19d58d31f has introduced a context manager to manage subtests of
test_training_gradient_checkpointing. However, test body was not
moved under "with" statement. Thus, while tests are correctly
marked as skipped, test bodies were still executed. In some cases,
as with llama this caused attribute errors.
Fixes: #34722
Fixes: 19d58d31f ("Add MLLama (#33703)")
Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
* save/load sub-configs
* nit forgot these
* fix copies
* move test to common
* use dict for sub-configs
* add load-save-laod test
* clean up modeling check
* oops this are correct keys
* fix some tests, missed some composite configs
* this model was missed
* tmp commit
* tmp commit
* cull overwrites of deleted tests
* typo
* more specific docstring
* make fixup
* parameterize at the top?
* correction
* more deletions :D
* tmp commit
* for VLMs too
* fix _check_outputs
* test nit
* make fixup
* fix another flaky
* test_generate_from_inputs_embeds -- handle missing attention mask
* this worked in normal generation, needs more tests
* fix almost all tests in t5
* nit
* longt5, umt5, mt5
* style
* udop, pix2struct
* more models
* fix some tests
* fix onnx tests
* tracing tests fixed
* compile enabled and tested for t5 models
* fix small bug in slow tests
* [run-slow] t5
* uncomment
* style
* update with new generation refactoring
* nit
* fix copies
* this is the fix, had to change t5 to fix copies
* update
* [run-slow] t5
* [run-slow] t5
* update
* add test for encoder only T5
* clean up after rebase
* fix pop2piano
* add comment
* style
* fix copies after rebase
* fix copies missed this one
* first try
* codestyle
* idefics2 is happy
* [run-slow] llava, llava_next, video_llava, vipllava, llava_next_video, idefics, idefics2, kosmos2, fuyu, blip, blip_2, instructblip, instructblipvideo, paligemma
* fix-copies
* [run-slow] llava, llava_next, video_llava, vipllava, llava_next_video, idefics, idefics2, kosmos2, fuyu, blip, blip_2, instructblip, instructblipvideo
* blip-2 needs to init vision from config
* when was this removed O_o
* minor fix
* tests
* this way?
* tests
* model-agnostic code
* codestyle
* add tests for idefics
* modify general test for VLMs
* no generation test for vlm yet!
* no generation test here also
* wanr in VIT-SDPA if output attn
* add more tests
* user can pass dict as attn impl
* repo consistency
* update
* muicgen
* no prints
* forgot speech enc-dec and clip
* how many composite models we have?
* musicgen meelody is same as mudicgen
* +siglip
* fix tests + add some more
* remove idefics custom overriden code
* make idefics2 automappable
* nits
* skip tests
* doctests
* Update src/transformers/models/idefics2/configuration_idefics2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/clip/test_modeling_clip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/idefics2/test_modeling_idefics2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/idefics2/test_modeling_idefics2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/configuration_utils.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* major update, no need for automap
* clean up
* add FA2 test
* more tests
* style
* skip tests
* why did these started failing now?
* no attributes for FA2 needed
* one tiny test
* address comment about FA2 false warning
* style
* add new models and resolve conflicts
* fix copies
* let it be this way for now, come back tomorrow to review
* some more fixes
* update
* more updates
* update
* fix copies
* style and tests
* another big update
* fix tests
* fix tests
* update
* another update
* fix tests
* fix copies
* fix tests
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* add idefics
* conflicts after merging main
* enable tests but need to fix some
* fix tests
* no print
* fix/skip some slow tests
* continue not skip
* rebasing broken smth, this is the fix
* Fix Failed tests with mobile bert
* Cast to the correct dtype
* Code fixup
* Fix padding_idx larger that embedding_size
* Reduce covariance more. use 1e-7 instead of 1e-5
* Comment fix
* Reduce covariance more. use 1e-9 instead of 1e-7
* Copy new config
* all but MRA fixed
* fix mra
* very flaky
* skip instead
* make fixup
---------
Co-authored-by: Joao Gante <joao@huggingface.co>
* intilize new embeddings from normal distrib
* Fix typo in comments
* Fix typo in comments
* Fix style
* Fix variables naming
* Add tests
* Fix style
* code consistency nit
* Add deepspeed support
* Add deepspeed support
* Conver embeddings weights to float32 before computations
* Add deepspeed tests
* Cover when vocab_size is smaller than embedding_size
* Style fix
* Add tests for vocab_size smaller than hiddin_size
* Style fix
* Nits in tests
* Nits in tests
* Check for deepspeed before importing it
* Increase vocab_size for positive definite covariance matrix test
* Add warning
* Add multivariate_resizing flag and implement resizing for lm_heads
* Fix typo
* Fix wrong bias indexing
* Fix bias is zero check
* remove multivariate_resizing flag from tests
* Intialize bias from old bias normal distribution
* Fixup
* Code usability
* Use mean_resizing instead of multivariate_resizing
* Fix up
* Fix comments and docs
* add tests
* fix whisper
* update
* nit
* add qwen2-vl
* more updates!
