype from tensors in the conversion script
* minor fix
- fix mdx issue
* minor fix
- change config docstring
* forward contrib credits from PR14084
* Apply suggestions from code review
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* apply modifications
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* resolve softmax upcast
* Apply suggestions from code review
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* Update src/transformers/models/bloom/modeling_bloom.py
Co-authored-by: Niklas Muennighoff <n.muennighoff@gmail.com>
* final changes modeling
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* Merge commit 'd156898f3b9b2c990e5963f5030a7143d57921a2'
* merge commit
* Apply suggestions from code review
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* apply suggestions
Apply suggestions from Stas comments
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* Fix gradient checkpointing
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* add slow but exact
* add accelerate compatibility
Co-authored-by: Nicolas Patry <Narsil@users.noreply.github.com>
* forward contrib credits
Co-authored-by: thomasw21 <thomasw21@users.noreply.github.com>
Co-authored-by: sgugger <sgugger@users.noreply.github.com>
Co-authored-by: patrickvonplaten <patrickvonplaten@users.noreply.github.com>
Co-authored-by: Niklas Muennighoff <n.muennighoff@gmail.com>
Co-authored-by: LysandreJik <LysandreJik@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix torch device on tests
* make style
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix nits
Co-authored-by: patrickvonplaten<patrickvonplaten@users.noreply.github.com>
* remove final nits
* fix doc
- add more details on the doc
- add links to checkpoints
* Update src/transformers/__init__.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/bloom/modeling_bloom.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* apply suggestions
Co-authored-by: sgugger <sgugger@users.noreply.github.com>
* put test torchscript to false
* Update src/transformers/models/bloom/modeling_bloom.py
Co-authored-by: justheuristic <justheuristic@gmail.com>
* fix alibi
- create alibi only once
* add small doc
* make quality
* replace torch.nn
* remove token type emb
* fix fused op + output bias
* add fused op
- now can control fused operation from config
* remove fused op
* make quality
* small changes
- remove unsed args on config
- removed bias gelu file
- make the model torchscriptable
- add torchscript slow tests
* Update src/transformers/models/bloom/modeling_bloom.py
* fix slow
* make style
* add accelerate support
* add bloom to deepspeed tests
* minor changes
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* minor change
* slow tests pass
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update docs/source/en/model_doc/bloom.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* minor changes:
- change docstring
- add link to paper
Co-authored-by: Thomwolf <thomwolf@gmail.com>
Co-authored-by: Thomas Wolf <thomas@huggingface.co>
Co-authored-by: thomasw21 <24695242+thomasw21@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: sIncerass <sheng.s@berkeley.edu>
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Niklas Muennighoff <n.muennighoff@gmail.com>
Co-authored-by: Nicolas Patry <Narsil@users.noreply.github.com>
Co-authored-by: thomasw21 <thomasw21@users.noreply.github.com>
Co-authored-by: sgugger <sgugger@users.noreply.github.com>
Co-authored-by: patrickvonplaten <patrickvonplaten@users.noreply.github.com>
Co-authored-by: LysandreJik <LysandreJik@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: justheuristic <justheuristic@gmail.com>
Co-authored-by: Stas Bekman <stas@stason.org>
* feat: initial implementation of data2vec segmentation model in TF.
* chore: minor corrections to make the segmenter work.
* chore: removed unncessary files.
* chore: add tests and other modifications.
* fix: loss computation for segmentation.
* chore: remove unused variable.
* chore: formatting.
* added a dummy adaptive pooling layer.
* removed unnecessary file.
* potentially add identifiers to layer names.
* fix: layer naming.
* chore: removed unnecessary print.
* Skipping unneeded test
* chore: add logging to debug tolerance.
* fix: segmentation tests for tfdata2vecvision
* chore: make style.
* fix: layer names, assertion to be resolved.
* Bumping test tolerance a bit
* chore: bump the tol in PT test.
Co-authored-by: matt <rocketknight1@gmail.com>
* added cbs to notebooks, made copy-paste error fix in generation_utils
* initial push for mctc model
* mctc feature extractor done
* added processor, tokenizer and their tests for MCTC. Have added an MCTC modeling test, adjusting model code accordingly.
* added processor, tokenizer and their tests for MCTC. Have added an MCTC modeling test, adjusting model code accordingly.
* passing attention, now struggling to figure out how attention masks make sense here
* works when excluding attention masks. ask later how one would integrate attention maskshere
* bizarre configuration error (model prefix comes first in config dict json and messes up the order)
* all passing but bizzarre config dict ordering issue when to_dict
* passing all major tests
* feature extraction, processor, tokenizer added & tests passing
* style & consistency & other logistical fixes
* copy paste fix
* model after feature extraction working
* commiting final feature extraction results; need to fix normalization
* feature extraction passing tests; probably should add tests on the specific flashlight-copied functions?
* delete print ; format code a bit
* fixing tests
* passing major tests
* fixing styles
* completed tokenization test with real example; not sure if these values are entirely correct.
* last test fixes from local
* reverting accidentally included custom setup configs
* remove load tf weights; fix config error
* testing couldnt import featureextractor
* fix docs
* fix docs
* resolving comments
* style fixes
* style fixes
* Update to MCTCConv1dSubSampler
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* relposemb fixes
* conv1d name issue; expecting config fail with paraentheses
* fix config issue
* fix config issue
* fix config issue
* change everything to MCTCT
* fixing naming change errors
* archive list
* copyrights and docs
* copyrights and docs
* copyrights and docs
* merge resolution
* move tests, fix to changed optionaldependency structure
* test directories changed
* fixing tests
* how to avoid tf tests?
* how to avoid tf tests?
* tests passing locally
* allow mctctprocessor imported any env
* allow mctctprocessor imported any env
* fixed second round of feedback, need to fix docs
* doc changes not being applied
* all fixed
* style fix
* feedback fixes
* fix copies and feature extraction style fix
* Update tests/models/visual_bert/test_modeling_visual_bert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* copy paste huggingface:main visual bert
* added eof newline to visual bert; all tests are passing otherwise
* fix slow tests by adding attention mask
* change model id to speechbrain
* make fix-copies
* fix readme unwanted deletes
* fixing readmes, make fix-copies
* consistent M-CTC-T naming
* Update src/transformers/models/mctct/__init__.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* all fixed but variable naming
* adjust double quotes
* fixed variable names
* copyright and mr quilter
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* correct slow tests
* make fix-copies
* Update src/transformers/models/mctct/configuration_mctct.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/mctct/configuration_mctct.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* m-ctc-t not mctct
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Add method to call to_tf_dataset() with column inference
* Add test for dataset creation
* Add a default arg for data collator
* Fix test
* Fix call with non-dev version of datasets
* Test correct column removal too
* make fixup
* More tests to make sure we remove unwanted columns
* Fix test to avoid predicting on unbuilt models
* Fix test to avoid predicting on unbuilt models
* Fix test to remove unwanted head mask columns from inputs
* Stop pushing your debug breakpoints to the main repo of the $2bn company you work for
* Skip the test in convnext because no grouped conv support
* Drop bools from the dataset dict
* Make style
* Skip the training test for models whose input dicts don't give us labels
* Skip transformerXL in the test because it doesn't return a simple loss
* Skip TFTapas because of some odd NaN losses
* make style
* make fixup
* Add docstring
* fixup
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Remove breakpoint from tests
* Fix assert, add requires_backends
* Protect tokenizer import with if TYPE_CHECKING
* make fixup
* Add noqa, more fixup
* More rearranging for ~* aesthetics *~
* Adding defaults for shuffle and batch_size to match to_tf_dataset()
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Add gated-silu to t5 architecture to support UL2
* Fix error message
* formatting
* formatting again
* refactor
* fix classnames in _init_weights
* remove is_gated
* add test
* fix test
* Try without the test?
* Add back the test.
* Improve error message.
