* Fix mistral generate for long prompt / response
* Add unit test
* fix linter
* fix linter
* fix test
* add assisted generation test for mistral and load the model in 4 bit + fa2
* initial commit
* Add inital testing files and modify __init__ files to add UnivNet imports.
* Fix some bugs
* Add checkpoint conversion script and add references to transformers pre-trained model.
* Add UnivNet entries for auto.
* Add initial docs for UnivNet.
* Handle input and output shapes in UnivNetGan.forward and add initial docstrings.
* Write tests and make them pass.
* Write docs.
* Add UnivNet doc to _toctree.yml and improve docs.
* fix typo
* make fixup
* make fix-copies
* Add upsample_rates parameter to config and improve config documentation.
* make fixup
* make fix-copies
* Remove unused upsample_rates config parameter.
* apply suggestions from review
* make style
* Verify and add reason for skipped tests inherited from ModelTesterMixin.
* Add initial UnivNetGan integration tests
* make style
* Remove noise_length input to UnivNetGan and improve integration tests.
* Fix bug and make style
* Make UnivNet integration tests pass
* Add initial code for UnivNetFeatureExtractor.
* make style
* Add initial tests for UnivNetFeatureExtractor.
* make style
* Properly initialize weights for UnivNetGan
* Get feature extractor fast tests passing
* make style
* Get feature extractor integration tests passing
* Get UnivNet integration tests passing
* make style
* Add UnivNetGan usage example
* make style and use feature extractor from hub in integration tests
* Update tips in docs
* apply suggestions from review
* make style
* Calculate padding directly instead of using get_padding methods.
* Update UnivNetFeatureExtractor.to_dict to be UnivNet-specific.
* Update feature extractor to support using model(**inputs) and add the ability to generate noise and pad the end of the spectrogram in __call__.
* Perform padding before generating noise to ensure the shapes are correct.
* Rename UnivNetGan.forward's noise_waveform argument to noise_sequence.
* make style
* Add tests to test generating noise and padding the end for UnivNetFeatureExtractor.__call__.
* Add tests for checking batched vs unbatched inputs for UnivNet feature extractor and model.
* Add expected mean and stddev checks to the integration tests and make them pass.
* make style
* Make it possible to use model(**inputs), where inputs is the output of the feature extractor.
* fix typo in UnivNetGanConfig example
* Calculate spectrogram_zero from other config values.
* apply suggestions from review
* make style
* Refactor UnivNet conversion script to use load_state_dict (following persimmon).
* Rename UnivNetFeatureExtractor to UnivNetGanFeatureExtractor.
* make style
* Switch to using torch.tensor and torch.testing.assert_close for testing expected values/slices.
* make style
* Use config in UnivNetGan modeling blocks.
* make style
* Rename the spectrogram argument of UnivNetGan.forward to input_features, following Whisper.
* make style
* Improving padding documentation.
* Add UnivNet usage example to the docs.
* apply suggestions from review
* Move dynamic_range_compression computation into the mel_spectrogram method of the feature extractor.
* Improve UnivNetGan.forward return docstring.
* Update table in docs/source/en/index.md.
* make fix-copies
* Rename UnivNet components to have pattern UnivNet*.
* make style
* make fix-copies
* Update docs
* make style
* Increase tolerance on flaky unbatched integration test.
* Remove torch.no_grad decorators from UnivNet integration tests to try to avoid flax/Tensorflow test errors.
* Add padding_mask argument to UnivNetModel.forward and add batch_decode feature extractor method to remove padding.
* Update documentation and clean up padding code.
* make style
* make style
* Remove torch dependency from UnivNetFeatureExtractor.
* make style
* Fix UnivNetModel usage example
* Clean up feature extractor code/docstrings.
* apply suggestions from review
* make style
* Add comments for tests skipped via ModelTesterMixin flags.
* Add comment for model parallel tests skipped via the test_model_parallel ModelTesterMixin flag.
* Add # Copied from statements to copied UnivNetFeatureExtractionTest tests.
* Simplify UnivNetFeatureExtractorTest.test_batch_decode.
* Add support for unbatched padding_masks in UnivNetModel.forward.
* Refactor unbatched padding_mask support.
* make style
* [Whisper] Add seq gen
* [Whisper] Add seq gen
* more debug
* Fix whisper logit processor
* Improve whisper code further
* Fix more
* more debug
* more debug
* Improve further
* Add tests
* Prep for batch size > 1
* Get batch_size>1 working
* Correct more
* Add extensive tests
* more debug
* more debug
* more debug
* add more tests
* more debug
* Apply suggestions from code review
* more debug
* add comments to explain the code better
* add comments to explain the code better
* add comments to explain the code better
* Add more examples
* add comments to explain the code better
* fix more
* add comments to explain the code better
* add comments to explain the code better
* correct
* correct
* finalize
* Apply suggestions from code review
* Apply suggestions from code review
* tvp model for video grounding
add tokenizer auto
fix param in TVPProcessor
add docs
clear comments and enable different torch dtype
add image processor test and model test and fix code style
* fix conflict
* fix model doc
* fix image processing tests
* fix tvp tests
* remove torch in processor
* fix grammar error
* add more details on tvp.md
* fix model arch for loss, grammar, and processor
* add docstring and do not regard TvpTransformer, TvpVisionModel as individual model
* use pad_image
* update copyright
* control first downsample stride
* reduce first only works for ResNetBottleNeckLayer
* fix param name
* fix style
* add testing
* fix style
* rm init_weight
* fix style
* add post init
* fix comments
* do not test TvpTransformer
* fix warning
* fix style
* fix example
* fix config map
* add link in config
* fix comments
* fix style
* rm useless param
* change attention
* change test
* add notes
* fix comments
* fix tvp
* import checkpointing
* fix gradient checkpointing
* Use a more accurate example in readme
* update
* fix copy
* fix style
* update readme
* delete print
* remove tvp test_forward_signature
* remove TvpTransformer
* fix test init model
* merge main and make style
* fix tests and others
* fix image processor
* fix style and model_input_names
* fix tests
* fix image_attention gate in idefics modeling
* update comment
* cleaner gating
* fix gate condition
* create attention gate once
* update comment
* update doc of cross-attention forward
* improve comment
* bring back no_images
* pass cross_attention_gate similarly to no_images gate
* add information on gate shape
* fix no_images placement
* make tests for gate
* take off no_images logic
* update test based on comments
* raise value error if cross_attention_gate is None
* send cross_attention_gate to device
* Revert "send cross_attention_gate to device"
This reverts commit 054f842284.
* send cross_attention_gate to device
* fix device in test + nit
* fill hidden_states with zeros instead of multiplying with the gate
* style
* Update src/transformers/models/idefics/modeling_idefics.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/idefics/modeling_idefics.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Load idx2sym from pretrained vocab file in Transformer XL
When loading vocab file from a pretrained tokenizer for Transformer XL,
although the pickled vocabulary file contains a idx2sym key, it isn't
loaded, because it is discarded as the empty list already exists as
an attribute.
Solution is to explicitly take it into account, just like for sym2idx.
* ran make style
* try to stylify using ruff
* might need to remove these changes?
* use ruf format andruff check
* use isinstance instead of type comparision
* use # fmt: skip
* use # fmt: skip
* nits
* soem styling changes
* update ci job
* nits isinstance
* more files update
* nits
* more nits
* small nits
* check and format
* revert wrong changes
* actually use formatter instead of checker
* nits
* well docbuilder is overwriting this commit
* revert notebook changes
* try to nuke docbuilder
* style
* fix feature exrtaction test
* remve `indent-width = 4`
* fixup
* more nits
* update the ruff version that we use
* style
* nuke docbuilder styling
* leve the print for detected changes
* nits
* Remove file I/O
Co-authored-by: charliermarsh
<charlie.r.marsh@gmail.com>
* style
* nits
* revert notebook changes
* Add # fmt skip when possible
* Add # fmt skip when possible
* Fix
* More ` # fmt: skip` usage
* More ` # fmt: skip` usage
* More ` # fmt: skip` usage
* NIts
* more fixes
* fix tapas
* Another way to skip
* Recommended way
* Fix two more fiels
* Remove asynch
Remove asynch
---------
Co-authored-by: charliermarsh <charlie.r.marsh@gmail.com>
* fix speecht5 wrong attention mask when padding
* enable batch generation and add parameter attention_mask
* fix doc
* fix format
* batch postnet inputs, return batched lengths, and consistent to old api
* fix format
* fix format
* fix the format
* fix doc-builder error
* add test, cross attention and docstring
* optimize code based on reviews
* docbuild
* refine
* not skip slow test
* add consistent dropout for batching
* loose atol
* add another test regarding to the consistency of vocoder
* fix format
* refactor
* add return_concrete_lengths as parameter for consistency w/wo batching
* fix review issues
* fix cross_attention issue
* Initial commit of PatchTST model classes
Co-authored-by: Phanwadee Sinthong <phsinthong@gmail.com>
Co-authored-by: Nam Nguyen <namctin@gmail.com>
Co-authored-by: Vijay Ekambaram <vijaykr.e@gmail.com>
Co-authored-by: Ngoc Diep Do <55230119+diepi@users.noreply.github.com>
Co-authored-by: Wesley Gifford <79663411+wgifford@users.noreply.github.com>
* Add PatchTSTForPretraining
* update to include classification
Co-authored-by: Phanwadee Sinthong <phsinthong@gmail.com>
Co-authored-by: Nam Nguyen <namctin@gmail.com>
Co-authored-by: Vijay Ekambaram <vijaykr.e@gmail.com>
Co-authored-by: Ngoc Diep Do <55230119+diepi@users.noreply.github.com>
Co-authored-by: Wesley Gifford <79663411+wgifford@users.noreply.github.com>
* clean up auto files
* Add PatchTSTForPrediction
* Fix relative import
* Replace original PatchTSTEncoder with ChannelAttentionPatchTSTEncoder
* temporary adding absolute path + add PatchTSTForForecasting class
* Update base PatchTSTModel + Unittest
* Update ForecastHead to use the config class
* edit cv_random_masking, add mask to model output
* Update configuration_patchtst.py
* add masked_loss to the pretraining
* add PatchEmbeddings
* Update configuration_patchtst.py
* edit loss which considers mask in the pretraining
* remove patch_last option
* Add commits from internal repo
* Update ForecastHead
* Add model weight initilization + unittest
* Update PatchTST unittest to use local import
* PatchTST integration tests for pretraining and prediction
* Added PatchTSTForRegression + update unittest to include label generation
* Revert unrelated model test file
* Combine similar output classes
* update PredictionHead
* Update configuration_patchtst.py
* Add Revin
* small edit to PatchTSTModelOutputWithNoAttention
* Update modeling_patchtst.py
* Updating integration test for forecasting
* Fix unittest after class structure changed
* docstring updates
* change input_size to num_input_channels
* more formatting
* Remove some unused params
* Add a comment for pretrained models
* add channel_attention option
add channel_attention option and remove unused positional encoders.
