* 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>
* 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 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.
* [docstring] Fix docstring for AltCLIPVisionConfig, AltCLIPTextConfig + cleaned some docstring
* Removed entries from check_docstring.py
* Removed entries from check_docstring.py
* Removed entry from check_docstring.py
* [docstring] Fix docstring for AltCLIPTextConfig, AltCLIPVisionConfig and AltCLIPConfig
* add `MaskGenerationPipeline` in docs
* Update __init__.py
* fix repo consistency and clarify docstring
* add on check docstirngs
* actually we do have a tf sam
* oops
* 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>
* remove docstrings CodeGen from objects_to_ignore
* autofix codegen docstrings
* fill in the missing types and docstrings
* fixup
* change descriptions to be in a separate line
* apply docstring suggestions from code review
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
* update n_ctx description in CodeGenConfig
---------
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
* Remove ChineseCLIPImageProcessor, ChineseCLIPTextConfig, ChineseCLIPVisionConfig from check_docstrings
* Run fix_and_overwrite for ChineseCLIPImageProcessor, ChineseCLIPTextConfig, ChineseCLIPVisionConfig
* Replace <fill_type> and <fill_docstring> in configuration_chinese_clip.py, image_processing_chinese_clip.py with type and docstring values
---------
Co-authored-by: vignesh-raghunathan <vignesh_raghunathan@intuit.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>
* Remove BertGenerationTokenizer from objects to ignore
The file BertGenerationTokenizer is removed from
objects to ignore as a first step to fix docstring.
* Docstrings fix for BertGenerationTokenizer
Docstring fix is generated for BertGenerationTokenizer
by using check_docstrings.py.
* Fix docstring for BertGenerationTokenizer
Added sep_token type and docstring in BertGenerationTokenizer.
* Remove CanineConfig from check_docstrings
* Run fix_and_overwrite for CanineConfig
* Replace <fill_type> and <fill_docstring> in configuration_canine.py with type and docstring values
---------
Co-authored-by: vignesh-raghunathan <vignesh_raghunathan@intuit.com>
* Remove UniSpeechConfig
* Remove , at the end otherwise check_docstring changes order
* Auto add new docstring
* Update docstring for UniSpeechConfig
* Remove from check_docstrings
* Remove UniSpeechSatConfig and UniSpeechSatForCTC from check_docstrings
* Remove , at the end
* Fix docstring
* Update docstring for Wav2Vec2ForCTC
* Update Wav2Vec2ForCTC docstring
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
* fix style
---------
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
* llm prompting guide
* updated code examples
* an attempt to fix the code example tests
* set seed in examples
* added a doctest comment
* added einops to the doc_test_job
* string formatting
* string formatting, again
* added the toc to slow_documentation_tests.txt
* minor list fix
* string formatting + pipe renamed
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* replaced max_length with max_new_tokens and updated the outputs to match
* minor formatting fix
* removed einops from circleci config
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <hi@lysand.re>
* removed einops and trust_remote_code parameter
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Lysandre Debut <hi@lysand.re>
* [docstring] Fix docstring for `LlamaTokenizer` and `LlamaTokenizerFast`
* [docstring] Fix docstring typo at `LlamaTokenizer` and `LlamaTokenizerFast`
* Your commit message here
* fix LlamaConfig docstring
* run make fixup
* fix formatting after review
reformat of the file to prevent script issues
* rerun make fixup after reformat
* removed donutimageprocessor from objects_to_ignore
* added docstring for donutimageprocessor
* readding donut file
* moved docstring to correct location
* 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 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>
* 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>
* 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>
* 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>
* add AutoModelForTextToSpeech class
* add TTS pipeline and tessting
* add docstrings to text_to_speech pipeline
* fix torch dependency
* corrector 'processor is None' case in Pipeline
* correct repo id
* modify text-to-speech -> text-to-audio
* remove processor
* rename text_to_speech pipelines files to text_audio
* add textToWaveform and textToSpectrogram instead of textToAudio classes
* update TTS pipeline to the bare minimum
* update tests TTS pipeline
* make style and erase useless import torch in TTS pipeline tests
* modify how to check if generate or forward in TTS pipeline
* remove unnecessary extra new lines
* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* refactor input_texts -> text_inputs
* correct docstrings of TTS.__call__
* correct the shape of generated waveform
* take care of Bark tokenizer special case
* correct run_pipeline_test TTS
* make style
* update TTS docstrings
* address Sylvain nit refactors
* make style
* refactor into one liners
* correct squeeze
* correct way to test if forward or generate
* Update output audio waveform shape
* make style
* correct import
* modify how the TTS pipeline test if a model can generate
* align shape output of TTS pipeline with consistent shape
---------
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* 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
* 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 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>
* 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>
* 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
* doc refocused on using optimum, tflite
* minor updates to fix checks
* Apply suggestions from code review
Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
* TFLite to separate page, added links
* Removed the onnx list builder
* make style
* Update docs/source/en/serialization.mdx
Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
---------
Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>
* intiial commit
* new styling
* update
* just run doctest in CI
* remove more test for fast dev
* update
* update refs
* update path and fetch upstream
* update documentatyion trests
* typo
* parse pwd
* don't check for files that are in hidden folders
* just give paths relative to transformers
* update
* update
* update
* major refactoring
* make sure options is ok
* lest test that mdx is tested
* doctest glob
* nits
* update doctest nightly
* some cleaning
* run correct test on diff
* debug
* run on a single worker
* skip_cuda_test tampkate
* updates
* add rA and continue on failure
* test options
* parse `py` codeblock?
* we don't need to replace ignore results, don't remember whyu I put it
* cleanup
* more cleaning
* fix arg
* more cleaning
* clean an todo
* more pre-processing
* doctest-module has none so extra `- ` is needed
* remove logs
* nits
* doctest-modules ....
* oups
* let's use sugar
* make dataset go quiet
* add proper timeout
* nites
* spleling timeout
* update
* properly skip tests that have CUDSA
* proper skipping
* cleaning main and get tests to run
* remove make report?
* remove tee
* some updates
* tee was removed but is the full output still available?
* [all-test]
* only our tests
* don't touch tee in this PR
* no atee-sys
* proper sub
* monkey
* only replace call
* fix sub
* nits
* nits
* fix invalid syntax
* add skip cuda doctest env variable
* make sure all packages are installed
* move file
* update check repo
* revert changes
* nit
* finish cleanup
* fix re
* findall
* update don't test init files
* ignore pycache
* `-ignore-pycache` when running pytests
* try to fix the import missmatch error
* install dec
* pytest is required as doctest_utils imports things from it
* the only log issues were dataset, ignore results should work
* more cleaning
* Update .circleci/create_circleci_config.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* [ydshieh] empty string if cuda is found
* [ydshieh] fix condition
* style
* [ydshieh] fix
* Add comment
* style
* style
* show failure
* trigger CI
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Add model to doc tests
* Remove generate and replace by prepare_inputs_for_generation
* More fixes
* Remove print statements
* Update integration tests
* Fix generate
* Remove model from auto mapping
* Use auto processor
* Fix integration tests
* Fix test
* Add inference code snippet
* Remove is_encoder_decoder
* Update docs
* Remove notebook link
