* fix the function load_balancing_loss_func in Mixtral_Moe to include attention_mask
* format code using black and ruff
* skip computing mask if attention_mask=None
* add tests for load balancing loss Mixtral-Moe
* fix assert loss is different in mixtral_test
* fix pad_leng
* use assertNotAlmostEqual and print to debug
* remove print for debug
* minor updates
* reduce rtol and atol
* Enable instantiating model with pretrained backbone weights
* Update tests so backbone checkpoint isn't passed in
* Remove doc updates until changes made in modeling code
* Clarify pretrained import
* Update configs - docs and validation check
* Update src/transformers/utils/backbone_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Clarify exception message
* Update config init in tests
* Add test for when use_timm_backbone=True
* Small test updates
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* [DETA] fix freeze/unfreeze function
* Update src/transformers/models/deta/modeling_deta.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/deta/modeling_deta.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* add freeze/unfreeze test case in DETA
* fix type
* fix typo 2
* fix : enable aux and enc loss in training pipeline
* Add unsynced variables from original DETA for training
* modification for passing CI test
* make style
* make fix
* manual make fix
* change deta_modeling_test of configuration 'two_stage' default to TRUE and minor change of dist checking
* remove print
* divide configuration in DetaModel and DetaForObjectDetection
* image smaller size than 224 will give topk error
* pred_boxes and logits should be equivalent to two_stage_num_proposals
* add missing part in DetaConfig
* Update src/transformers/models/deta/modeling_deta.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* add docstring in configure and prettify TO DO part
* change distribute related code to accelerate
* Update src/transformers/models/deta/configuration_deta.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/deta/test_modeling_deta.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* protect importing accelerate
* change variable name to specific value
* wrong import
* fix aux_loss in conditional_detr
* add test aux_loss
* add aux_loss test in deta and table_transformer
* fix yolos since it doesn't have auxiliary function
* fix maskformer auxiliary_loss related code
* make style
* change param 'auxiliary_loss' to 'use_auxiliary_loss'
* change param 'auxiliary_loss' to 'use_auxiliary_loss' in tests
* make style & fix-copies, also revert yolos related parameter
* revert variable name 'use_auxiliary_loss' to 'auxiliary_loss' due to DetrConfig
* revert variable name in yolos
* revert maskformer
* add aux_loss test in maskformer
* make style
* Update src/transformers/models/yolos/configuration_yolos.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Allow non-special tokens to be added
* Add test, fix token adding code
* Revert changes to id_to_token and token_to_id
* Update the ESM tokenizer to be a bit more standardized
* Update src/transformers/models/esm/tokenization_esm.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* finalize
* make fix copies whisper
* [Tests] Make sure that we don't run tests mulitple times
* Update src/transformers/models/whisper/modeling_whisper.py
* [Tests] Make sure that we don't run tests mulitple times
* fix more
* improve
* improve
* improve further
* improve more
* improve
* fix more
* git commit and git push
* fix more
* fix more
* fix more
* New try
* Fix more whisper stuff
* Improve
* correct more
* correct more
* correct more
* Fix some tests
* Add more tests
* correct more
* correct more
* correct more
* push
* correct more
* Fix more
* Better
* without dec mask
* correct more
* clean
* save intermediate
* Fix more
* Fix VAD for large-v2
* Save new
* Correct more
* make cleaner
* correct tests
* correct src
* Finish
* Fix more
* Fix more
* finish
* Fix edge cases
* fix return_dict_in_generate
* fix all tests
* make style
* add docstrings
* add docstrings
* Fix logit processor
* make style
* fix pipeline test
* fix more style
* Apply suggestions from code review
* apply feedback Sanchit
* correct more
* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* correct more
* correct more
* correct more
* Fix staticmethod
* correct more
* fix
* fix slow tests
* make style
* fix tokenizer test
* fix tokenizer test
* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* finish
* finish
* revert kwargs change
---------
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* first commit
* correct default value non causal
* update config and modeling code
* update converting checkpoint
* clean modeling and fix tests
* make style
* add new config parameters to docstring
* fix copied from statements
* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* make position_embeddings_type docstrings clearer
* clean converting script