* Update PatchTST models to use HF's MultiHeadAttention module
* Update paper + github urls
* Fix hidden_state return value
* Update integration test to use PatchTSTForForecasting
* Adding dataclass decorator for model output classes
* Run fixup script
* Rename model repos for integration test
* edit argument explanation
* change individual option to shared_projection
* style
* Rename integration test + import cleanup
* Fix outpu_hidden_states return value
* removed unused mode
* added std, mean and nops scaler
* add initial distributional loss for predition
* fix typo in docs
* add generate function
* formatting
* add num_parallel_samples
* Fix a typo
* copy weighted_average function, edit PredictionHead
* edit PredictionHead
* add distribution head to forecasting
* formatting
* Add generate function for forecasting
* Add generate function to prediction task
* formatting
* use argsort
* add past_observed_mask ordering
* fix arguments
* docs
* add back test_model_outputs_equivalence test
* formatting
* cleanup
* formatting
* use ACT2CLS
* formatting
* fix add_start_docstrings decorator
* add distribution head and generate function to regression task
add distribution head and generate function to regression task. Also made add PatchTSTForForecastingOutput, PatchTSTForRegressionOutput.
* add distribution head and generate function to regression task
add distribution head and generate function to regression task. Also made add PatchTSTForForecastingOutput, PatchTSTForRegressionOutput.
* fix typos
* add forecast_masking
* fixed tests
* use set_seed
* fix doc test
* formatting
* Update docs/source/en/model_doc/patchtst.md
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* better var names
* rename PatchTSTTranspose
* fix argument names and docs string
* remove compute_num_patches and unused class
* remove assert
* renamed to PatchTSTMasking
* use num_labels for classification
* use num_labels
* use default num_labels from super class
* move model_type after docstring
* renamed PatchTSTForMaskPretraining
* bs -> batch_size
* more review fixes
* use hidden_state
* rename encoder layer and block class
* remove commented seed_number
* edit docstring
* Add docstring
* formatting
* use past_observed_mask
* doc suggestion
* make fix-copies
* use Args:
* add docstring
* add docstring
* change some variable names and add PatchTST before some class names
* formatting
* fix argument types
* fix tests
* change x variable to patch_input
* format
* formatting
* fix-copies
* Update tests/models/patchtst/test_modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* move loss to forward
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* formatting
* fix a bug when pre_norm is set to True
* output_hidden_states is set to False as default
* set pre_norm=True as default
* format docstring
* format
* output_hidden_states is None by default
* add missing docs
* better var names
* docstring: remove default to False in output_hidden_states
* change labels name to target_values in regression task
* format
* fix tests
* change to forecast_mask_ratios and random_mask_ratio
* change mask names
* change future_values to target_values param in the prediction class
* remove nn.Sequential and make PatchTSTBatchNorm class
* black
* fix argument name for prediction
* add output_attentions option
* add output_attentions to PatchTSTEncoder
* formatting
* Add attention output option to all classes
* Remove PatchTSTEncoderBlock
* create PatchTSTEmbedding class
* use config in PatchTSTPatchify
* Use config in PatchTSTMasking class
* add channel_attn_weights
* Add PatchTSTScaler class
* add output_attentions arg to test function
* format
* Update doc with image patchtst.md
* fix-copies
* rename Forecast <-> Prediction
* change name of a few parameters to match with PatchTSMixer.
* Remove *ForForecasting class to match with other time series models.
* make style
* Remove PatchTSTForForecasting in the test
* remove PatchTSTForForecastingOutput class
* change test_forecast_head to test_prediction_head
* style
* fix docs
* fix tests
* change num_labels to num_targets
* Remove PatchTSTTranspose
* remove arguments in PatchTSTMeanScaler
* remove arguments in PatchTSTStdScaler
* add config as an argument to all the scaler classes
* reformat
* Add norm_eps for batchnorm and layernorm
* reformat.
* reformat
* edit docstring
* update docstring
* change variable name pooling to pooling_type
* fix output_hidden_states as tuple
* fix bug when calling PatchTSTBatchNorm
* change stride to patch_stride
* create PatchTSTPositionalEncoding class and restructure the PatchTSTEncoder
* formatting
* initialize scalers with configs
* edit output_hidden_states
* style
* fix forecast_mask_patches doc string
---------
Co-authored-by: Gift Sinthong <gift.sinthong@ibm.com>
Co-authored-by: Nam Nguyen <namctin@gmail.com>
Co-authored-by: Vijay Ekambaram <vijaykr.e@gmail.com>
Co-authored-by: Ngoc Diep Do <55230119+diepi@users.noreply.github.com>
Co-authored-by: Wesley Gifford <79663411+wgifford@users.noreply.github.com>
Co-authored-by: Wesley M. Gifford <wmgifford@us.ibm.com>
Co-authored-by: nnguyen <nnguyen@us.ibm.com>
Co-authored-by: Ngoc Diep Do <diiepy@gmail.com>
Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* only dir not even init
* init
* tokenizer removed and reference of codegen added
* modeling file updated a lot remaining app_rotary_emb
* conversion script done
* conversion script fixed, a lot of factoring done and most tests pass
* added token_clf and extractive_QA_head
* integration tests pass
* flash attn tests pass!
* config done
* more docs in modeling file
* some style fix
* style and others
* doc test error fix
* more doc fix
* some attention fixes
* most fixes
* style and other fixes
* docs fix and config
* doc fix
* some comments
* conversion script updated
* conversion script updated
* Revert "conversion script updated"
This reverts commit e92378c54084ec0747041b113083d1746ecb6c7f.
* final comments
* add Phi to language_modeling.md
* edit phi.md file
* rebase and fix
* removed phi-1.5 example
* changed model_type from 'phi'->'mixformer-sequential'
* small change
* small change
* revert \small change
* changed mixformer-sequential->phi
* small change
* added phi-1.5 example instead of phi-1
* doc test might pass now
* rebase and small change
* added the dropout layer
* more fixes
* modified .md file
* very very small doc change
* init commit
* attention arch done except rotary emb
* rotary emb done
* text encoder working
* outputs matching
* arch first pass done
* make commands done, tests and docs remaining
* all tests passed, only docs remaining
* docs done
* doc-builder fix
* convert script removed(not relevant)
* minor comments done
* added ckpt conversion script
* tokenizer done
* very minor fix of index.md 2
* mostly make fixup related
* all done except fe and rotary emb
* very small change
* removed unidecode dependency
* style changes
* tokenizer removed require_backends
* added require_inflect to tokenizer tests
* removed VOCAB_FILES in tokenizer test
* inflect dependency removed
* added rotary pos emb cache and simplified the apply method
* style
* little doc change
* more comments
* feature extractor added
* added processor
* auto-regressive config added
* added CLVPConditioningEncoder
* comments done except the test one
* weights added successfull(NOT tested)
* tokenizer fix with numbers
* generate outputs matching
* almost tests passing Integ tests not written
* Integ tests added
* major CUDA error fixed
* docs done
* rebase and multiple fixes
* fixed rebase overwrites
* generate code simplified and tests for AutoRegressive model added
* minor changes
* refectored gpt2 code in clvp file
* weights done and all code refactored
* mostly done except the fast_tokenizer
* doc test fix
* config file's doc fixes
* more config fix
* more comments
* tokenizer comments mostly done
* modeling file mostly refactored and can load modules
* ClvpEncoder tested
* ClvpDecoder, ClvpModel and ClvpForCausalLM tested
* integration and all tests passed
* more fixes
* docs almost done
* ckpt conversion refectored
* style and some failing tests fix
* comments
* temporary output fix but test_assisted_decoding_matches_greedy_search test fails
* majority changes done
* use_cache outputs same now! Along with the asisted_greedy_decoding test fix
* more comments
* more comments
* prepare_inputs_for_generation fixed and _prepare_model_inputs added
* style fix
* clvp.md change
* moved clvpconditionalencoder norms
* add model to new index
* added tokenizer input_ids_with_special_tokens
* small fix
* config mostly done
* added config-tester and changed conversion script
* more comments
* comments
* style fix
* some comments
* tokenizer changed back to prev state
* small commnets
* added output hidden states for the main model
* style fix
* comments
* small change
* revert small change
* .
* Update clvp.md
* Update test_modeling_clvp.py
* :)
* some minor change
* new fixes
* remove to_dict from FE
* add audio_utils usage in the FE of SpeechToText
* clean unecessary parameters of AudioSpectrogramTransformer FE
* add audio_utils usage in AST
* add serialization tests and function to FEs
* make style
* remove use_torchaudio and move to_dict to FE
* test audio_utils usage
* make style and fix import (remove torchaudio dependency import)
* fix torch dependency for jax and tensor tests
* fix typo
* clean tests with suggestions
* add lines to test if is_speech_availble is False
* Use Llama RoPE implementation for Falcon
+ Add copy functionalities
* Use standard cache format for Falcon
* Simplify apply_rotary_pos_emb, copy from Llama
* Remove unnecessary cache conversion test
We don't need to convert any caches anymore!
* Resolve copy complaint
* Fixing m4t.
* Trying to remove comparison ? Odd test failure.
* Adding shared. But why on earth does it hang ????
* Putting back the model weights checks the test is silently failing on
cuda.
* Fix style + unremoved comment.
* Fix Fuyu image scaling bug
It could produce negative padding and hence inference errors for certain
image sizes.
* initial rework commit
* add batching capabilities, refactor image processing
* add functional batching for a list of images and texts
* make args explicit
* Fuyu processing update (#27133)
* Add file headers
* Add file headers
* First pass - preprocess method with standard args
* First pass image processor rework
* Small tweaks
* More args and docstrings
* Tidying iterating over batch
* Tidying up
* Modify to have quick tests (for now)
* Fix up
* BatchFeature
* Passing tests
* Add tests for processor
* Sense check when patchifying
* Add some tests
* FuyuBatchFeature
* Post-process box coordinates
* Update to `size` in processor
* Remove unused and duplicate constants
* Store unpadded dims after resize
* Fix up
* Return FuyuBatchFeature
* Get unpadded sizes after resize
* Update exception
* Fix return
* Convert input `<box>` coordinates to model format.
* Post-process point coords, support multiple boxes/points in a single
sequence
* Replace constants
* Update src/transformers/models/fuyu/image_processing_fuyu.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Preprocess List[List[image]]
* Update src/transformers/models/fuyu/image_processing_fuyu.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update to Amy's latest state.
* post-processing returns a list of tensors
* Fix error when target_sizes is None
Co-authored-by: Pablo Montalvo <pablo.montalvo.leroux@gmail.com>
* Update src/transformers/models/fuyu/image_processing_fuyu.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update src/transformers/models/fuyu/image_processing_fuyu.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update src/transformers/models/fuyu/image_processing_fuyu.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update src/transformers/models/fuyu/image_processing_fuyu.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Review comments
* Update src/transformers/models/fuyu/image_processing_fuyu.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Fix up
* Fix up
---------
Co-authored-by: Ubuntu <ubuntu@ip-172-31-72-126.ec2.internal>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Pablo Montalvo <pablo.montalvo.leroux@gmail.com>
* Fix conflicts in fuyu_follow_up_image_processing (#27228)
fixing conflicts and updating on main
* Revert "Fix conflicts in fuyu_follow_up_image_processing" (#27232)
Revert "Fix conflicts in fuyu_follow_up_image_processing (#27228)"
This reverts commit acce10b6c6.