Co-authored-by: Daniel Hesslow <daniel@lighton.ai>
* add a test for a word only input
* make LukeForMaskedLM work without entity inputs
* update test
* add LukeForMaskedLM to MODEL_FOR_MASKED_LM_MAPPING_NAMES
* restore pyproject.toml
* empty line at the end of pyproject.toml
* initial commit
* add init file
* update globakl init
* update index and dummy objects
* style
* update modelling auto
* fix initi typo in src/transformers
* fix typo in modeling tf auto, opt was in wrong mapping name
* fixed a slow test : saved_model
* style
* fix positionnal embedding if no position id is provided
* update tf test
* update test flax requirements
* fixed serialization
* update
* update tf name to allow smooth convertion
* update flax tests
* style
* fix test typo
* fix tf typo test
* add xla for generate support in causal LM
* fixed bug
* cleaned tf tests
* style
* removed from PT for slow tests
* fix typp
* opt test as slow
* trying to fix GPT2 undefined
* correct documentation and add to test doc
* update tf doc
* fix doc
* fake commit
* Apply suggestions from code review
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* update test based on review
* merged main layer for functionning test
* fixup + quality
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* update long comment
* make fix copies
Co-authored-by: Arthur <arthur@huggingface.co>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* [Json dump] Make json prettier
* correct more tokenizeirs
* more patterns
* add aggressive test
* the aggressive test was actually useful :-)
* more tests
* Apply suggestions from code review
* Add onnx configuration for xlm
* Add supported features for xlm
* Add xlm to models exportable with onnx
* Add xlm architecture to test file
* Modify docs
* Make code quality fixes
* Support for Bart and LayoutLM, and partial support for XLNet
* Support for mbart
* A lot of new models supported
* Support for other models
* LayoutLM fix
* Use strings instead of classes
* Enablign `imageGPT` auto feature extractor.
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Small updates.
* Update after rebase to use `input_ids` instead of `pixel_values`.
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Make forward pass work
* More improvements
* Remove unused imports
* Remove timm dependency
* Improve loss calculation of token classifier
* Fix most tests
* Add docs
* Add model integration test
* Make all tests pass
* Add LayoutLMv3FeatureExtractor
* Improve integration test + make fixup
* Add example script
* Fix style
* Add LayoutLMv3Processor
* Fix style
* Add option to add visual labels
* Make more tokenizer tests pass
* Fix more tests
* Make more tests pass
* Fix bug and improve docs
* Fix import of processors
* Improve docstrings
* Fix toctree and improve docs
* Fix auto tokenizer
* Move tests to model folder
* Move tests to model folder
* change default behavior add_prefix_space
* add prefix space for fast
* add_prefix_spcae set to True for Fast
* no space before `unique_no_split` token
* add test to hightligh special treatment of added tokens
* fix `test_batch_encode_dynamic_overflowing` by building a long enough example
* fix `test_full_tokenizer` with add_prefix_token
* Fix tokenizer integration test
* Make the code more readable
* Add tests for LayoutLMv3Processor
* Fix style
* Add model to README and update init
* Apply suggestions from code review
* Replace asserts by value errors
* Add suggestion by @ducviet00
* Add model to doc tests
* Simplify script
* Improve README
* a step ahead to fix
* Update pair_input_test
* Make all tokenizer tests pass - phew
* Make style
* Add LayoutLMv3 to CI job
* Fix auto mapping
* Fix CI job name
* Make all processor tests pass
* Make tests of LayoutLMv2 and LayoutXLM consistent
* Add copied from statements to fast tokenizer
* Add copied from statements to slow tokenizer
* Remove add_visual_labels attribute
* Fix tests
* Add link to notebooks
* Improve docs of LayoutLMv3Processor
* Fix reference to section
Co-authored-by: SaulLu <lucilesaul.com@gmail.com>
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
* Initial work
* More or less finished with first draft
* Update src/transformers/modeling_utils.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* Update src/transformers/modeling_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Fix randomly initialized weights
* Update src/transformers/modeling_utils.py
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
* Address review comments
* Rename DeepSpeed folder to temporarily fix the test issue?
* Revert to try if Accelerate fix works
* Use latest Accelerate release
* Quality and fixes
* Style
* Quality
* Add doc
* Test + fix
* More blocks
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
* Fix torch.jit.script and pickling issues
* Fix get_attr issues
* Fix import in function
* Fix GPT-J and T5 tracing for torch=1.11
* Gate graph surgery on torch version
* Modeling minor changes to enable TorchScripting
* Model serialization / deserialization test
* Remove _assert_is_none users
* [BC] Fixing usage of text pairs
The BC is actually preventing users from misusing the pipeline since
users could have been willing to send text pairs and the pipeline would
instead understand the thing as a batch returning bogus results.
The correct usage of text pairs is preserved in this PR even when that
makes the code clunky.
Adds support for {"text":..,, "text_pair": ...} inputs for both dataset
iteration and more explicit usage to pairs.
* Updating the doc.
* Update src/transformers/pipelines/text_classification.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/pipelines/text_classification.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update tests/pipelines/test_pipelines_text_classification.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* quality.
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Initial commit
* Better label renaming
* Remove breakpoint before pushing (this is your job)
* Test a lot more in the Keras fit() test
* make fixup
* Clarify the case where we flatten y dicts into tensors
* Clarify the case where we flatten y dicts into tensors
* Extract label name remapping to a method
* Automatically sort auto mappings
* Better class extraction
* Some auto class magic
* Adapt test and underlying behavior
* Remove re-used config
* Quality
* Add test to ensure models can take int64 inputs
* is_integer is an attribute, not a method
* Fix test when some inputs aren't tensors
* Add casts to blenderbot and blenderbot-small
* Add casts to the other failing models
* First version - OPT model
* Final changes
- putting use cache to False
* few changes
- remove commented block
* few changes
- remove unecessary files
* fix style issues
* few changes
- remove a test file
- added the logits test
* Update src/transformers/models/auto/tokenization_auto.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add gen tests
* few changes
- rm mask filling example on docstring
* few changes
- remove useless args
* some changes
- more tests should pass now
- needs to clean more
- documentation still needs to be done
* fix code quality
* major changes
- change attention architecture to BART-like
- modify some tests
- style fix
* rm useless classes
- remove opt for:
- QA
- cond generation
- seq classif
* Removed autodoc calls to non-existant classes
TOkenizers are not implemented
* Update src/transformers/__init__.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/__init__.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/auto/modeling_tf_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Replaced OPTTokeniser with GPT2 tokenizer
* added GPT2Tokenizer.from_pretrained("patrickvonplaten/opt_gpt2_tokenizer")
* Removed OPTTokenizer
* make style
* Make style replaces
``` ...).unsqueeze(```
by
``` >>>).unsqueeze(```
* make repo consistency
* Removed PretrainedOPTModel
* fix opt.mdx removed other heads
* fix init, removed 3 heads
* removed heads
* finished cleaning head
* removed seauence classif and question answering
* removed unused imports
* removed useless dummy object for QA, SC and CG
* removed tests for removed useless dummy object for QA, SC and CG
* Removed head_mask using encoder layers which don't exist
* fixed test
* fix line
* added OPT to toctree
* Updated model path with pushed weigths
* fix model path
* fixed code quality
* fixed embeddings and generation tests
* update paths
* clean comments
* removed OPTClassificationHead for sentence classification
* renamed hidden layer
* renamed num layers to standard num_hidden_layers
* num_attention_heads fix
* changes for 125m
* add first version for 125m
* add first version - flax
* add new version
* causal LM output
* replace output type with BaseModelOutputWithPastAndCrossAttentions
* revert working config from 150m to 350m
* clean
* removed decoder input ids
* fixed embed dim
* more embed_dim issues
* make style + removed enc_dec test
* update falx model
* removed troublesome copy
* added is_encoder_decoder=False to config
* added set_input emb fuinction to model class
* requires torch on embed test
* use head mask instead of decoder head mask input param solves a test
* 8 test remaining, update
* Updated create_and_check_decoder_model_past_large_inputs
* Make style
* update op tokenizer with condition
* make style
* See if I can push
* some clean up
* remove linear head hack
* save intermediate
* save correct attention
* add copied from from bart
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix part of the reviewss
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* same changes in naming / conversion
* correct mask
* more fixes
* delete FlaxOPT and TfOPT
* clean traces of Flax and Tf
* fix mask
* fixed positionnal embedding length when past key value is provoded
* get 125m, 6.7b to work
* Added do_layer_norm
* solved mismatch in load dictionnary
* clean up preapre opt input dict
* fixed past key value as bool
* fix previus
* fixed return dict False tuple issue
* All tests are passing
* Make style
* Ignore OPTDecoder non tested
* make fix-copies
* make repo consistency
* small fix
* removed uselss @torch.no_grad decorator
* make styl;e
* fix previous opt test
* style
* make style
* added opt documentation
* update OPT_PRETRAINED_MODEL_ARCHIVE_LIST
* up
* more fixes
* model & config work
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* added comment on padding hack (+2)
* cleaup
* review update
* docstring for missing arg
* Update docs/source/en/model_doc/opt.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update docs/source/en/model_doc/opt.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update docs/source/en/model_doc/opt.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/opt/__init__.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* update pretrained map
* update path and tests
* make style
* styling
* make consistency
* add gpt2 tok new
* more tok fixes
* Update src/transformers/models/auto/tokenization_auto.py
* Update docs/source/en/model_doc/opt.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update docs/source/en/model_doc/opt.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update docs/source/en/model_doc/opt.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update tests/models/opt/test_modeling_opt.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update based on reviews
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* make style
* make tokenizer auto tests pass
* apply Lysandre suggestion
* finish tests
* add some good tokenizer tests
* improve docs slighly
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: ArthurZucker <arthur.zucker@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* [WIP] Add FLAVA model
This PR aims to add [FLAVA](ihttps://arxiv.org/abs/2112.04482) model to the transformers repo.