* remove function not used
* clean modeling file
* apply suggestion for test file + add convert script to not_doctested
* modify tests according to review - cleaner logic and more tests
* Apply nit suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* add checker of valid position embeddings type
* instantiate new layer norm layer with the right eps
* fix freeze_feature_encoder since it can be None in some cases
* add test same output in convert script
* restore wav2vec2conformer and add new model
* create processor and FE + clean
* add new model code
* fix convert script and set default config parameters
* correct model id paths
* make style
* make fix-copies and cleaning files
* fix copied from statements
* complete .md and fixe copies
* clean convert script argument defaults
* fix config parameters docstrings
* fix config docstring
* add copied from and enrich FE tests
* fix copied from and repo-consistency
* add autotokenizer
* make test input length shorter and change docstring code
* fix docstrings and copied from
* add add_adapter to ASR training example
* make testing of adapters more robust
* adapt to multi adapter layers
* refactor input_values->input_features and remove w2v2-bert feature extractor
* remove pretraining model
* remove depreciated features and useless lines
* add copied from and ignore statements to modeling tests
* remove pretraining model #2
* change import in convert script
* change default in convert script
* update readme and remove useless line
* Update tests/models/wav2vec2_bert/test_processor_wav2vec2_bert.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* refactor BERT to Bert for consistency
* remove useless ignore copy statement
* add persistent to buffer in rotary
* add eps in LayerNorm init and remove copied from
* add adapter activation parameters and add copied from statements
* Fix copied statements and add unitest.skip reasons
* add copied statement in test_processor
* refactor processor
* make style
* replace numpy random by torch rand
* remove expected output CTC
* improve converting script with processor class
* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* remove gumbel class
* remove tests related to previously deleted class
* Update src/transformers/models/wav2vec2_bert/configuration_wav2vec2_bert.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* correct typos
* remove uused parameters
* update processor to takes both text and audio
* update checkpoints
* update expected output and add ctc expected output
* add label_attention_mask
* replace pt with np in processor tests
* fix typo
* revert to behaviour with labels_attention_mask
---------
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* 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
* the fix
* where do we stand
* nits
* nits
* revert unrelated changes
* nits nits nits
* styling
* don't break llama just yet
* revert llama changes
* safe arg check
* fixup
* Add a test for T5
* Necessary changes
* Tests passing, added tokens need to not be normalized. If the added tokens are normalized, it will the stripping which seems to be unwanted for a normal functioning
* Add even more tests, when normalization is set to True (which does not work 😓 )
* Add even more tests, when normalization is set to True (which does not work 😓 )
* Update to main
* nits
* fmt
* more and more test
* comments
* revert change as tests are failing
* make the test more readble
* nits
* refactor the test
* nit
* updates
* simplify
* style
* style
* style convert slow
* Update src/transformers/convert_slow_tokenizer.py
* skip bf16 test if not supported by device
* fix
* fix bis
* use is_torch_bf16_available_on_device
* use is_torch_fp16_available_on_device
* fix & use public llama
* use 1b model
* fix flacky test
---------
Co-authored-by: Your Name <you@example.com>
* fix adding special tokens when the token is already there.
* add a test
* add a test
* nit
* fix the test: make sure the order is preserved
* Update tests/test_tokenization_common.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Fix bug in SpeechT5 speech decoder prenet's forward method
- Removed redundant `repeat` operation on speaker_embeddings in the forward method. This line was erroneously duplicating the embeddings, leading to incorrect input size for concatenation and performance issues.
- Maintained original functionality of the method, ensuring the integrity of the speech decoder prenet's forward pass remains intact.
- This change resolves a critical bug affecting the model's performance in handling speaker embeddings.
* Refactor SpeechT5 text to speech integration tests
- Updated SpeechT5ForTextToSpeechIntegrationTests to accommodate the variability in sequence lengths due to dropout in the speech decoder pre-net. This change ensures that our tests are robust against random variations in generated speech, enhancing the reliability of our test suite.