---------
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-72-126.ec2.internal>
* add whisper fa2
* correct
* change all
* correct
* correct
* fix more
* fix more
* fix more
* fix more
* fix more
* fix more
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* fix more
* fix more
* fix more
* fix more
* fix more
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Add type annotations to TFConvNextDropPath
* Use tf.debugging.assert_equal for TFConvNextEmbeddings shape check
* Add TensorFlow implementation of ConvNeXTV2
* check_docstrings: add TFConvNextV2Model to exclusions
TFConvNextV2Model and TFConvNextV2ForImageClassification have docstrings
which are equivalent to their PyTorch cousins, but a parsing issue prevents them
from passing the test.
Adding exclusions for these two classes as discussed in #25558.
* Safetensors serialization by default
* First pass on the tests
* Second pass on the tests
* Third pass on the tests
* Fix TF weight loading from TF-format safetensors
* Specific encoder-decoder fixes for weight crossloading
* Add VisionEncoderDecoder fixes for TF too
* Change filename test for pt-to-tf
* One missing fix for TFVisionEncoderDecoder
* Fix the other crossload test
* Support for flax + updated tests
* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* Sanchit's comments
* Sanchit's comments 2
* Nico's comments
* Fix tests
* cleanup
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
---------
Co-authored-by: Matt <rocketknight1@gmail.com>
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* stronger GC tests
* better tests and skip failing tests
* break down into 3 sub-tests
* break down into 3 sub-tests
* refactor a bit
* more refactor
* fix
* last nit
* credits contrib and suggestions
* credits contrib and suggestions
---------
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* add early stopping logits processor
* black formmated
* indent
* follow method signature
* actual logic
* check for None
* address comments on docstrings and method signature
* add unit test under `LogitsProcessorTest` wip
* unit test passing
* black formatted
* condition per sample
* add to BarkModelIntegrationTests
* wip BarkSemanticModelTest
* rename and add to kwargs handling
* not add to BarkSemanticModelTest
* correct logic and assert last outputs tokens different in test
* doc-builder style
* read from kwargs as well
* assert len of with less than that of without
* ruff
* add back seed and test case
* add original impl default suggestion
* doc-builder
* rename and use softmax
* switch back to LogitsProcessor and update docs wording
* camelCase and spelling and saving compute
* assert strictly less than
* assert less than
* expand test_generate_semantic_early_stop instead
* Add a default decoder_attention_mask for EncoderDecoderModel during training
Since we are already creating the default decoder_input_ids from the labels, we should also
create a default decoder_attention_mask to go with it.
* Fix test constant that relied on manual_seed()
The test was changed to use a decoder_attention_mask that ignores padding instead (which is
the default one created by BERT when attention_mask is None).
* Create the decoder_attention_mask using decoder_input_ids instead of labels
* Fix formatting in test
* adds agnostic decorators and availability fns
* renaming decorators and fixing imports
* updating some representative example tests
bloom, opt, and reformer for now
* wip device agnostic functions
* lru cache to device checking functions
* adds `TRANSFORMERS_TEST_DEVICE_SPEC`
if present, imports the target file and updates device to function
mappings
* comments `TRANSFORMERS_TEST_DEVICE_SPEC` code
* extra checks on device name
* `make style; make quality`
* updates default functions for agnostic calls
* applies suggestions from review
* adds `is_torch_available` guard
* Add spec file to docs, rename function dispatch names to backend_*
* add backend import to docs example for spec file
* change instances of to
* Move register backend to before device check as per @statelesshz changes
* make style
* make opt test require fp16 to run
---------
Co-authored-by: arsalanu <arsalanu@graphcore.ai>
Co-authored-by: arsalanu <hzji210@gmail.com>
* first raw commit
* still POC
* tentative convert script
* almost working speech encoder conversion scripts
* intermediate code for encoder/decoders
* add modeling code
* first version of speech encoder
* make style
* add new adapter layer architecture
* add adapter block
* add first tentative config
* add working speech encoder conversion
* base model convert works now
* make style
* remove unnecessary classes
* remove unecessary functions
* add modeling code speech encoder
* rework logics
* forward pass of sub components work
* add modeling codes
* some config modifs and modeling code modifs
* save WIP
* new edits
* same output speech encoder
* correct attention mask
* correct attention mask
* fix generation
* new generation logics
* erase comments
* make style
* fix typo
* add some descriptions
* new state
* clean imports
* add tests
* make style
* make beam search and num_return_sequences>1 works
* correct edge case issue
* correct SeamlessM4TConformerSamePadLayer copied from
* replace ACT2FN relu by nn.relu
* remove unecessary return variable
* move back a class
* change name conformer_attention_mask ->conv_attention_mask
* better nit code
* add some Copied from statements
* small nits
* small nit in dict.get
* rename t2u model -> conditionalgeneration
* ongoing refactoring of structure
* update models architecture
* remove SeamlessM4TMultiModal classes
* add tests
* adapt tests
* some non-working code for vocoder
* add seamlessM4T vocoder
* remove buggy line
* fix some hifigan related bugs
* remove hifigan specifc config
* change
* add WIP tokenization
* add seamlessM4T working tokenzier
* update tokenization
* add tentative feature extractor
* Update converting script
* update working FE
* refactor input_values -> input_features
* update FE
* changes in generation, tokenizer and modeling
* make style and add t2u_decoder_input_ids
* add intermediate outputs for ToSpeech models
* add vocoder to speech models
* update valueerror
* update FE with languages
* add vocoder convert
* update config docstrings and names
* update generation code and configuration
* remove todos and update config.pad_token_id to generation_config.pad_token_id
* move block vocoder
* remove unecessary code and uniformize tospeech code
* add feature extractor import
* make style and fix some copies from
* correct consistency + make fix-copies
* add processor code
* remove comments
* add fast tokenizer support
* correct pad_token_id in M4TModel
* correct config
* update tests and codes + make style
* make some suggested correstion - correct comments and change naming
* rename some attributes
* rename some attributes
* remove unecessary sequential
* remove option to use dur predictor
* nit
* refactor hifigan
* replace normalize_mean and normalize_var with do_normalize + save lang ids to generation config
* add tests
* change tgt_lang logic
* update generation ToSpeech
* add support import SeamlessM4TProcessor
* fix generate
* make tests
* update integration tests, add option to only return text and update tokenizer fast
* fix wrong function call
* update import and convert script
* update integration tests + update repo id
* correct paths and add first test
* update how new attention masks are computed
* update tests
* take first care of batching in vocoder code
* add batching with the vocoder
* add waveform lengths to model outputs
* make style
* add generate kwargs + forward kwargs of M4TModel
* add docstrings forward methods
* reformate docstrings
* add docstrings t2u model
* add another round of modeling docstrings + reformate speaker_id -> spkr_id
* make style
* fix check_repo
* make style
* add seamlessm4t to toctree
* correct check_config_attributes
* write config docstrings + some modifs
* make style
* add docstrings tokenizer
* add docstrings to processor, fe and tokenizers
* make style
* write first version of model docs
* fix FE + correct FE test
* fix tokenizer + add correct integration tests
* fix most tokenization tests
* make style
* correct most processor test
* add generation tests and fix num_return_sequences > 1
* correct integration tests -still one left
* make style
* correct position embedding
* change numbeams to 1
* refactor some modeling code and correct one test
* make style
* correct typo
* refactor intermediate fnn
* refactor feedforward conformer
* make style
* remove comments
* make style
* fix tokenizer tests
* make style
* correct processor tests
* make style
* correct S2TT integration
* Apply suggestions from Sanchit code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* correct typo
* replace torch.nn->nn + make style
* change Output naming (waveforms -> waveform) and ordering
* nit renaming and formating
* remove return None when not necessary
* refactor SeamlessM4TConformerFeedForward
* nit typo
* remove almost copied from comments
* add a copied from comment and remove an unecessary dropout
* remove inputs_embeds from speechencoder
* remove backward compatibiliy function
* reformate class docstrings for a few components
* remove unecessary methods
* split over 2 lines smthg hard to read
* make style
* replace two steps offset by one step as suggested
* nice typo
* move warnings
* remove useless lines from processor
* make generation non-standard test more robusts
* remove torch.inference_mode from tests
* split integration tests
* enrich md
* rename control_symbol_vocoder_offset->vocoder_offset
* clean convert file
* remove tgt_lang and src_lang from FE
* change generate docstring of ToText models
* update generate docstring of tospeech models
* unify how to deal withtext_decoder_input_ids
* add default spkr_id
* unify tgt_lang for t2u_model
* simplify tgt_lang verification
* remove a todo
* change config docstring
* make style
* simplify t2u_tgt_lang_id
* make style
* enrich/correct comments
* enrich .md
* correct typo in docstrings
* add torchaudio dependency
* update tokenizer
* make style and fix copies
* modify SeamlessM4TConverter with new tokenizer behaviour
* make style
* correct small typo docs
* fix import
* update docs and add requirement to tests
* add convert_fairseq2_to_hf in utils/not_doctested.txt
* update FE
* fix imports and make style
* remove torchaudio in FE test
* add seamless_m4t.md to utils/not_doctested.txt
* nits and change the way docstring dataset is loaded
* move checkpoints from ylacombe/ to facebook/ orga
* refactor warning/error to be in the 119 line width limit
* round overly precised floats
* add stereo audio behaviour
* refactor .md and make style
* enrich docs with more precised architecture description
* readd undocumented models
* make fix-copies
* apply some suggestions
* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* correct bug from previous commit
* refactor a parameter allowing to clean the code + some small nits
* clean tokenizer
* make style and fix
* make style
* clean tokenizers arguments
* add precisions for some tests
* move docs from not_tested to slow
* modify tokenizer according to last comments
* add copied from statements in tests
* correct convert script
* correct parameter docstring style
* correct tokenization
* correct multi gpus
* make style
* clean modeling code
* make style
* add copied from statements
* add copied statements
* add support with ASR pipeline
* remove file added inadvertently
* fix docstrings seamlessM4TModel
* add seamlessM4TConfig to OBJECTS_TO_IGNORE due of unconventional markdown
* add seamlessm4t to assisted generation ignored models
---------
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* initial commit
* add processor, add fuyu naming
* add draft processor
* fix processor
* remove dropout to fix loading of weights
* add image processing fixes from Pedro
* fix
* fix processor
* add basic processing fuyu test
* add documentation and TODO
* address comments, add tests, add doc
* replace assert with torch asserts
* add Mixins and fix tests
* clean imports
* add model tester, clean imports
* fix embedding test
* add updated tests from pre-release model
* Processor: return input_ids used for inference
* separate processing and model tests
* relax test tolerance for embeddings
* add test for logit comparison
* make sure fuyu image processor is imported in the init
* fix formattingh
* more formatting issues
* and more
* fixups
* remove some stuff
* nits
* update init
* remove the fuyu file
* Update integration test with release model
* Update conversion script.