Following checklist delineates the list of things to be done for this PR
to be complete:
[x] Flava init
[x] Flava base models
[x] Flava layers
[x] Flava Configs
[x] Flava encoders
[x] Flava pretraining models
[ ] Flava classification/retrieval models (To be added in a separate PR)
[x] Documentation updates
[x] Imports updates
[x] Argstring updates
[x] Flava pretrained checkpoints
[x] Flava tests
[x] Flava processors
[x] Sanity check
[x] Lint
* unhardcode pretrained model path, make it a class var
* add tests for mobilebert tokenizer
* allow tempfiles for vocab & merge similarity test to autodelete
* add explanatory comments
* remove unused imports, let make style do its.. thing
* remove inheritance and use BERT tok tests for MobileBERT
* Update tests/mobilebert/test_tokenization_mobilebert.py
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>
* amend class names, remove unused import, add fix for mobilebert's hub pathname
* unhardcode pretrained model path, make it a class var
* add tests for mobilebert tokenizer
* allow tempfiles for vocab & merge similarity test to autodelete
* add explanatory comments
* remove unused imports, let make style do its.. thing
* remove inheritance and use BERT tok tests for MobileBERT
* Update tests/mobilebert/test_tokenization_mobilebert.py
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>
* amend class names, remove unused import, add fix for mobilebert's hub pathname
* amend paths for model tests being in models/ subdir of /tests
* explicitly rm test from prev path
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>
* add support for MLFLOW_FLATTEN_PARAMS
* ensure key is str
* fix style and update warning msg
* Empty commit to trigger CI
* fix bug in check_inits.py
* add unittest for flatten_dict utils
* fix 'NoneType' object is not callable on __del__
* add generic flatten_dict unittest to SPECIAL_MODULE_TO_TEST_MAP
* fix style
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
- Adds auto_batch_size finder
- Moves training loop to an inner training loop
* add get_overflowing_images function to ensure 1-to-1 mapping between samples and images in LayoutLMv2Processor
* make style
* add test for overflowing_tokens, change assert to ValueError, avoiding unrelated formatting changes
* change line length by passing --preview into black
* CLIP Serving
* Add type hints per code review
* Use black, flake8, and isort
* Update src/transformers/models/clip/modeling_tf_clip.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Rollback serving_output and add TODO
* Remove irrelevant portions of failing tests
* Revert "Rollback serving_output and add TODO"
This reverts commit a4abfa6ba3b7875a13538dbc2ddc4eb17dfcca8d.
* Rollback to original test/serving_output
* Fix unused var
* Apply suggestions from code review
* Update formatting with black
* Fix style again from rebase
* Update tests/models/clip/test_modeling_tf_clip.py
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Sean Moriarity <sean.l.moriarity.mil@army.mil>
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
* [T5 Tokenizer] Model has no fixed position ids - there is no hardcoded max length
* [T5 Tokenizer] Model has no fixed position ids - there is no hardcoded max length
* correct t5 tokenizer
* correct t5 tokenizer
* fix test
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* finish
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* First draft
* Add YolosForObjectDetection
* Make forward pass work
* Add mid position embeddings
* Add interpolation of position encodings
* Add expected values
* Add YOLOS to tests
* Add integration test
* Support tiny model as well
* Support all models in conversion script
* Remove mid_pe_size attribute
* Make more tests pass
* Add model to README and fix config
* Add copied from statements
* Rename base_model_prefix to vit
* Add missing YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP
* Apply suggestions from code review
* Apply more suggestions from code review
* Convert remaining checkpoints
* Improve docstrings
* Add YolosFeatureExtractor
* Add feature extractor to docs
* Add corresponding tests
* Fix style
* Fix docs
* Apply suggestion from code review
* Fix bad rebase
* Fix some more bad rebase
* Fix missing character
* Improve docs and variable names
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
* Fix issue avoid-misusing-assert-true found at https://codereview.doctor
* fix tests
* fix tf
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* begin do_init
* add params_shape_tree
* raise error if params are accessed when do_init is False
* don't allow do_init=False when keys are missing
* make shape tree a property
* assign self._params at the end
* add test for do_init
* add do_init arg to all flax models
* fix param setting
* disbale do_init for composite models
* update test
* add do_init in FlaxBigBirdForMultipleChoice
* better names and errors
* improve test
* style
* add a warning when do_init=False
* remove extra if
* set params after _required_params
* add test for from_pretrained
* do_init => _do_init
* chage warning to info
* fix typo
* add params in init_weights
* add params to gpt neo init
* add params to init_weights
* update do_init test
* Trigger CI
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* update template
* trigger CI
* style
* style
* fix template
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Add passing encoder_outputs as tuple to existing test
* Add check for tuple
* Add check for tuple also for speech and vision
Co-authored-by: jsnfly <jsnfly@gmx.de>
* Improve code
* Fix bugs
* Fix another bug
* Clean up DTP as well
* Update DPT model outputs
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
* [trainer / deepspeed] fix hyperparameter_search
* require optuna
* style
* oops
* add dep in the right place
* create deepspeed-testing dep group
* Trigger CI
* Fix setters of *_token_id properties of SpecialTokensMixin
* Test setters of common tokens ids
* Move to a separate test checks of setters of tokens ids
* Add independent test for ByT5
* Add Canine test
* Test speech to text
* Change the chunk_iter function to handle
the subtle cases where the last chunk gets ignored since all the
data is in the `left_strided` data.
We need to remove the right striding on the previous item.
* Remove commented line.
* update proto sentencepiece model
* Revert "update proto sentencepiece model"
This reverts commit b07f671747.
* add check
* add test
* Revert "Revert "update proto sentencepiece model""
This reverts commit 46108257b8.