- Removed hardcoded dimensions in test assertions. Replaced with dynamic checks based on model configuration and seed settings, ensuring tests remain valid across different runs and configurations.
- Added new test cases to thoroughly validate the shapes of generated spectrograms and waveforms. These tests leverage seed settings to ensure consistent and predictable behavior in testing, addressing potential issues in speech generation and vocoder processing.
- Fixed existing test cases where incorrect assumptions about output shapes led to potential errors.
* Fix bug in SpeechT5 speech decoder prenet's forward method
- Removed redundant `repeat` operation on speaker_embeddings in the forward method. This line was erroneously duplicating the embeddings, leading to incorrect input size for concatenation and performance issues.
- Maintained original functionality of the method, ensuring the integrity of the speech decoder prenet's forward pass remains intact.
- This change resolves a critical bug affecting the model's performance in handling speaker embeddings.
* Refactor SpeechT5 text to speech integration tests
- Updated SpeechT5ForTextToSpeechIntegrationTests to accommodate the variability in sequence lengths due to dropout in the speech decoder pre-net. This change ensures that our tests are robust against random variations in generated speech, enhancing the reliability of our test suite.
- Removed hardcoded dimensions in test assertions. Replaced with dynamic checks based on model configuration and seed settings, ensuring tests remain valid across different runs and configurations.
- Added new test cases to thoroughly validate the shapes of generated spectrograms and waveforms. These tests leverage seed settings to ensure consistent and predictable behavior in testing, addressing potential issues in speech generation and vocoder processing.
- Fixed existing test cases where incorrect assumptions about output shapes led to potential errors.
* Enhance handling of speaker embeddings in SpeechT5
- Refined the generate and generate_speech functions in the SpeechT5 class to robustly handle two scenarios for speaker embeddings: matching the batch size (one embedding per sample) and one-to-many (a single embedding for all samples in the batch).
- The update includes logic to repeat the speaker embedding when a single embedding is provided for multiple samples, and a ValueError is raised for any mismatched dimensions.
- Also added corresponding test cases to validate both scenarios, ensuring complete coverage and functionality for diverse speaker embedding situations.
* Improve Test Robustness with Randomized Speaker Embeddings
* fix mismatching behavior in from_pretrained with/without accelerate
* meaningful refactor
* remove added space
* add test
* fix model on the hub
* comment
* use tiny model
* style
* added args to the pipeline
* added test
* more sensical tests
* fixup
* docs
* typo
;
* docs
* made changes to support named args
* fixed test
* docs update
* styles
* docs
* docs
* Correct the implementation of auxiliary loss of mixtrtal
* correct the implementation of auxiliary loss of mixtrtal
* Implement a simpler calculation method
---------
Co-authored-by: zhangliangxu3 <zhangliangxu3@jd.com>
* chore(phi): Updates configuration_phi with missing keys.
* chore(phi): Adds first draft of combined modeling_phi.
* fix(phi): Fixes according to latest review.
* fix(phi): Removes pad_vocab_size_multiple to prevent inconsistencies.
* fix(phi): Fixes unit and integration tests.
* fix(phi): Ensures that everything works with microsoft/phi-1 for first integration.
* fix(phi): Fixes output of docstring generation.
* fix(phi): Fixes according to latest review.
* fix(phi): Fixes according to latest review.
* fix(tests): Re-enables Phi-1.5 test.
* fix(phi): Fixes attention overflow on PhiAttention (for Phi-2).
* fix(phi): Improves how queries and keys are upcast.
* fix(phi): Small updates on latest changes.
* optionally preprocess segmentation maps for mobilevit
* changed pretrained model name to that of segmentation model
* removed voc-deeplabv3 from model archive list
* added preprocess_image and preprocess_mask methods for processing images and segmentation masks respectively
* added tests for segmentation masks based on segformer feature extractor
* use crop_size instead of size
* reverting to initial model