The projection is not used, as confirmed by the authors.
* improve geenration
* Remove duplicate function
* Trickle down patches to model call
* processing fuyu updates
* remove things
* fix prepare_inputs_for_generation to fix generate()
* remove model_input
* update
* add generation tests
* nits
* draft leverage automodel and autoconfig
* nits
* fix dtype patch
* address comments, update READMEs and doc, include tests
* add working processing test, remove refs to subsequences
* add tests, remove Sequence classification
* processing
* update
* update the conversion script
* more processing cleanup
* safe import
* take out ModelTesterMixin for early release
* more cl;eanup
* more cleanup
* more cleanup
* and more
* register a buffer
* nits
* add postprocessing of generate output
* nits
* updates
* add one working test
* fix test
* make fixup works
* fixup
* Arthur's updates
* nits
* update
* update
* fix processor
* update tests
* passe more fixups
* fix
* nits
* don't import torch
* skip fuyu config for now
* fixup done
* fixup
* update
* oups
* nits
* Use input embeddings
* no buffer
* update
* styling processing fuyu
* fix test
* update licence
* protect torch import
* fixup and update not doctested
* kwargs should be passed
* udpates
* update the impofixuprts in the test
* protect import
* protecting imports
* protect imports in type checking
* add testing decorators
* protect top level import structure
* fix typo
* fix check init
* move requires_backend to functions
* Imports
* Protect types
---------
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: ArthurZucker <arthur.zucker@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Lysandre <lysandre@huggingface.co>
* fix
* last attempt
* current work
* fix forward compatibility
* save all special tokens
* current state
* revert additional changes
* updates
* remove tokenizer.model
* add a test and the fix
* nit
* revert one more break
* fix typefield issue
* quality
* more tests
* fix fields for FC
* more nits?
* new additional changes
* how
* some updates
* simplify all
* more nits
* revert some things to original
* nice
* nits
* a small hack
* more nits
* ahhaha
* fixup
* update
* make test run on ci
* use subtesting
* update
* Update .circleci/create_circleci_config.py
* updates
* fixup
* nits
* replace typo
* fix the test
* nits
* update
* None max dif pls
* a partial fix
* had to revert one thing
* test the fast
* updates
* fixup
* and more nits
* more fixes
* update
* Oupsy 👁️
* nits
* fix marian
* on our way to heaven
* Update src/transformers/models/t5/tokenization_t5.py
Co-authored-by: Lysandre Debut <hi@lysand.re>
* fixup
* Update src/transformers/tokenization_utils_fast.py
Co-authored-by: Leo Tronchon <leo.tronchon@gmail.com>
* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Leo Tronchon <leo.tronchon@gmail.com>
* fix phobert
* skip some things, test more
* nits
* fixup
* fix deberta
* update
* update
* more updates
* skip one test
* more updates
* fix camembert
* can't test this one
* more good fixes
* kind of a major update
- seperate what is only done in fast in fast init and refactor
- add_token(AddedToken(..., speicla = True)) ignores it in fast
- better loading
* fixup
* more fixups
* fix pegasus and mpnet
* remove skipped tests
* fix phoneme tokenizer if self.verbose
* fix individual models
* update common tests
* update testing files
* all over again
* nits
* skip test for markup lm
* fixups
* fix order of addition in fast by sorting the added tokens decoder
* proper defaults for deberta
* correct default for fnet
* nits on add tokens, string initialized to special if special
* skip irrelevant herbert tests
* main fixes
* update test added_tokens_serialization
* the fix for bart like models and class instanciating
* update bart
* nit!
* update idefix test
* fix whisper!
* some fixup
* fixups
* revert some of the wrong chanegs
* fixup
* fixup
* skip marian
* skip the correct tests
* skip for tf and flax as well
---------
Co-authored-by: Lysandre Debut <hi@lysand.re>
Co-authored-by: Leo Tronchon <leo.tronchon@gmail.com>
* Adjust length limits and allow naked conversation list inputs
* Adjust length limits and allow naked conversation list inputs
* Maybe use a slightly more reasonable limit than 1024
* Skip tests for old models that never supported this anyway
* Cleanup input docstrings
* More docstring cleanup + skip failing TF test
* Make fixup
* add FA-2 support for mistral
* fixup
* add sliding windows
* fixing few nits
* v1 slicing cache - logits do not match
* add comment
* fix bugs
* more mem efficient
* add warning once
* add warning once
* oops
* fixup
* more comments
* copy
* add safety checker
* fixup
* Update src/transformers/models/mistral/modeling_mistral.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* copied from
* up
* raise when padding side is right
* fixup
* add doc + few minor changes
* fixup
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* add tokenizer kwarg inputs
* Adding tokenizer_kwargs to _sanitize_parameters
* Add truncation=True example to tests
* Update test_pipelines_fill_mask.py
* Update test_pipelines_fill_mask.py
* make fix-copies and make style
* Update fill_mask.py
Replace single tick with double
* make fix-copies
* Style
---------
Co-authored-by: Lysandre <lysandre@huggingface.co>
* fix wav2vec2
* nit
* stash
* one more file to update
* fix byt5
* vocab size is 256, don't change that!
* use other revision
* test persimon in smaller size
* style
* tests
* nits
* update add tokens from pretrained
* test tokenization
* nits
* potential fnet fix?
* more nits
* nits
* correct test
* assert close
* udpate
* ouch
* fix it
* some more nits
* FINALLU
* use `adept` checkpoints
* more adept checkpoints
* that was invlved!
* fix test for bart. Order is correct now let's skip BPEs
* ouf
* styling
* fix bert....
* slow refactoring
* current updates
* massive refactoring
* update
* NICE!
* update to see where I am at
* updates
* update
* update
* revert
* updates
* updates
* start supporting legacy_save
* styling
* big update
* revert some changes
* nits
* nniiiiiice
* small fixes
* kinda fix t5 with new behaviour
* major update
* fixup
* fix copies
* today's updates
* fix byt5
* upfate
* update
* update
* updates
* update vocab size test
* Barthez does not use not need the fairseq offset ids
* super calll must be after
* calll super
* move all super init
* move other super init
* fixup
* nits
* more fixes
* nits
* more fixes
* nits
* more fix
* remove useless files
* ouch all of them are affected
* and more!
* small imporvements
* no more sanitize token
* more changes around unique no split tokens
* partially fix more things
* keep legacy save but add warning
* so... more fixes
* updates
* guess deberta tokenizer could be nuked
* fixup
* fixup did some bad things
* nuke it if it breaks
* remove prints and pretrain fast from slow with new format.
* fixups
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* fiou
* nit
* by default specials should not be normalized?
* update
* remove brakpoint
* updates
* a lot of updates
* fixup
* fixes revert some changes to match fast
* small nits
* that makes it cleaner
* fix camembert accordingly
* update
* some lest breaking changes
* update
* fixup
* fix byt5 and whisper mostly
* some more fixes, canine's byte vocab
* fix gpt2
* fix most of the perceiver tests (4 left)
* fix layout lmv3
* fixup
* fix copies for gpt2 style
* make sure to only warn once
* fix perciever and gpt2 tests
* some more backward compatibility: also read special tokens map because some ppl use it........////.....
* fixup
* add else when reading
* nits
* fresh updates
* fix copies
* will this make everything faster?
* fixes
* more fixes
* update
* more fixes
* fixup
* is the source of truth right?
* sorry camembert for the troubles
* current updates
* fixup
* update led
* update
* fix regression
* fix single word
* more model specific fixes
* fix t5 tests
* fixup
* more comments
* update
* fix nllb
* rstrip removed
* small fixes
* better handle additional_special_tokens and vocab sizes
* fixing
* styling
* fix 4 / 21
* fixup
* fix nlbb's tests
* some fixes
* fix t5
* fixes
* style
* fix canine tests
* damn this is nice
* nits
* m2m100 nit
* fixups
* fixes!
* fixup
* stash
* fix merge
* revert bad change
* fixup
* correct order for code Llama
* fix speecht5 post merge
* styling
* revert source of 11 fails
* small nits
* all changes in one go
* fnet hack
* fix 2 more tests
* update based on main branch of tokenizers
* fixup
* fix VITS issues
* more fixes
* fix mgp test
* fix camembert issues
* oups camembert still has 2 failing tests
* mluke fixes
* decode fixes
* small nits
* nits
* fix llama and vits
* fix camembert
* smal nits
* more fixes when initialising a fast from a slow and etc
* fix one of the last test
* fix CPM tokenizer test
* fixups
* fix pop2piano
* fixup
* ⚠️ Change tokenizers required version ⚠️
* ⚠️ Change tokenizers required version ⚠️
* "tokenizers>=0.14,<0.15", don't forget smaller than
* fix musicgen tests and pretraiendtokenizerfast
* fix owlvit and all
* update t5
* fix 800 red
* fix tests
* fix the fix of the fix of t5
* styling
* documentation nits
* cache _added_tokens_encoder
* fixups
* Nit
* fix red tests
* one last nit!