* test for log level
* test for log level 2
* warning at the warning level
* clean
* format
* add explanation in docstring
* Add TapexTokenizer
* Improve docstrings and provide option to provide answer
* Remove option for pretokenized inputs
* Add TAPEX to README
* Fix copies
* Remove option for pretokenized inputs
* Initial commit: add tapex fine-tuning examples on both table-based question answering and table-based fact verification.
* - Draft a README file for running the script and introducing some background.
- Remove unused code lines in tabfact script.
- Disable the deafult `pad_to_max_length` option which is memory-consuming.
* * Support `as_target_tokenizer` function for TapexTokenizer.
* Fix the do_lower_case behaviour of TapexTokenizer.
* Add unit tests for target scenarios and cased/uncased scenarios for both source and target.
* * Replace the label BartTokenizer with TapexTokenizer's as_target_tokenizer function.
* Fix typos in tapex example README.
* * fix the evaluation script - remove the property `task_name`
* * Make the label space more clear for tabfact tasks
* * Using a new fine-tuning script for tapex-base on tabfact.
* * Remove the lowercase code outside the tokenizer - we use the tokenizer to control whether do_lower_case
* Guarantee the hyper-parameter can be run without out-of-memory on 16GB card and report the new reproduced number on wikisql
* * Remove the default tokenizer_name option.
* Provide evaluation command.
* * Support for WikiTableQuestion dataset.
* Fix a typo in README.
* * Fix the datasets's key name in WikiTableQuestions
* Run make fixup and move test to folder
* Fix quality
* Apply suggestions from code review
* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* Apply suggestions from code review
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Apply some more suggestions from code review
* Improve docstrings
* Overwrite failing test
* Improve comment in example scripts
* Fix rebase
* Add TAPEX to Auto mapping
* Add TAPEX to auto config mappings
* Put TAPEX higher than BART in auto mapping
* Add TAPEX to doc tests
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>
Co-authored-by: SivilTaram <qianlxc@outlook.com>
Co-authored-by: Niels Rogge <nielsrogge@nielss-mbp.home>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
* Adding new train_step logic to make things less confusing for users
* DO NOT ASK WHY WE NEED THAT SUBCLASS
* Metrics now working, at least for single-output models with type annotations!
* Updates and TODOs for the new train_step
* Make fixup
* Temporary test workaround until T5 has types
* Temporary test workaround until T5 has types
* I think this actually works! Needs a lot of tests though
* MAke style/quality
* Revert changes to T5 tests
* Deleting the aforementioned unmentionable subclass
* Deleting the aforementioned unmentionable subclass
* Adding a Keras API test
* Style fixes
* Removing unneeded TODO and comments
* Update test_step too
* Stop trying to compute metrics with the dummy_loss, patch up test
* Make style
* make fixup
* Docstring cleanup
* make fixup
* make fixup
* Stop expanding 1D input tensors when using dummy loss
* Adjust T5 test given the new compile()
* make fixup
* Skipping test for convnext
* Removing old T5-specific Keras test now that we have a common one
* make fixup
* make fixup
* Only skip convnext test on CPU
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Avoiding TF import issues
* make fixup
* Update compile() to support TF 2.3
* Skipping model.fit() on template classes for now
* Skipping model.fit() on template class tests for now
* Replace ad-hoc solution with find_labels
* make fixup
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Add utility to find model labels
* Use it in the Trainer
* Update src/transformers/utils/generic.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* Quality
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* feature extractor accepts
* resolved conversations
* added examples in test for ADE20K
* num_classes -> num_labels
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* resolving conversations
* resolving conversations
* removed ADE
* CI
* minor changes in conversion script
* reduce_labels in feature extractor
* minor changes
* correct preprocess for instace segmentation maps
* minor changes
* minor changes
* CI
* debugging
* better padding
* going to update labels inside the model
* going to update labels inside the model
* minor changes
* tests
* removed changes in feature_extractor_utils
* conversation
* conversation
* example in feature extractor
* more docstring in modeling
* test
* make style
* doc
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* ported TFViTMAEIntermediate and TFViTMAEOutput.
* added TFViTMAEModel and TFViTMAEDecoder.
* feat: added a noise argument in the implementation for reproducibility.
* feat: vit mae models with an additional noise argument for reproducibility.
Co-authored-by: ariG23498 <aritra.born2fly@gmail.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Fix for test_mixed_precision
* Fix test_saved_model_creation by using shape_list instead of shape
* skit test_model_from_pretrained on GPU for now to avoid GPU OOM
* skip test_gptj_sample_max_time for now
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Created the Decision Transformer Modle
* updating tests, copy to other machine
* Added last hidden size to Decision Transformer modelling outputs
* Removed copy of original DT file
* made a temporary change to gpt2 to have it conform with the Decision Transformer version
* Updated tests
* Ignoring a file used to test the DT model
* added comments to config file
* added comments and argument descriptions to decision transformer file
* Updated doc
* Ran "make style"
* Remove old model imports
* Removed unused imports, cleaned up init file
* Update docs/source/model_doc/decision_transformer.mdx
added my username
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Reverted changes made to gpt2
* Removed datasets submodule
* Update the modeling outputs to include gpt2 attentions, hidden states and last hidden states
* Added support for return of hidden states, attentions and return dict of gpt2 model.
* Updated tests to include many of the ModelTesterMixin tests.
The following tests are skipped: test_generate_without_input_ids, test_pruning, test_resize_embeddings, test_head_masking, test_attention_outputs, test_hidden_states_output, test_inputs_embeds, test_model_common_attributes
* Added missing line to the end of gpt2 file
* Added an integration test for the Decision Transformer
Test performs and autoregressive evaluation for two time steps
* Set done and info to _ to fix failing test
* Updated integration test to be deterministic and check expected outputs
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Removed unnecessary config options
* Cleaned up commented code and old comments.
* Cleaned up commented code.
* Changed DecisionTransformer to Decision Transformer
* Added Decision Transformer to the main README file
* Added copy of GTP2 called DecisionTranformerGPT2Model
* isorted imports
* isorted imports
* Added model to non-English README files
* Ran make fix-copies and corrected some cases.
* Updated index file to include Decision Transformer
* Added gpt2 model as copy inside the Decision Transformer model file
* Added the unit test file to the list of TEST_FILES_WITH_NO_COMMON_TESTS
* Deleted redundant checkpoint files (I don't know how these got committed)
* Removed testing files. (These should have never been committed)
* Removed accidentally committed files
* Moved the Decision Transformer test to its own directory
* Add type hints for Pegasus (#16324)
* Funnel type hints (#16323)
* add pt funnel type hints
* add tf funnel type hints
* Add type hints for ProphetNet PyTorch (#16272)
* [GLPN] Improve docs (#16331)
* Add link to notebook
* Add link
* Fix bug
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
* Added type hints for Pytorch Marian calls (#16200)
* Added type hinting for forward functions in pytorch marian
* typo correction
* Removed type hints on functions from BART per Suraj Patil request
* fix import pb
* fix typo
* corrected tuple call
* ran black
* after fix-copies
Some optional tags on primitives were removed, past_key_values in MarianForCausalLM changed from Tuple of Tuple to List
* Fixing copies to roformer and pegasus
Co-authored-by: Clementine Fourrier <cfourrie@inria.fr>
Co-authored-by: matt <rocketknight1@gmail.com>
* Moved DecisionTransformOutput to modeling_decision_transformer
* Moved the example usage to research project and cleaned comments
* Made tests ignore the copy of gpt2 in Decision Transformer
* Added module output to modelling decision transformer
* removed copied gpt2 model from list of transformers models
* Updated tests and created __init__ file for new test location
* Update README.md
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/decision_transformer/configuration_decision_transformer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Removed unneeded summary type from config file
* Fixed copies
* Updated pretrained config map to refer to hopper-medium checkpoint
* done (#16340)
* Added Decision transformer to model docs
* Update src/transformers/models/decision_transformer/modeling_decision_transformer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/decision_transformer/modeling_decision_transformer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/decision_transformer/configuration_decision_transformer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Add type annotations for Rembert/Splinter and copies (#16338)
* undo black autoformat
* minor fix to rembert forward with default
* make fix-copies, make quality
* Adding types to template model
* Removing List from the template types
* Remove `Optional` from a couple of types that don't accept `None`
Co-authored-by: matt <rocketknight1@gmail.com>
* [Bug template] Shift responsibilities for long-range (#16344)
* Fix code repetition in serialization guide (#16346)
* Adopt framework-specific blocks for content (#16342)
* ✨ refactor code samples with framework-specific blocks
* ✨ update training.mdx
* 🖍 apply feedback
* Updates the default branch from master to main (#16326)
* Updates the default branch from master to main
* Links from `master` to `main`
* Typo
* Update examples/flax/README.md
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Updated model with custom docstring example
* Created the Decision Transformer Modle
* updating tests, copy to other machine
* Added last hidden size to Decision Transformer modelling outputs
* Removed copy of original DT file
* made a temporary change to gpt2 to have it conform with the Decision Transformer version
* Updated tests
* Ignoring a file used to test the DT model
* added comments to config file
* added comments and argument descriptions to decision transformer file
* Updated doc
* Ran "make style"
* Remove old model imports
* Removed unused imports, cleaned up init file
* Update docs/source/model_doc/decision_transformer.mdx
added my username
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Reverted changes made to gpt2
* Removed datasets submodule
* Update the modeling outputs to include gpt2 attentions, hidden states and last hidden states
* Added support for return of hidden states, attentions and return dict of gpt2 model.
* Updated tests to include many of the ModelTesterMixin tests.
The following tests are skipped: test_generate_without_input_ids, test_pruning, test_resize_embeddings, test_head_masking, test_attention_outputs, test_hidden_states_output, test_inputs_embeds, test_model_common_attributes
* Added missing line to the end of gpt2 file
* Added an integration test for the Decision Transformer
Test performs and autoregressive evaluation for two time steps
* Set done and info to _ to fix failing test
* Updated integration test to be deterministic and check expected outputs
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Removed unnecessary config options
* Cleaned up commented code and old comments.
* Cleaned up commented code.
* Changed DecisionTransformer to Decision Transformer
* Added Decision Transformer to the main README file
* Added copy of GTP2 called DecisionTranformerGPT2Model
* isorted imports
* isorted imports
* Added model to non-English README files
* Ran make fix-copies and corrected some cases.
* Updated index file to include Decision Transformer
* Added gpt2 model as copy inside the Decision Transformer model file
* Added the unit test file to the list of TEST_FILES_WITH_NO_COMMON_TESTS
* Deleted redundant checkpoint files (I don't know how these got committed)
* Removed testing files. (These should have never been committed)
* Removed accidentally committed files
* Moved the Decision Transformer test to its own directory
* Moved DecisionTransformOutput to modeling_decision_transformer
* Moved the example usage to research project and cleaned comments
* Made tests ignore the copy of gpt2 in Decision Transformer
* Added module output to modelling decision transformer
* removed copied gpt2 model from list of transformers models
* Updated tests and created __init__ file for new test location
* Update README.md
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/decision_transformer/configuration_decision_transformer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Removed unneeded summary type from config file
* Fixed copies
* Updated pretrained config map to refer to hopper-medium checkpoint
* Added Decision transformer to model docs
* Update src/transformers/models/decision_transformer/modeling_decision_transformer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/decision_transformer/modeling_decision_transformer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/decision_transformer/configuration_decision_transformer.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Updated model with custom docstring example
* Updated copies, config auto, and readme files.
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Dan Tegzes <48134725+Tegzes@users.noreply.github.com>
Co-authored-by: Adam Montgomerie <adam@avanssion.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
Co-authored-by: Clémentine Fourrier <22726840+clefourrier@users.noreply.github.com>
Co-authored-by: Clementine Fourrier <cfourrie@inria.fr>
Co-authored-by: matt <rocketknight1@gmail.com>
Co-authored-by: Francesco Saverio Zuppichini <francesco.zuppichini@gmail.com>
Co-authored-by: Jacob Dineen <54680234+jacobdineen@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Omar Sanseviero <osanseviero@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
* Make Transformers use cache files when hf.co is down
* Fix tests
* Was there a random circleCI failure?
* Isolate patches
* Style
* Comment out the failure since it doesn't fail anymore
* Better comment
* Split file_utils in several submodules
* Fixes
* Add back more objects
* More fixes
* Who exactly decided to import that from there?
* Second suggestion to code with code review
* Revert wront move
* Fix imports
* Adapt all imports
* Adapt all imports everywhere
* Revert this import, will fix in a separate commit
* Updates the default branch from master to main
* Links from `master` to `main`
* Typo
* Update examples/flax/README.md
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Aggressive PT/TF equivalence test on PT side
* Ugly fix for `TFTapasForQuestionAnswering`
* apply review suggestions
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Attention mask is important in the case of batching...
* Improve the fix.
* Making the sentence different enough that they exhibit different
predictions.
* Update expected slices for pillow > 9
* Add expected slices depending on pillow version
* Add different slices depending on pillow version for other models
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
* padding done
* correctly return one attention per layer
* almost correct, attentions are not flatten one tuple per stage
* tests green
* doc
* conversations
* reshaping hidden_states
* view in the test
* reshape_hidden_states in Encoder and Model
* new outputs with reshaped_hidden_states
* conversations
* doc
* Update docs/source/model_doc/swin.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* conversations
* fix tests
* minor changes
* resolved conversations
* attentions one per stage
* typo
* typos
* typos
* function signature
* CI
* clean up tests
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* First attempt at TF XLA generation
* Fix comments
* Update XLA greedy generate with direct XLA calls
* Support attention mask, prepare_inputs_for_generation no longer hardcoded for greedy
* Handle position_ids correctly
* make xla generate work for non xla case
* force using xla generate
* refactor
* more fixes
* finish cleaning
* finish
* finish
* clean gpt2 tests
* add gpt2 tests
* correct more cases
* up
* finish
* finish
* more fixes
* flake 8 stuff
* final rag fix
* Update src/transformers/models/rag/modeling_tf_rag.py
* finish t5 as well
* finish
* Update src/transformers/generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* first commit
* ResNet model correctly implemented.