* make eveything a lot simpler
* Now it's over 😉
* few small nits
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* updates that work for now
* tests that should no be skipped / changed and fixed next
* fixup
* i am ashamed
* pushe the fix
* update
* fixups
* nits
* fix added_tokens_encoder
* fix canine test
* fix pegasus vocab
* fix transfoXL
* fixup
* whisper needs to be fixed for train new
* pegasus nits
* more pegasus fixes
* minor update
* better error message in failed test
* fix whisper failing test
* fix whisper failing test
* fix pegasus
* fixup
* fix **** pegasus
* reset things
* remove another file
* attempts to fix the strange custome encoder and offset
* nits here and there
* update
* fixup
* nit
* fix the whisper test
* nits nits
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* updates based on review
* some small update to potentially remove
* nits
* import rlu cache
* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Lysandre Debut <hi@lysand.re>
* move warning to `from_pretrained`
* update tests results now that the special tokens are always added
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Lysandre Debut <hi@lysand.re>
* moved `ctrl` to `Salesforce/ctrl`
redirects should theoretically work, but still updating those repo references for clarity
* Fixup
* Slow doc tests
* Add modeling file
---------
Co-authored-by: Lysandre <lysandre@huggingface.co>
* add pos embed interpolation for vision encoder
* style
* update config with interpolate_pos_encoding arg
* fix imports formatting
* take off copied from on vision embeddings
* add test for image embeddings interpolation
* add credit for interpolation code
* Update src/transformers/models/idefics/configuration_idefics.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/idefics/vision.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* fix condition to check nbr image patches match shape of pos embeddings
* use kwargs in the forward methods for interpolation
* fix tests
* have interpolate_pos_encoding default to False instead of None
* Update tests/models/idefics/test_modeling_idefics.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/idefics/test_modeling_idefics.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/idefics/test_modeling_idefics.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/idefics/configuration_idefics.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* take off for loop meant to print k,v
* add interpolate_pos_encoding arg in prepare_inputs_for_generation
* add test for interpolated generation
* fix edge case num_patches == num_positions and height == width
* add test for edge case
* fix pos_embed in interpolate
* allow interpolation in bf16 with upcasting
* Update src/transformers/models/idefics/vision.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/idefics/vision.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* add multiple images tests for interpolation and generation
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* add Bros boilerplate
* copy and pasted modeling_bros.py from official Bros repo
* update copyright of bros files
* copy tokenization_bros.py from official repo and update import path
* copy tokenization_bros_fast.py from official repo and update import path
* copy configuration_bros.py from official repo and update import path
* remove trailing period in copyright line
* copy and paste bros/__init__.py from official repo
* save formatting
* remove unused unnecessary pe_type argument - using only crel type
* resolve import issue
* remove unused model classes
* remove unnecessary tests
* remove unused classes
* fix original code's bug - layer_module's argument order
* clean up modeling auto
* add bbox to prepare_config_and_inputs
* set temporary value to hidden_size (32 is too low because of the of the
Bros' positional embedding)
* remove decoder test, update create_and_check* input arguemnts
* add missing variable to model tests
* do make fixup
* update bros.mdx
* add boilerate plate for no_head inference test
* update BROS_PRETRAINED_MODEL_ARCHIVE_LIST (add naver-clova-ocr prefix)
* add prepare_bros_batch_inputs function
* update modeling_common to add bbox inputs in Bros Model Test
* remove unnecessary model inference
* add test case
* add model_doc
* add test case for token_classification
* apply fixup
* update modeling code
* update BrosForTokenClassification loss calculation logic
* revert logits preprocessing logic to make sure logits have original shape
* - update class name
* - add BrosSpadeOutput
- update BrosConfig arguments
* add boilerate plate for no_head inference test
* add prepare_bros_batch_inputs function
* add test case
* add test case for token_classification
* update modeling code
* update BrosForTokenClassification loss calculation logic
* revert logits preprocessing logic to make sure logits have original shape
* apply masking on the fly
* add BrosSpadeForTokenLinking
* update class name
put docstring to the beginning of the file
* separate the logits calculation logic and loss calculation logic
* update logic for loss calculation so that logits shape doesn't change
when return
* update typo
* update prepare_config_and_inputs
* update dummy node initialization
* update last_hidden_states getting logic to consider when return_dict is False
* update box first token mask param
* bugfix: remove random attention mask generation
* update keys to ignore on load missing
* run make style and quality
* apply make style and quality of other codes
* update box_first_token_mask to bool type
* update index.md
* apply make style and quality
* apply make fix-copies
* pass check_repo
* update bros model doc
* docstring bugfix fix
* add checkpoint for doc, tokenizer for doc
* Update README.md
* Update docs/source/en/model_doc/bros.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update bros.md
* Update src/transformers/__init__.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update docs/source/en/model_doc/bros.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* apply suggestions from code review
* apply suggestions from code review
* revert test_processor_markuplm.py
* Update test_processor_markuplm.py
* apply suggestions from code review
* apply suggestions from code review
* apply suggestions from code review
* update BrosSpadeELForTokenClassification head name to entity linker
* add doc string for config params
* update class, var names to more explicit and apply suggestions from code review
* remove unnecessary keys to ignore
* update relation extractor to be initialized with config
* add bros processor
* apply make style and quality
* update bros.md
* remove bros tokenizer, add bros processor that wraps bert tokenizer
* revert change
* apply make fix-copies
* update processor code, update itc -> initial token, stc -> subsequent token
* add type hint
* remove unnecessary condition branches in embedding forward
* fix auto tokenizer fail
* update docstring for each classes
* update bbox input dimension as standard 2 points and convert them to 4
points in forward pass
* update bros docs
* apply suggestions from code review : update Bros -> BROS in bros.md
* 1. box prefix var -> bbox
2. update variable names to be more explicit
* replace einsum with torch matmul
* apply style and quality
* remove unused argument
* remove unused arguments
* update docstrings
* apply suggestions from code review: add BrosBboxEmbeddings, replace
einsum with classical matrix operations
* revert einsum update
* update bros processor
* apply suggestions from code review
* add conversion script for bros
* Apply suggestions from code review
* fix readme
* apply fix-copies
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* First commit while I figure this out
* make fixup
* Remove unused method
* Store prompt attrib
* Fix prompt argument for tests
* Make same changes in fast tokenizer
* Remove global prompts from fast tokenizer too
* stash commit
* stash commit
* Migrate PromptConfig to its True Final Location
* Replace Conversation entirely with the new class
* Import/dependency fixes
* Import/dependency fixes
* Change format for lots of default prompts
* More default prompt fixups
* Revert llama old methods so we can compare
* Fix some default configs
* Fix some default configs
* Fix misspelled kwarg
* Fixes for Blenderbot
* make fixup
* little rebase cleanup
* Add basic documentation
* Quick doc fix
* Truncate docstring for now
* Add handling for the case when messages is a single string
* Quick llama merges
* Update conversational pipeline and tests
* Add a couple of legacy properties for backward compatibility
* More legacy handling
* Add docstring for build_conversation_input_ids
* Restructure PromptConfig
* Let's start T E M P L A T I N G
* Refactor all default configs to use templates instead
* Revert changes to the special token properties since we don't need them anymore
* More class templates
* Make the sandbox even sandier
* Everything replaced with pure templating
* Remove docs for PromptConfig
* Add testing and optional requirement boilerplate
* Fix imports and make fixup
* Fix LLaMA tests and add Conversation docstring
* Finally get LLaMA working with the template system
* Finally get LLaMA working with the template system
* make fixup
* make fixup
* fmt-off for the long lists of test tokens
* Rename method to apply_chat_template for now
* Start on documentation
* Make chat_template a property that reads through to the default if it's not set
* Expand docs
* Expand chat templating doc some more
* trim/lstrip blocks by default and update doc
* Few doc tweaks
* rebase cleanup
* Clarify docstring
* rebase cleanup
* rebase cleanup
* make fixup
* Quick doc edit
* Reformat the standard template to match ChatML
* Re-add PEFT check
* Update docs/source/en/chat_templating.md
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Add apply_chat_template to the tokenizer doc
* make fixup
* Add doc links
* Fix chat links
* Fix chat links
* Explain system messages in the doc
* Add chat template test
* Proper save-loading for chat template attribute
* Add test skips for layout models
* Remove _build_conversation_input_ids, add default_chat_template to code_llama
* Make sure all LLaMA models are using the latest template
* Remove default_system_prompt block in code_llama because it has no default prompt
* Update ConversationPipeline preprocess
* Add correct #Copied from links to the default_chat_templates
* Remove unneeded type checking line
* Add a dummy mark_processsed method
* Reorganize Conversation to have **deprecated_kwargs
* Update chat_templating.md
* Quick fix to LLAMA tests
* Small doc tweaks
* Add proper docstrings and "copied from" statements to all default chat templates
* Merge use_default_system_prompt support for code_llama too
* Improve clarity around self.chat_template
* Docstring fix
* Fix blenderbot default template
* More doctest fix
* Break out some tokenizer kwargs
* Update doc to explain default templates
* Quick tweaks to tokenizer args
* Cleanups for tokenizer args
* Add note about cacheing
* Quick tweak to the chat-templating doc
* Update the LLaMA template with error checking and correct system message embedding
* make fixup
* make fixup
* add requires_jinja
* Cleanup to expected output formatting
* Add cacheing
* Fix typo in llama default template
* Update LLaMA tests
* Update documentation
* Improved legacy handling in the Conversation class
* Update Jinja template with proper error handling
* Quick bugfix
* Proper exception raising
* Change cacheing behaviour so it doesn't try to pickle an entire Jinja env
* make fixup
* rebase cleanup
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* [Whisper Tokenizer] Fix tests after adding timestamps
* fix s2t tokenizer tests
* fix vocab test
* backwards comp
* fix tests
* comment
* style
* fix last test
* fix fast
* make faster
* move logic to decode
* remove skip test
* fix decode with offsets
* fix special tokens
* empty commit to re-trigger ci
* use lru cache
* add: check to remove metaspace from marian tokenizer
* fix: metaspace character being removed from everywhere
* fix: remove redundant check at top
* add: test for marian tokenizer decode fix
* fix: simplified the test
* intiial commit
* updates
* nits
* update conversion script
* update conversion script
* use path to load
* add tips etc
* some modeling logic
* modeling update
* more nits
* nits
* normal layer norm
* update config and doc
* nits
* update doc remove unused
* update
* fix inits and stuff
* fixup
* revert wrong changes
* updates
* more nits
* add default config values to the configuration file
* fixup happy
* update
* 2 tests left
* update readmes
* more nits
* slow test and more documentation
* update readme
* fix licences
* styling
* use fast if possible when saving tokenizer
* remove todo
* remove tokenization tests
* small last nits
* Apply suggestions from code review
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* nits to skip the timout doctest
* fix integration test
* fix test
* update eos token
* update to allow fast tokenization
* styling
* fix codeLlama as well for the update post processor
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* add more copied from statements
* update
* doc passes doctest
* remove `# final layer norm?`
* change docstring prompot
* update
* Update README.md
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* don't doctest the conversion script as it requires more packages
* don't init a model in the config
* oups
* fix doctest
---------
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Put Falcon back
* Update src/transformers/models/auto/configuration_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update test
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* return when length is zero
* Add tests
Co-authored-by: Avnish Narayan <38871737avnishn@users.noreply.github.com>
* Co-authored-by: avnishn
<38871737+avnishn@users.noreply.github.com>
* codeLlama doc should not be on Main
* update test
---------
Co-authored-by: Avnish Narayan <38871737avnishn@users.noreply.github.com>
* fixing name position_embeddings to object_queries
* [fix] renaming variable and docstring do object queries
* [fix] comment position_embedding to object queries
* [feat] changes from make-fix-copies to keep consistency
* Revert "[feat] changes from make-fix-copies to keep consistency"
This reverts commit 56e3e9ede1.
* [tests] fix wrong expected score
* [fix] wrong assignment causing wrong tensor shapes
* [fix] fixing position_embeddings to object queries to keep consistency (make fix copies)
* [fix] make fix copies, renaming position_embeddings to object_queries
* [fix] positional_embeddingss to object queries, fixes from make fix copies
* [fix] comments frmo make fix copies
* [fix] adding args validation to keep version support
* [fix] adding args validation to keep version support -conditional detr
* [fix] adding args validation to keep version support - maskformer
* [style] make fixup style fixes
* [feat] adding args checking
* [feat] fixcopies and args checking
* make fixup
* make fixup
---------
Co-authored-by: Lorenzobattistela <lorenzobattistela@gmail.com>
* add all
* Revert "Delete .github directory"
This reverts commit 9b0ff7b052e2b20b629a26fb13606b78a42944d1.
* make conversion script backward compatible
* fixup
* more styling
* copy to llama changes
* fix repo consistency
* nits
* document correct classes
* updates
* more fixes
* nits
* update auto mappings
* add readmes
* smallupdates
* llama-code replace with llama_code
* make fixup
* updates to the testsing suite
* fix fast nits
* more small fixes
* fix decode
* fix template processing
* properly reset the normalizer
* nits processor
* tokenization tests pass
* styling
* last tests
* additional nits
* one test is left
* nits
Co-authored-by faabian <faabian@users.noreply.github.com>
* update failing test
* fixup
* remove decode infilling users should handle it on their onw after generation, padding can be a problem
* update
* make test slow and more meaningfull
* fixup
* doc update
* fixup
* Apply suggestions from code review
* add kwargs doc
* tokenizer requires `requires_backend`
* type requires_backends
* CodeLlama instead of LlamaCode
* more name cahnges
* nits
* make doctests happy
* small pipeline nits
* last nit
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* update
* add codellama to toctree
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Correct attention mask dtype
* reformat code
* add a test for boolean mask
* convert test to fast test
* delete unwanted print
* use assertTrue for testing
* Add FlaxClipTextModelWithProjection
This is necessary to support the Flax port of Stable Diffusion XL: fb6d705fb5/text_encoder_2/config.json (L3)
Co-authored-by: Martin Müller <martin.muller.me@gmail.com>
Co-authored-by: Juan Acevedo <juancevedo@gmail.com>
* Use FlaxCLIPTextModelOutput
* make fix-copies again
* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* Use `return_dict` for consistency with other uses.
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* Fix docstring example.
* Add new model to FlaxCLIPTextModelTest
* Add to IGNORE_NON_AUTO_CONFIGURED list
* Fix naming convention.
---------
Co-authored-by: Martin Müller <martin.muller.me@gmail.com>
Co-authored-by: Juan Acevedo <juancevedo@gmail.com>
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* properly support Sequence of pretokenizers
* actual fix
* make sure the fix works. Tests are not working for sure!
* hacky way
* add TODO
* update
* add a todo
* nits
* rename test
* nits
* rename test
* add: NumberNormalizer works for integers, floats, common currencies, negative numbers and percentages
* fix: renamed number normalizer class and added normalization to SpeechT5Processor
* fix: restyled with black and ruff, should pass code quality tests
* fix: moved normalization to tokenizer and other small changes to normalizer
* add: test for normalization and changed the existing full tokenizer test
* fix: tokenization tests now pass, made changes to existing tokenization where normalization is covered; added normalize arg to func signature
* fix: changed default normalize setting to False, modified the tests a bit
* fix: added support for comma separated numbers, tokenization on the fly with kwargs and normalizer getter setter funcs
* init commit
* config updated also some modeling
* Processor and Model config combined
* extraction pipeline(upto before spectogram & mel_conditioner) added but not properly tested
* model loading successful!
* feature extractor done!
* FE can now be called from HF
* postprocessing added in fe file
* same as prev commit
* Pop2PianoConfig doc done
* cfg docs slightly changed
* fe docs done
* batched
* batched working!
* temp
* v1
* checking
* trying to go with generate
* with generate and model tests passed
* before rebasing
* .
* tests done docs done remaining others & nits
* nits
* LogMelSpectogram shifted to FeatureExtractor
* is_tf rmeoved from pop2piano/init
* import solved
* tokenization tests added
* minor fixed regarding modeling_pop2piano
* tokenizer changed to only return midi_object and other changes
* Updated paper abstract(Camera-ready version) (#2)
* more comments and nits
* ruff changes
* code quality fix
* sg comments
* t5 change added and rebased
* comments except batching
* batching done
* comments
* small doc fix
* example removed from modeling
* ckpt
* forward it compatible with fe and generation done
* comments
* comments
* code-quality fix(maybe)
* ckpts changed
* doc file changed from mdx to md
* test fixes
* tokenizer test fix
* changes
* nits done main changes remaining
* code modified
* Pop2PianoProcessor added with tests
* other comments
* added Pop2PianoProcessor to dummy_objects
* added require_onnx to modeling file
* changes
* update .md file
* remove extra line in index.md
* back to the main index
* added pop2piano to index
* Added tokenizer.__call__ with valid args and batch_decode and aligned the processor part too
* changes
* added return types to 2 tokenizer methods
* the PR build test might work now
* added backends
* PR build fix
* vocab added
* comments
* refactored vocab into 1 file
* added conversion script
* comments
* essentia version changed in .md
* comments
* more tokenizer tests added
* minor fix
* tests extended for outputs acc check
* small fix
---------
Co-authored-by: Jongho Choi <sweetcocoa@snu.ac.kr>
* draft changes
* update and add tests
* styling for no
* move test
* path to usable model
* update test
* small update
* update bertbased tokenizers
* don'tuse kwargs for _tokenize
* don'tuse kwargs for _tokenize
* fix copies
* update
* update test for special tokenizers
* fixup
* skip two tests
* remove pdb breakpiont()
* wowo
* rewrite custom tests
* nits
* revert chang in target keys
* fix markup lm
* update documentation of the argument
* Replaces calls to `.cuda` with `.to(torch_device)` in tests
`torch.Tensor.cuda()` is a pre-0.4 solution to changing a tensor's device. It is recommended to prefer `.to(...)` for greater flexibility and error handling. Furthermore, this makes it more consistent with other tests (that tend to use `.to(torch_device)`) and ensures the correct device backend is used (if `torch_device` is neither `cpu` or `cuda`).
* addressing review comments
* more formatting changes in Bloom test
* `make style`
* Update tests/models/bloom/test_modeling_bloom.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* fixes style failures
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* fix EVERYTHING
* more fixes
* ⚗️⚗️ Tokenizer magic ⚗️⚗️
* wrong value but test passes for the TODO
* update
* updat
* safe protobuf import?
* style
* non gated repo
* update
* fixup
* Update src/transformers/models/llama/tokenization_llama.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/llama/tokenization_llama.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/t5/test_tokenization_t5.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* nits
* fix t5 too
* use assert equal
* fix llama decoding
* nits on t5
* fixup
* only remove the prefix space, not other spaces
* more deconding tests and more todos
* fix CI as well
* fixup
* skip failing test on CI (its tf its ok)
* skip test_subword_regularization_tokenizer that is also crashing on the CI for TF
* update llama
* revert good fixes
* fixup
* empty
* explain why we need to encode with an additional token
* better warning?
* nits
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Add copied from statements for image processors
* Move out rescale and normalize to base image processor
* Remove rescale and normalize from vit (post rebase)
* Update docstrings and tidy up
* PR comments
* Add input_data_format as preprocess argument
* Resolve tests and tidy up
* Remove num_channels argument
* Update doc strings -> default ints not in code formatting
* Refactor image processor test mixin
- Move test_call_numpy, test_call_pytorch, test_call_pil to mixin
- Rename mixin to reflect handling of logic more than saving
- Add prepare_image_inputs, expected_image_outputs for tests
* Fix for oneformer
* Update InstructBLIP values
Note: the tests are not independent. Running the test independentely produces different logits compared to running all the integration tests
* Update test values after rescale update
* Remove left over commented out code
* Revert to previous rescaling logic
* Update rescale tests
* Fix rescaling bug
* Add tests
* Update integration tests
* Fix up
* Update src/transformers/image_transforms.py
* Update test - new possible order in list
* Initial addition of t5forsequenceclassification
* Adding imports and adding tests
* Formatting
* Running make fix-copies
* Adding mt5forseq
* Formatting
* run make fix-copies
* Adding to docs
* Add model_parallel
* Fix bug
* Fix
* Remove TODO
* Fixing tests for T5ForSequenceClassification
* Undo changes to dependency_versions_table.py
* Change classification head to work with T5Config directly
* Change seq length to let tests pass
* PR comments for formatting
* Formatting
* Initial addition of UMT5ForSequenceClassification
* Adding to inits and formatting
* run make fix-copies
* Add doc for UMT5ForSeqClass
* Update UMT5 config
* Fix docs
* Skip torch fx test for SequenceClassification
* Formatting
* Add skip to UMT5 tests as well
* Fix umt5 tests
* Running make fix-copies
* PR comments
* Fix for change to sentence_representation
* Rename seq_len to hidden_size since that's what it is
* Use base_model to follow format of the rest of the library
* Update docs
* Extract the decoder_input_ids changes and make one liner
* Make one-liner
* pull and push updates
* add docs
* fix modeling
* Add and run test
* make copies
* add task
* fix tests and fix small issues
* Checks on a Pull Request
* fix docs
* add desc pvt.md
* Resolve typo in check_repo.py
* Specify encoding when opening modeling files
* Deprecate the OpenLlama architecture
* Add disclaimer pointing to Llama
I'm open to different wordings here
* Match the capitalisation of LLaMA
* add llama
* add other readmes
* update padding id in readme
* add link to paper
* fix paths and tokenizer
* more nits
* styling
* fit operation in 2 lines when possible
* nits
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* add form
* update reademe
* update readme, we don't have a default pad token
* update test and tokenization
* LLaMA instead of Llama
* nits
* add expected text
* add greeedy output
* styling
* Update src/transformers/models/llama/modeling_llama.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* sequential device map
* skip relevant changes
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* first raw version of the bark integration
* working code on small models with single run
* add converting script from suno weights 2 hf
* many changes
* correct past_kv output
* working implementation for inference
* update the converting script according to the architecture changes
* add a working end-to-end inference code
* remove some comments and make small changes
* remove unecessary comment
* add docstrings and ensure no unecessary intermediary output during audio generation
* remove done TODOs
* make style + add config docstrings
* modification for batch inference support on the whole model
* add details to .generation_audio method
* add copyright
* convert EncodecModel from original library to transformers implementation
* add two class in order to facilitate model and sub-models loading from the hub
* add support of loading the whole model
* add BarkProcessor
* correct modeling according to processor output
* Add proper __init__ and auto support
* Add up-to-date copyright/license message
* add relative import instead of absolute
* cleaner head_dim computation
* small comment removal or changes
* more verbose LayerNorm init method
* specify eps for clearer comprehension
* more verbose variable naming in the MLP module
* remove unecessary BarkBlock parameter
* clearer code in the forward pass of the BarkBlock
* remove _initialize_modules method for cleaner code
* Remove unnecessary methods from sub-models
* move code to remove unnecessary function
* rename a variable for clarity and change an assert
* move code and change variable name for clarity
* remove unnecessary asserts
* correct small bug
* correct a comment
* change variable names for clarity
* remove asserts
* change import from absolute to relative
* correct small error due to comma missing + correct import
* Add attribute Bark config
* add first version of tests
* update attention_map
* add tie_weights and resize_token_embeddings for fineModel
* correct getting attention_mask in generate_text_semantic
* remove Bark inference trick
* leave more choices in barkProcessor
* remove _no_split_modules