basic modeling + weights conversion is done
removed unused doc
mdx file
doc and conversion script
added feature_extractor to auto
test
minor changes + style + quality
doc
test
Delete process.yml
A left over from my attempt of running circleci locally
* minor changes
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* new test format
* minor changes from conversations
* minor changes from conversations
* make style + quality
* readded the tests
* test + README
* minor changes from conversations
* error in README
* make fix-copies
* removed regression for classification head
* make quality
* fixed loss control flow
* fixed loss control flow
* resolved conversations
* Apply suggestions from code review
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* READMEs
* index.mdx
* minor changes
* updated tests and models
* unused import
* outputs
* Update docs/source/model_doc/resnet.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* added embeddings_size
* Apply suggestions from code review
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* conversation
* added push to hub
* test
* embedding_size
* make fix-copies
* resolved conversations
* CI
* changed organization
* minor changes
* CI
* minor changes
* conversations
* conversation
* doc
* tests
* removed unused docstring
* conversation
* removed unused outputs
* CI
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Make TF pt-tf equivalence test more aggressive
* Fix for TFConvNextModelTest and TFTransfoXLModelTest
* fix kwargs for outputs
* clean-up
* Add docstring for check_outputs()
* remove: need to rename encoder-decoder
* clean-up
* send PyTorch things to the correct device
* Add back the accidentally removed test case in test_pt_tf_model_equivalence()
* Fix: change to tuple before calling check_outputs()
* Fix: tfo could be a list
* use to_tuple()
* allow tfo only to be tuple or tensor
* allow tfo to be list or tuple for now + style change
* minor fix
* remove np.copy and update comments
* tfo -> tf_output, same for pt
* Add more detailed comment
* remove the incorrect comment
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* add possibility to softly regulate length when using sampling method in model.generate() function
* fix test config, fix formatting
* fix rag integration, fix docstyling
* fix wrong docstring
* change param to tuple, add test
* fix old param in rag_model, remove unused import
* change test according to new param
* fix formatting
* fix test case
* fix doc style
* move start_length calculation to Logitprocessor
* add possibility to softly regulate length when using sampling method in model.generate() function
* fix rag integration, fix docstyling
* fix test config, fix formatting
* change param to tuple, add test
* fix old param in rag_model, remove unused import
* add possibility to softly regulate length when using sampling method in model.generate() function
* change param to tuple, add test
* fix old param in rag_model, remove unused import
* remove unused import
* fix small errors
* fix test
* add possibility to softly regulate length when using sampling method in model.generate() function
* fix test config, fix formatting
* fix rag integration, fix docstyling
* change param to tuple, add test
* fix old param in rag_model, remove unused import
* change test according to new param
* fix test case
* move start_length calculation to Logitprocessor
* add possibility to softly regulate length when using sampling method in model.generate() function
* fix rag integration, fix docstyling
* fix test config, fix formatting
* change param to tuple, add test
* fix old param in rag_model, remove unused import
* add possibility to softly regulate length when using sampling method in model.generate() function
* fix test config, fix formatting
* fix rag integration, fix docstyling
* add possibility to softly regulate length when using sampling method in model.generate() function
* fix rag integration, fix docstyling
* change param to tuple, add test
* fix old param in rag_model, remove unused import
* fix small errors
* Update src/transformers/generation_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/generation_utils.py
* Update src/transformers/generation_utils.py
* fix docstring, add type ind model rag
* fix docstrings
* introduce seq_length variable for cleaner code
* fix black formatting
* add input_ids_seq_length to modeling_rag
* add input_ids_seq_length to test
* retrigger checks
* retrigger checks
Co-authored-by: Kevin Bondzio <kev@AIM-LAP-02.local>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Kevin Bondzio <kev@AIM-LAP-02.fritz.box>
* Fix duplicate arguments passed to dummy inputs in ONNX export
* Fix M2M100 ONNX config
* Ensure we check PreTrained model only if torch is available
* Remove TensorFlow tests for models without PyTorch parity
* Add ONNX support for ViT
* Refactor to use generic preprocessor
* Add vision dep to tests
* Extend ONNX slow tests to ViT
* Add dummy image generator
* Use model_type to determine modality
* Add deprecation warnings for tokenizer argument
* Add warning when overwriting the preprocessor
* Add optional args to docstrings
* Add minimum PyTorch version to OnnxConfig
* Refactor OnnxConfig class variables from CONSTANT_NAME to snake_case
* Add reasonable value for default atol
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Seed get_train_sampler's generator with arg seed to improve reproducibility
and make the world_size<=1 code path more similar to the others
* move test file into trainer test explicitly
* dumb typo
* make style lint happy
* per discussion, switch to data_seed
* 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>
* added classes to get started with constrained beam search
* in progress, think i can directly force tokens now but not yet with the round robin
* think now i have total control, now need to code the bank selection
* technically works as desired, need to optimize and fix design choices leading to undersirable outputs
* complete PR #1 without disjunctive decoding
* removed incorrect tests
* Delete k.txt
* Delete test.py
* Delete test.sh
* revert changes to test scripts
* genutils
* full implementation with testing, no disjunctive yet
* shifted docs
* passing all tests realistically ran locally
* removing accidentally included print statements
* fixed source of error in initial PR test
* fixing the get_device() vs device trap
* fixed documentation docstrings about constrained_beam_search
* fixed tests having failing for Speech2TextModel's floating point inputs
* fix cuda long tensor
* added examples and testing for them and founx & fixed a bug in beam_search and constrained_beam_search
* deleted accidentally added test halting code with assert False
* code reformat
* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update tests/test_generation_utils.py
* fixing based on comments on PR
* took out the testing code that should but work fails without the beam search moditification ; style changes
* fixing comments issues
* docstrings for ConstraintListState
* typo in PhrsalConstraint docstring
* docstrings improvements
* finished adding what is sort of an opinionated implementation of disjunctive generation, but it revealed errors in inner beam search logic during testing.
* fixed bug found in constrained beam search that used beam_idx that were not global across all the batches
* disjunctive constraint working 100% correctly
* passing all tests
* Accidentally included mlruns
* Update src/transformers/generation_beam_constraints.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/generation_beam_constraints.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* complete overhaul of type complexities and other nits
* strict type checks in generate()
* fixing second round of feedback by narsil
* fixed failing generation test because of type check overhaul
* generation test fail fix
* fixing test fails
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Fix to support fast tokenizer with `CLIPProcessor`
* Update CLIPProcessor test for fast tokenizer
* Fix Docstring Style
* Rename into meaningful Variable name in test code
* send PyTorch inputs to the correct device
* Fix: TypeError: can't convert cuda:0 device type tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first.
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Add TF logits wrappers
* Add sample method
* add tests for TF logit wrappers
* TF generate sample tests now run on CPU
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* maskformer
* conflicts
* conflicts
* minor fixes
* feature extractor test fix
refactor MaskFormerLoss following conversation
MaskFormer related types should not trigger a module time import error
missed one
removed all the types that are not used
update config mapping
minor updates in the doc
resolved conversation that doesn't need a discussion
minor changes
resolved conversations
fixed DetrDecoder
* minor changes
minor changes
fixed mdx file
test feature_extractor return types
functional losses -> classes
removed the return type test for the feature extractor
minor changes + style + quality
* conflicts?
* rebase master
* readme
* added missing files
* deleded poolformers test that where in the wrong palce
* CI
* minor changes
* Apply suggestions from code review
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* resolved conversations
* minor changes
* conversations
[Unispeech] Fix slow tests (#15818)
* remove soundfile old way of loading audio
* Adapt slow test
[Barthez Tokenizer] Fix saving (#15815)
[TFXLNet] Correct tf xlnet generate (#15822)
* [TFXLNet] Correct tf xlnet
* adapt test comment
Fix the push run (#15807)
Fix semantic segmentation pipeline test (#15826)
Fix dummy_inputs() to dummy_inputs in symbolic_trace doc (#15776)
Add model specific output classes to PoolFormer model docs (#15746)
* Added model specific output classes to poolformer docs
* Fixed Segformer typo in Poolformer docs
Adding the option to return_timestamps on pure CTC ASR models. (#15792)
* Adding the option to return_timestamps on pure CTC ASR models.
* Remove `math.prod` which was introduced in Python 3.8
* int are not floats.
* Reworking the PR to support "char" vs "word" output.
* Fixup!
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Quality.
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
HFTracer.trace should use/return self.graph to be compatible with torch.fx.Tracer (#15824)
Fix tf.concatenate + test past_key_values for TF models (#15774)
* fix wrong method name tf.concatenate
* add tests related to causal LM / decoder
* make style and quality
* clean-up
* Fix TFBertModel's extended_attention_mask when past_key_values is provided
* Fix tests
* fix copies
* More tf.int8 -> tf.int32 in TF test template
* clean-up
* Update TF test template
* revert the previous commit + update the TF test template
* Fix TF template extended_attention_mask when past_key_values is provided
* Fix some styles manually
* clean-up
* Fix ValueError: too many values to unpack in the test
* Fix more: too many values to unpack in the test
* Add a comment for extended_attention_mask when there is past_key_values
* Fix TFElectra extended_attention_mask when past_key_values is provided
* Add tests to other TF models
* Fix for TF Electra test: add prepare_config_and_inputs_for_decoder
* Fix not passing training arg to lm_head in TFRobertaForCausalLM
* Fix tests (with past) for TF Roberta
* add testing for pask_key_values for TFElectra model
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
[examples/summarization and translation] fix readme (#15833)
Add ONNX Runtime quantization for text classification notebook (#15817)
Re-enable doctests for the quicktour (#15828)
* Re-enable doctests for the quicktour
* Re-enable doctests for task_summary (#15830)
* Remove &
Framework split model report (#15825)
Add TFConvNextModel (#15750)
* feat: initial implementation of convnext in tensorflow.