* fixe error in forward of block and introduce clearer notations
* correct converting script with last changes
* make style + add draft bark.mdx
* correct BarkModelTest::test_generate_text_semantic
* add Bark in main README
* add dummy_pt_objects for Bark
* add missing models in the main init
* correct test_decoder_model_past_with_large_inputs
* disable torchscript test
* change docstring of BarkProcessor
* Add test_processor_bark
* make style
* correct copyrights
* add bark.mdx + make style, quality and consistency
* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* Remove unnecessary test method
* simply logic of a test
* Only check first ids for slow audio generation
* split full end-to-end generation tests
* remove unneccessary comment
* change submodel names for clearer naming
* remove ModuleDict from modeling_bark
* combine two if statements
* ensure that an edge misued won't happen
* modify variable name
* move code snippet to the right place (coarse instead of semantic)
* change BarkSemanticModule -> BarkSemanticModel
* align BarkProcessor with transformers paradigm
* correct BarkProcessor tests with last commit changes
* change _validate_voice_preset to an instance method instead of a class method
* tie_weights already called with post_init
* add codec_model config to configuration
* update bark modeling tests with recent BarkProcessor changes
* remove SubModelPretrainedModel + change speakers embeddings prompt type in BarkModel
* change absolute imports to relative
* remove TODO
* change docstrings
* add examples to docs and docstrings
* make style
* uses BatchFeature in BarkProcessor insteads of dict
* continue improving docstrings and docs + make style
* correct docstrings examples
* more comprehensible speaker_embeddings load/Save
* rename speaker_embeddings_dict -> speaker_embeddings
* correct bark.mdx + add bark to documentation_tests
* correct docstrings configuration_bark
* integrate last nit suggestions
* integrate BarkGeneration configs
* make style
* remove bark tests from documentation_tests.txt because timeout - tested manually
* add proper generation config initialization
* small bark.mdx documentation changes
* rename bark.mdx -> bark.md
* add torch.no_grad behind BarkModel.generate_audio()
* replace assert by ValueError in convert_suno_to_hf.py
* integrate a series of short comments from reviewer
* move SemanticLogitsProcessors and remove .detach() from Bark docs and docstrings
* actually remove SemanticLogitsProcessor from modeling_bark.oy
* BarkProcessor returns a single output instead of tuple + correct docstrings
* make style + correct bug
* add initializer_range to BarkConfig + correct slow modeling tests
* add .clone() to history_prompt.coarse_prompt to avoid modifying input array
* Making sure no extra "`" are present
* remove extra characters in modeling_bark.py
* Correct output if history_prompt is None
* remove TODOs
* remove ravel comment
* completing generation_configuration_bark.py docstrings
* change docstrings - number of audio codebooks instead of Encodec codebooks
* change 'bias' docstrings in configuration_bark.py
* format code
* rename BarkModel.generate_audio -> BarkModel.generate_speech
* modify AutoConfig instead of EncodecConfig in BarkConfig
* correct AutoConfig wrong init
* refactor BarkModel and sub-models generate_coarse, generate_fine, generate_text_semantic
* remove SemanticLogitsProcessor and replace it with SuppressTokensLogitsProcessor
* move nb_codebook related config arguments to BarkFineConfig
* rename bark.mdx -> bark.md
* correcting BarkModelConfig from_pretrained + remove keys_to_ignore
* correct bark.md with correct hub path
* correct code bug in bark.md
* correct list tokens_to_suppress
* modify Processor to load nested speaker embeddings in a safer way
* correct batch sampling in BarkFineModel.generate_fine
* Apply suggestions from code review
Small docstrings correction and code improvements
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* give more details about num_layers in docstrings
* correct indentation mistake
* correct submodelconfig order of docstring variables
* put audio models in alphabetical order in utils/check_repo.my
* remove useless line from test_modeling_bark.py
* makes BarkCoarseModelTest inherits from (ModelTesterMixin, GenerationTesterMixin, unittest.TestCase) instead of BarkSemanticModelTest
* make a Tester class for each sub-model instead of inheriting
* add test_resize_embeddings=True for Bark sub-models
* add Copied from transformers.models.gpt_neo.modeling_gpt_neo.GPTNeoSelfAttention._split_heads
* remove 'Copied fom Bark' comment
* remove unneccessary comment
* change np.min -> min in modeling_bark.py
* refactored all custom layers to have Bark prefix
* add attention_mask as an argument of generate_text_semantic
* refactor sub-models start docstrings to have more precise config class definition
* move _tied_weights_keys overriding
* add docstrings to generate_xxx in modeling_bark.py
* add loading whole BarkModel to convert_suno_to_hf
* refactor attribute and variable names
* make style convert_suno
* update bark checkpoints
* remove never entered if statement
* move bark_modeling docstrings after BarkPretrainedModel class definition
* refactor modeling_bark.py: kv -> key_values
* small nits - code refactoring and removing unecessary lines from _init_weights
* nits - replace inplace method by variable assigning
* remove *optional* when necessary
* remove some lines in generate_speech
* add default value for optional parameter
* Refactor preprocess_histories_before_coarse -> preprocess_histories
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* correct usage after refactoring
* refactor Bark's generate_xxx -> generate and modify docstrings and tests accordingly
* update docstrings python in configuration_bark.py
* add bark files in utils/documentation_test.txt
* correct docstrings python snippet
* add the ability to use parameters in the form of e.g coarse_temperature
* add semantic_max_new_tokens in python snippet in docstrings for quicker generation
* Reformate sub-models kwargs in BakModel.generate
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* correct kwargs in BarkModel.generate
* correct attention_mask kwarg in BarkModel.generate
* add tests for sub-models args in BarkModel.generate and correct BarkFineModel.test_generate_fp16
* enrich BarkModel.generate docstrings with a description of how to use the kwargs
---------
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* fix: Apostraphe splitting in the BasicTokenizer for CLIPTokenizer
* account for apostrophe at start of new word
* remove _run_split_on_punc, use re.findall instead
* remove debugging, make style and quality
* use pattern and punc splitting, repo-consistency will fail
* remove commented out debugging
* adds bool args to BasicTokenizer, remove pattern
* do_split_on_punc default True
* clean stray comments and line breaks
* rebase, repo-consistency
* update to just do punctuation split
* add unicode normalizing back
* remove redundant line
* Initial commit
* Update src/transformers/models/falcon/configuration_falcon.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/falcon/configuration_falcon.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Cleanup config docstring
* Update src/transformers/models/falcon/configuration_falcon.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Convert to relative imports
* Remove torch < 1.8 warning
* Restructure cos_sin header
* qkv -> query, key, value
* Refactor attention calculation
* Add a couple of config variables to account for the different checkpoints
* Successful merging of the code paths!
* Fix misplaced line in the non-parallel attention path
* Update config and tests
* Add a pad_token_id when testing
* Support output_attentions when alibi is None
* make fixup
* Skip KV cache shape test
* No more _keys_to_ignore_on_load_missing
* Simplify self attention a bit
* Simplify self attention a bit
* make fixup
* stash commit
* Some more attention mask updates
* Should pass all tests except assisted generation!
* Add big model generation test
* make fixup
* Add temporary workaround for test
* Test overrides for assisted generation
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update tests/models/falcon/test_modeling_falcon.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Test overrides for assisted generation
* Add generation demo
* Update copyright
* Make the docstring model actually small
* Add module-level docstring
* Remove all assertions
* Add copied from bloom
* Reformat the QKV layer
* Add copied from bloom
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Remove unused line and reformat
* No single letter variables
* Cleanup return names
* Add copied from line
* Remove the deprecated arguments blocks
* Change the embeddings test to an alibi on/off test
* Remove position_ids from FalconForQA
* Remove old check for token type IDs
* Fix the alibi path when multi_query is False
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/falcon/modeling_falcon.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/falcon/test_modeling_falcon.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update config naming
* Fix typo for new_decoder_architecture
* Add some comments
* Fix docstring
* Fix docstring
* Create range in the right dtype from the start
* Review comment cleanup
* n_head_kv -> num_kv_heads
* self.alibi -> self.use_alibi
* self.num_kv -> self.num_kv_heads
* Reorder config args
* Made alibi arguments Optional
* Add all model docstrings
* Add extra checkpoints
* Add author info for Falcon
* Stop removing token_type_ids because our checkpoints shouldn't return it anymore
* Add one hopeful comment for the future
* Fix typo
* Update tests, fix cache issue for generation
* Use -1e9 instead of -inf to avoid float overflow
* Recompute the rotary embeddings much less often
* Re-enable disabled tests
* One final fix to attention mask calculation, and update tests
* Cleanup targeting falcon-40b equivalency
* Post-rebase docs update
* Update docstrings, especially in the config
* More descriptive variable names, and comments where we can't rename them
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* hidden layers, huh, what are they good for (absolutely nothing)
* Some tests break with 1 hidden layer, use 2
* Use 1 hidden layer in a few slow models
* Use num_hidden_layers=2 everywhere
* Slightly higher tol for groupvit
* Slightly higher tol for groupvit
* Adding warning messages to BERT for missing attention masks
These warning messages when there are pad tokens within the input ids and
no attention masks are given. The warning message should only show up once.
* Adding warning messages to BERT for missing attention masks
These warning messages are shown when the pad_token_id is not None
and no attention masks are given. The warning message should only
show up once.
* Ran fix copies to copy over the changes to some of the other models
* Add logger.warning_once.cache_clear() to the test
* Shows warning when there are no attention masks and input_ids start/end with pad tokens
* Using warning_once() instead and fix indexing in input_ids check
---------
Co-authored-by: JB Lau <hckyn@voyager2.local>
* don't add space before single letter chars that don't have a merge
* fix the fix
* fixup
* add a test
* more testing
* fixup
* hack to make sure fast is also fixed
* update switch transformers test
* revert convert slow
* Update src/transformers/models/t5/tokenization_t5.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* add typechecking
* quality
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Preliminary work on some models
* Fix test load missing and make sure nonpersistent buffers are tested
* Always ignore nonpersistent buffers if in state_dict
* Treat models
* More models
* Treat remaining models
* Fix quality
* Fix tests
* Remove draft
* This test is not needed anymore
* Fix copies
* Fix last test
* Newly added models
* Fix last tests
* Address review comments
* Fix TypeError: Object of type int64 is not JSON serializable
* Convert numpy.float64 and numpy.int64 to float and int for json serialization
* Black reformatted examples/pytorch/token-classification/run_ner_no_trainer.py
* * make style
* Squash 88 commits
* Use markdown
* Remove mdx files due to bad rebase
* Fix modeling files due to bad rebase
* Fix style
* Update comment
* fix
---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* let's go!
* initial implementation of token-level timestamps
* only return a single timestamp per token
* remove token probabilities
* fix return type
* fix doc comment
* strip special tokens
* rename
* revert to not stripping special tokens
* only support models that have alignment_heads
* add integration test
* consistently name it token-level timestamps
* small DTW tweak
* initial support for ASR pipeline
* fix pipeline doc comments
* resolve token timestamps in pipeline with chunking
* change warning when no final timestamp is found
* return word-level timestamps
* fixup
* fix bug that skipped final word in each chunk
* fix failing unit tests
* merge punctuations into the words
* also return word tokens
* also return token indices
* add (failing) unit test for combine_tokens_into_words
* make combine_tokens_into_words private
* restore OpenAI's punctuation rules
* add pipeline tests
* make requested changes
* PR review changes
* fix failing pipeline test
* small stuff from PR
* only return words and their timestamps, not segments
* move alignment_heads into generation config
* forgot to set alignment_heads in pipeline tests
* tiny comment fix
* grr
* Fix saved_model_creation_extended
* Skip the BLIP model creation test for now
* Fix TF SAM test
* Fix longformer tests
* Fix Wav2Vec2
* Add a skip for XLNet
* make fixup
* make fix-copies
* Add comments
* Fix one BLIP arg not being optional, remove misspelled arg
* Remove the lxmert test overrides and just use the base test_saved_model_creation
* saved_model_creation fixes and re-enabling tests across the board
* Remove unnecessary skip
* Stop caching sinusoidal embeddings in speech_to_text
* Fix transfo_xl compilation
* Fix transfo_xl compilation
* Fix the conditionals in xglm
* Set the save spec only when building
* Clarify comment
* Move comment correctly
* Correct embeddings generation for speech2text
* Mark RAG generation tests as @slow
* Remove redundant else:
* Add comment to clarify the save_spec line in build()
* Fix size tests for XGLM at last!
* make fixup
* Remove one band_part operation
* Mark test_keras_fit as @slow
* Revert whisper change and modify the test_compile_tf_model test
* make fixup
* Tweak test slightly
* Add functional model saving to test
* Ensure TF can infer shapes for data2vec
* Add override for efficientformer
* Mark test as slow
* Stop storing references to bound methods in tf.functions
* Remove the gc.collect calls now that we resolved the underlying problem
* Remove the default signature from model.serving entirely, big cleanup
* Remove _prune_signature as self.input_signature can prune itself
* Restore serving docstring
* Update int support test to check the input signature
* Make sure other tests also use model.input_signature and not serving.input_signature
* Restore _prune_signature
* Remove the doctest GC now it's no longer needed
* Correct core tests to use the pruned sig
* order lines correctly in core tests
* Add eager_serving back with a deprecation warning
* Fix model load when it has both code on the Hub and locally
* Add input check with timeout
* Add tests
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
* Some non-saved stuff
* Add feature extractors
* Add image processor
* Add model
* Add processor and tokenizer
* Reduce timeout
---------
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
* A fun new PR where I break the entire codebase again
* A fun new PR where I break the entire codebase again
* Handle cross-attention
* Move calls to model(model.dummy_inputs) to the new build() method
* Seeing what fails with the build context thing
* make fix-copies
* Let's see what fails with new build methods
* Fix the pytorch crossload build calls
* Fix the overridden build methods in vision_text_dual_encoder
* Make sure all our build methods set self.built or call super().build(), which also sets it
* make fix-copies
* Remove finished TODO
* Tentatively remove unneeded (?) line
* Transpose b in deberta correctly and remove unused threading local
* Get rid of build_with_dummies and all it stands for
* Rollback some changes to TF-PT crossloading
* Correctly call super().build()
* Add test_backbone for convnext
* Add TimmBackbone model
* Add check for backbone type
* Tidying up - config checks
* Update convnextv2
* Tidy up
* Fix indices & clearer comment
* Exceptions for config checks
* Correclty update config for tests
* Safer imports
* Safer safer imports
* Fix where decorators go
* Update import logic and backbone tests
* More import fixes
* Fixup
* Only import all_models if torch available
* Fix kwarg updates in from_pretrained & main rebase
* Tidy up
* Add tests for AutoBackbone
* Tidy up
* Fix import error
* Fix up
* Install nattan in doc_test_job
* Revert back to setting self._out_xxx directly
* Bug fix - out_indices mapping from out_features
* Fix tests
* Dont accept output_loading_info for Timm models
* Set out_xxx and don't remap
* Use smaller checkpoint for test
* Don't remap timm indices - check out_indices based on stage names
* Skip test as it's n/a
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Cleaner imports / spelling is hard
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* fix for ragged list
* unpin numba
* make style
* np.object -> object
* propagate changes to tokenizer as well
* np.long -> "long"
* revert tokenization changes
* check with tokenization changes
* list/tuple logic
* catch numpy
* catch else case
* clean up
* up
* better check
* trigger ci
* Empty commit to trigger CI
* Add tf code for efficientformer
* Fix return dict bug - return last hidden state after last stage
* Fix corresponding return dict bug
* Override test tol
* Change default values of training to False
* Set training to default False X3
* Rm axis from ln
* Set init in dense projection
* Rm debug stuff
* Make style; all tests pass.
* Modify year to 2023
* Fix attention biases codes
* Update the shape list logic
* Add a batch norm eps config
* Remove extract comments in test files
* Add conditional attn and hidden states return for serving output
* Change channel dim checking logic
* Add exception for withteacher model in training mode
* Revert layer count for now
* Add layer count for conditional layer naming
* Transpose for conv happens only in main layer
* Make tests smaller
* Make style
* Update doc
* Rm from_pt
* Change to actual expect image class label
* Remove stray print in tests
* Update image processor test
* Remove the old serving output logic
* Make style
* Make style
* Complete test
* Rework TF type hints to use | None instead of Optional[] for tf.Tensor
* Rework TF type hints to use | None instead of Optional[] for tf.Tensor
* Don't forget the imports
* Add the imports to tests too
* make fixup
* Refactor tests that depended on get_type_hints
* Better test refactor
* Fix an old hidden bug in the test_keras_fit input creation code
* Fix for the Deit tests
* First commit
* Add auto-translation with GPT-4
* make fixup
* Add a functional layernorm for TF
* Add all the auxiliary imports etc.
* Add the extra processor and tests
* rebase to main
* Add all the needed fixes to the GPT code
* make fixup
* Make convolutions channels-last so they run on CPU
* make fixup
* Fix final issues
* Fix other models affected by test change
* Clarify comment on the sparse_prompt_embeddings check
* Refactor functional_layernorm, use shape_list in place of .shape in some places
* Remove deprecated torch-alike code
* Update tests/models/sam/test_modeling_tf_sam.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/sam/test_modeling_tf_sam.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Refactor processor with common methods and separated private methods
* make fixup
* Quietly delete the file that didn't do anything (sorry Sylvain)
* Refactor the processor tests into one file
* make fixup
* Clean up some unnecessary indirection
* Fix TF mask postprocessing
* Add more processor equivalence tests
* Refactor generate_crop_boxes to use framework-neutral np code
* Make the serving output correctly conditional
* Fix error message line length
* Use dict keys rather than indices internally in both TF and PT SAM call/forward
* Return dicts internally in the call/forward methods
* Revert changes to common tests and just override check_pt_tf_outputs
* Revert changes to other model tests
* Clarify comments for functional layernorm
* Add missing transpose from PT code
* Removed unused copied from in PT code
* Remove overrides for tests that don't exist in TF
* Fix transpose and update tests for PT and TF to check pred_masks
* Add training flag
* Update tests to use TF checkpoints
* Update index.mdx
* Add missing cross-test decorator
* Remove optional extra asterisks
* Revert return_dict changes in PT code
* Update src/transformers/models/sam/modeling_tf_sam.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Remove None return annotations on init methods
* Update tests/models/sam/test_processor_sam.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Fix input_boxes shapes
* make fixup
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* initial working additions
* clean and rename, add cond stripping initial prompt to decode
* cleanup, edit create_initial_prompt_ids, add tests
* repo consistency, flip order of conditional
* fix error, move the processor fn to the tokenizer
* repo consistency, update test ids to corresponding tokenizer
* use convert_tokens_to_ids not get_vocab...
* use actual conditional in generate
* make sytle
* initial address comments
* initial working add new params to pipeline
* first draft of sequential generation for condition_on_previous_text
* add/update tests, make compatible with timestamps
* make compatible with diff. input kwargs and max length
* add None check
* add temperature check
* flip temp check operand
* refocusing to prev pr scope
* remove the params too
* make style
* edits, move max length incorporating prompt to whisper
* address comments
* remove asr pipeline prompt decoding, fix indexing
* address comments (more tests, validate prompt)
* un-comment out tests (from debug)
* remove old comment
* address comments
* fix typo
* remove timestamp token from test
* make style
* cleanup
* copy method to fast tokenizer, set max_new_tokens for test
* prompt_ids type just pt
* address Amy's comments
* make style
* First draft of RWKV-4
* Add support for generate
* Style post-rebase
* Properly use state
* Write doc
* Fix doc
* More math
* Add model to README, dummies and clean config
* Fix init
* multiple fixes:
- fix common tests
- fix configuraion default values
- add CI test for checking state computation
- fix some CI tests
* correct tokenizer
* some tweaks
- fix config docstring
- fix failing tests
* fix CI tests
- add output_attention / output_hidden_states
- override test_initialization
- fix failing CIs
* fix conversion script
- fix sharded case
- add new arguments
* add slow tests + more fixes on conversion script
* add another test
* final fixes
* change single name variable
* add mock attention mask for pipeline to work
* correct eos token id
* fix nits
* add checkpoints
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* add `tie_word_embeddings` in docstring
* change tensor name
* fix final nits
* Trigger CI
---------
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* first draft - gives index error in question_answering.py
* maturing
* no labels
* pipeline should know about QA
* fixing checks
* formatting
* fixed docstring
* initial commit
* formatting
* adding the class to many places
* towards less unhappy checks
* nearly there
* and gpt neox for qa
* use right model
* forgot this one
* base_model_prefix is "gpt_neox" for GPTNeoX* models
* unnecessary stuff
* Update src/transformers/models/gpt_neox/modeling_gpt_neox.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* format
* Update src/transformers/models/gpt_neox/modeling_gpt_neox.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* removed gpt2 stuff
---------
Co-authored-by: Prof. Peter Schneider-Kamp <jps@ordbogen.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* first draft - gives index error in question_answering.py
* maturing
* no labels
* pipeline should know about QA
* fixing checks
* formatting
* fixed docstring
* initial commit
* formatting
* adding the class to many places
* towards less unhappy checks
* nearly there
* Update src/transformers/models/gpt_neo/modeling_gpt_neo.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* avoid error
* moving to device of star/end_logits
---------
Co-authored-by: Prof. Peter Schneider-Kamp <jps@ordbogen.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* first draft - gives index error in question_answering.py
* maturing
* no labels
* pipeline should know about QA
* fixing checks
* formatting
* fixed docstring
* make sure legacy code executes
* comment
* like this
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Co-authored-by: Prof. Peter Schneider-Kamp <jps@ordbogen.com>
Adds FocalNet by Microsoft to transformers
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Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
Co-authored-by: alaradirik <alaradirik@gmail.com>
* initial work
* Add other classes
* Refactor code
* Move warning and fix dynamic pipeline
* Issue warning when necessary
* Add test
* Do not skip auto tests
* Fix failing tests
* Refactor and address review comments
* Address review comments