* fix: sample code for the classification model.
* chore: added checked for from the classification model.
* chore: set bias initializer in the classification head.
* chore: updated license terms.
* chore: removed ununsed imports
* feat: enabled argument during using drop_path.
* chore: replaced tf.identity with layers.Activation(linear).
* chore: edited default checkpoint.
* fix: minor bugs in the initializations.
* partial-fix: tf model errors for loading pretrained pt weights.
* partial-fix: call method updated
* partial-fix: cross loading of weights (4x3 variables to be matched)
* chore: removed unneeded comment.
* removed playground.py
* rebasing
* rebasing and removing playground.py.
* fix: renaming TFConvNextStage conv and layer norm layers
* chore: added initializers and other minor additions.
* chore: added initializers and other minor additions.
* add: tests for convnext.
* fix: integration tester class.
* fix: issues mentioned in pr feedback (round 1).
* fix: how output_hidden_states arg is propoagated inside the network.
* feat: handling of arg for pure cnn models.
* chore: added a note on equal contribution in model docs.
* rebasing
* rebasing and removing playground.py.
* feat: encapsulation for the convnext trunk.
* Fix variable naming; Test-related corrections; Run make fixup
* chore: added Joao as a contributor to convnext.
* rebasing
* rebasing and removing playground.py.
* rebasing
* rebasing and removing playground.py.
* chore: corrected copyright year and added comment on NHWC.
* chore: fixed the black version and ran formatting.
* chore: ran make style.
* chore: removed from_pt argument from test, ran make style.
* rebasing
* rebasing and removing playground.py.
* rebasing
* rebasing and removing playground.py.
* fix: tests in the convnext subclass, ran make style.
* rebasing
* rebasing and removing playground.py.
* rebasing
* rebasing and removing playground.py.
* chore: moved convnext test to the correct location
* fix: locations for the test file of convnext.
* fix: convnext tests.
* chore: applied sgugger's suggestion for dealing w/ output_attentions.
* chore: added comments.
* chore: applied updated quality enviornment style.
* chore: applied formatting with quality enviornment.
* chore: revert to the previous tests/test_modeling_common.py.
* chore: revert to the original test_modeling_common.py
* chore: revert to previous states for test_modeling_tf_common.py and modeling_tf_utils.py
* fix: tests for convnext.
* chore: removed output_attentions argument from convnext config.
* chore: revert to the earlier tf utils.
* fix: output shapes of the hidden states
* chore: removed unnecessary comment
* chore: reverting to the right test_modeling_tf_common.py.
* Styling nits
Co-authored-by: ariG23498 <aritra.born2fly@gmail.com>
Co-authored-by: Joao Gante <joao@huggingface.co>
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>
* minor changes
* doc fix in feature extractor
* doc
* typose
* removed detr logic from config
* removed detr logic from config
* removed num_labels
* small fix in the config
* auxilary -> auxiliary
* make style
* some test is failing
* fix a weird char in config prevending doc-builder
* retry to fix the doc-builder issue
* make style
* new try to fix the doc builder
* CI
* change weights to facebook
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: ariG23498 <aritra.born2fly@gmail.com>
Co-authored-by: Joao Gante <joao@huggingface.co>
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>
* Add data2vec model cloned from roberta
* Add checkpoint conversion script
* Fix copies
* Update docs
* Add checkpoint conversion script
* Remove fairseq data2vec_text script and fix format
* Add comment on where to get data2vec_text.py
* Remove mock implementation cheat.py and fix style
* Fix copies
* Remove TF and Flax classes from init
* Add back copy from fairseq data2vec_text.py and fix style
* Update model name in docs/source/index.mdx to be CamelCase
* Revert model name in table to lower-case to get check_table test to pass
* Update src/transformers/models/data2vec/__init__.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/data2vec/convert_data2vec_original_pytorch_checkpoint_to_pytorch.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update docs/source/model_doc/data2vec.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update docs/source/model_doc/data2vec.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/auto/configuration_auto.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/data2vec/configuration_data2vec.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update tests/test_modeling_data2vec.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/data2vec/configuration_data2vec.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update documentation
* Copy-paste Data2VecConfig from BertConfig
* Update config checkpoint to point to edugp/data2vec-nlp-base. Fix style and repo-consistency
* Update config special tokens to match RoBERTa
* Split multiple assertions and add individual error messages
* Rename Data2VecModel to Data2VecForTextModel
* Add Data2Vec to _toctree.yml
* Rename Data2VecEmbeddings to Data2VecForTextEmbeddings
* Add initial Data2VecForAudio model (unfinished). Only matching fairseq's implementation up to the feature encoder (before positional encoding).
* finish audio model
* finish audio file
* Update names and fix style, quality and repo consistency
* Remove Data2VecAudioForPretraining. Add tests for Data2VecAudio, mimicking the Wav2Vec2 test suite. Fix bias initilization in positional conv layers. Move back configurations for audio and text to separate files.
* add inputs to logits to data2vec'
* correct autio models
* correct config auto
* correct tok auto
* Update utils/tests_fetcher.py
* delete unnecessary files
* delete unnecessary files
* further renaming
* make all tests pass
* finish
* remove useless test file
* Update tests/test_modeling_common.py
* Update utils/check_repo.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/data2vec/modeling_data2vec_text.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Fix copies
* Update docs
* Remove fairseq data2vec_text script and fix format
* Add comment on where to get data2vec_text.py
* Remove mock implementation cheat.py and fix style
* Fix copies
* Remove TF and Flax classes from init
* Add back copy from fairseq data2vec_text.py and fix style
* Update model name in docs/source/index.mdx to be CamelCase
* Revert model name in table to lower-case to get check_table test to pass
* Update documentation
* Update src/transformers/models/data2vec/__init__.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/data2vec/convert_data2vec_original_pytorch_checkpoint_to_pytorch.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/auto/configuration_auto.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/data2vec/configuration_data2vec.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update tests/test_modeling_data2vec.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/data2vec/configuration_data2vec.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/data2vec/modeling_data2vec.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Copy-paste Data2VecConfig from BertConfig
* Update config checkpoint to point to edugp/data2vec-nlp-base. Fix style and repo-consistency
* Update config special tokens to match RoBERTa
* Split multiple assertions and add individual error messages
* Rename Data2VecModel to Data2VecForTextModel
* Add Data2Vec to _toctree.yml
* Rename Data2VecEmbeddings to Data2VecForTextEmbeddings
* Add initial Data2VecForAudio model (unfinished). Only matching fairseq's implementation up to the feature encoder (before positional encoding).
* finish audio model
* finish audio file
* add inputs to logits to data2vec'
* Update names and fix style, quality and repo consistency
* Remove Data2VecAudioForPretraining. Add tests for Data2VecAudio, mimicking the Wav2Vec2 test suite. Fix bias initilization in positional conv layers. Move back configurations for audio and text to separate files.
* correct autio models
* correct config auto
* correct tok auto
* delete unnecessary files
* delete unnecessary files
* Update utils/tests_fetcher.py
* further renaming
* make all tests pass
* finish
* remove useless test file
* Update tests/test_modeling_common.py
* Update utils/check_repo.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/data2vec/modeling_data2vec_text.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Move data2vec tests to new structure
* Fix test imports for text tests
* Remove fairseq files
* Change paper link to arxiv
* Modify Data2Vec documentation to reflect that the encoder is not shared across the audio and text models in the current implementation.
* Update text model checkpoint to be facebook/data2vec-text-base
* Add 'Copy from' statements and update paper links and docs
* fix copy from statements
* improve copied from
* correct more copied from statements
* finish copied from stuff
* make style
* add model to README
* add to master
Co-authored-by: Eduardo Gonzalez Ponferrada <eduardo@ferrumhealth.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Fixing the timestamps with chunking.
* The changes modified (and fixed) the striding tests.
* Adding a tokenizer test.
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Defense -> comment.
* Update src/transformers/models/wav2vec2/tokenization_wav2vec2.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* rebase
* Delete shift tokens func
* downsample decoder input seq len for init
* correct attention mask
* add tests
* pt flax cross test
* make fixup
* init file for import
* change pt-flax cross test threshold
* pt-flax test logits only
* move tests
* make repo-consistency
* consistent indentation
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* feat: initial implementation of convnext in tensorflow.
* fix: sample code for the classification model.
* chore: added checked for from the classification model.
* chore: set bias initializer in the classification head.
* chore: updated license terms.
* chore: removed ununsed imports
* feat: enabled argument during using drop_path.
* chore: replaced tf.identity with layers.Activation(linear).
* chore: edited default checkpoint.
* fix: minor bugs in the initializations.
* partial-fix: tf model errors for loading pretrained pt weights.
* partial-fix: call method updated
* partial-fix: cross loading of weights (4x3 variables to be matched)
* chore: removed unneeded comment.
* removed playground.py
* rebasing
* rebasing and removing playground.py.
* fix: renaming TFConvNextStage conv and layer norm layers
* chore: added initializers and other minor additions.
* chore: added initializers and other minor additions.
* add: tests for convnext.
* fix: integration tester class.
* fix: issues mentioned in pr feedback (round 1).
* fix: how output_hidden_states arg is propoagated inside the network.
* feat: handling of arg for pure cnn models.
* chore: added a note on equal contribution in model docs.
* rebasing
* rebasing and removing playground.py.
* feat: encapsulation for the convnext trunk.
* Fix variable naming; Test-related corrections; Run make fixup
* chore: added Joao as a contributor to convnext.
* rebasing
* rebasing and removing playground.py.
* rebasing
* rebasing and removing playground.py.
* chore: corrected copyright year and added comment on NHWC.
* chore: fixed the black version and ran formatting.
* chore: ran make style.
* chore: removed from_pt argument from test, ran make style.
* rebasing
* rebasing and removing playground.py.
* rebasing
* rebasing and removing playground.py.
* fix: tests in the convnext subclass, ran make style.
* rebasing
* rebasing and removing playground.py.
* rebasing
* rebasing and removing playground.py.
* chore: moved convnext test to the correct location
* fix: locations for the test file of convnext.
* fix: convnext tests.
* chore: applied sgugger's suggestion for dealing w/ output_attentions.
* chore: added comments.
* chore: applied updated quality enviornment style.
* chore: applied formatting with quality enviornment.
* chore: revert to the previous tests/test_modeling_common.py.
* chore: revert to the original test_modeling_common.py
* chore: revert to previous states for test_modeling_tf_common.py and modeling_tf_utils.py
* fix: tests for convnext.
* chore: removed output_attentions argument from convnext config.
* chore: revert to the earlier tf utils.
* fix: output shapes of the hidden states
* chore: removed unnecessary comment
* chore: reverting to the right test_modeling_tf_common.py.
* Styling nits
Co-authored-by: ariG23498 <aritra.born2fly@gmail.com>
Co-authored-by: Joao Gante <joao@huggingface.co>
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>
* fix wrong method name tf.concatenate
* add tests related to causal LM / decoder
* make style and quality
* clean-up
* Fix TFBertModel's extended_attention_mask when past_key_values is provided
* Fix tests
* fix copies
* More tf.int8 -> tf.int32 in TF test template
* clean-up
* Update TF test template
* revert the previous commit + update the TF test template
* Fix TF template extended_attention_mask when past_key_values is provided
* Fix some styles manually
* clean-up
* Fix ValueError: too many values to unpack in the test
* Fix more: too many values to unpack in the test
* Add a comment for extended_attention_mask when there is past_key_values
* Fix TFElectra extended_attention_mask when past_key_values is provided
* Add tests to other TF models
* Fix for TF Electra test: add prepare_config_and_inputs_for_decoder
* Fix not passing training arg to lm_head in TFRobertaForCausalLM
* Fix tests (with past) for TF Roberta
* add testing for pask_key_values for TFElectra model
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Adding the option to return_timestamps on pure CTC ASR models.
* Remove `math.prod` which was introduced in Python 3.8
* int are not floats.
* Reworking the PR to support "char" vs "word" output.
* Fixup!
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines/automatic_speech_recognition.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Quality.
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Enabling Beit SegFormer to `image-segmentation`.
* Fixing the score.
* Fix import ?
* Missing in type hint.
* Multiple test fixes:
- Add `raw_image` support. It should be the default IMHO since in Python
world it doesn't make any sense to base64 encode the image (Sorry
@mishig, didn't catch that in my review). I really think we should
consider breaking BC here.
- Add support for Segformer tiny test (needed
`SegformerModelTester.get_config` to enable TinyConfig
@NielsRogge)
- Add the check that `batch_size` works correctly on that pipeline.
Uncovered that it doesn't for Detr, which IMO is OK since images
after `feature_extractor` don't have the same size. Comment should
explain.
* Type hint as a string.
* Make fixup + update black.
* torch+vision protections.
* Don't use torchvision, use F.interpolate instead (no new dep).
* Last fixes for Segformer.
* Update test to reflect new image (which was broken)
* Update tests.
* Major BC modification:
- Removed the string compressed PNG string, that's a job for users
`transformers` stays in python land.
- Removed the `score` for semantic segmentation. It has hardly a meaning
on its own in this context.
- Don't include the grayscale with logits for now (which could enable
users to get a sense of confidence). Might be done later.
- Don't include the surface of the mask (could be used for sorting by
users, to filter out small masks). It's already calculable, and
it's easier to add later, than to add now and break later if we need.
* `make fixup`.
* Small changes.
* Rebase + doc fixup.
* [Proposal] Adding ZeroShotImageClassificationPipeline
- Based on CLIP
* WIP, Resurection in progress.
* Resurrection... achieved.
* Reword handling different `padding_value` for `feature_extractor` and
`tokenizer`.
* Thanks doc-builder !
* Adding docs + global namespace `ZeroShotImageClassificationPipeline`.
* Fixing templates.
* Make the test pass and be robust to floating error.
* Adressing suraj's comments on docs mostly.
* Tf support start.
* TF support.
* Update src/transformers/pipelines/zero_shot_image_classification.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* fix bug in PT speech-encoder-decoder
* add pt test for `inputs is not None`
* fix test
* new pt test
* Update tests/test_modeling_speech_encoder_decoder.py
* make fixup
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Very big changes concerning the tokenizer fast of CLIP which did not correspond to the tokenizer slow of CLIP
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Added all files, PoolFormerFeatureExtractor still failing tests
* Fixed PoolFormerFeatureExtractor not being able to import
* Completed Poolformer doc
* Applied Suggested fixes
* Fixed errors in modeling_auto.py
* Fix feature extractor, convert docs to Markdown, styling of code
* Remove PoolFormer from check_repo and fix integration test
* Remove Poolformer from check_repo
* Fixed configuration_poolformer.py docs and removed inference.py from poolformer
* Ran with black v22
* Added PoolFormer to _toctree.yml
* Updated poolformer doc
* Applied suggested fixes and added on README.md
* Did make fixup and make fix-copies, tests should pass now
* Changed PoolFormer weights conversion script name and fixed README
* Applied fixes in test_modeling_poolformer.py and modeling_poolformer.py
* Added PoolFormerFeatureExtractor to AutoFeatureExtractor API
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>
* Implement activations as pytorch modules
* Apply fixup
* Add missing tests for activations
* Update docstring
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