* better this way
* fix this one
* fix more tests
* fix final tests, hope so
* fix led
* Update tests/generation/test_utils.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* pr comments
* not pass pixels and extra for low-mem tests, very flaky because of visio tower
---------
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* idefics2 enable_input_require_grads not aligned with disable_input_require_grads
make peft+idefics2 checkpoints disable fail
Signed-off-by: Wang, Yi <yi.a.wang@intel.com>
* split test case
Signed-off-by: Wang, Yi <yi.a.wang@intel.com>
* fix ci failure
Signed-off-by: Wang, Yi <yi.a.wang@intel.com>
* refine test
Signed-off-by: Wang, Yi <yi.a.wang@intel.com>
---------
Signed-off-by: Wang, Yi <yi.a.wang@intel.com>
* Add .float() in all generation methods logit outputs
* Switch float-casting of logits to training only for main models
* Add `num_logits_to_keep` in Llama and add it by default in generate
* Apply style
* Add num_logits_to_keep as arg in prepare_input_for_generation
* Add support for Mistral
* Revert models except llama and mistral
* Fix default None value in _supports_num_logits_to_keep()
* Fix dimension of dummy input
* Add exception for prophetnet in _supports_num_logits_to_keep()
* Update _supports_num_logits_to_keep() to use inspect.signature()
* Add deprecation cycle + remove modification with pretraining_tp
* Apply style
* Add most used models
* Apply style
* Make `num_logits_to_keep` an int in all cases to remove if-else clause
* Add compile check for the warning
* Fix torch versions
* style
* Add gemma2
* Update warning version
* Add comment about .float operations in generation utils
* Add tests in GenerationTesterMixin and ModelTesterMixin
* Fix batch size for assisted decoding in tests
* fix small issues in test
* refacor test
* fix slicing removing dim issue
* Add nemotron support (should fix check-copy issue in CIs)
* Trigger new CIs
* Trigger new CIs
* Bump version
* Bump version in TODO
* Trigger CIs
* remove blank space
* Trigger CIs
* add DataCollatorBatchFlattening
* Update data_collator.py
* change name
* new FA2 flow if position_ids is provided
* add comments
* minor fix
* minor fix data collator
* add test cases for models
* add test case for data collator
* remove extra code
* formating for ruff check and check_repo.py
* ruff format
ruff format tests src utils
* custom_init_isort.py
* Change resize_token_embeddings to make it return same Class that is passed to it
* Add explanatory comment as requested in review
* Add explanatory comments for add resizing function in lxmert
* Add comment for padding_idx and moving _resize_bias in lxmert to LxmertForPreTraining
---------
Co-authored-by: Prashanth Sateesh <prasatee@Prashanths-MBP.attlocal.net>
Co-authored-by: Prashanth Sateesh <prasatee@Prashanths-MacBook-Pro.local>
* Rename to test_model_common_attributes
The method name is misleading - it is testing being able to get and set embeddings, not common attributes to all models
* Explicitly skip
* Fix llama model forward function with attention=True, same-length encoded sequence.
* Fix style
* propagate fix to modeling_cohere, gemma, dbrx, and olmo (which copy the same sdpa masking logic from llama)
* Fix style
* ignore unnecessary sdpa mask converter when output_attentions=True
* add tests checking sdpa and eager outputs match when output_attentions=True
* Split if statements in two lines
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Fix formatting
* Add fix to new jetmoe model
* Add missing output_attentions argument to jetmoe mask creation
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Adding _tie_weights() to prediction heads to support low_cpu_mem_usage=True
* Testing for the non-safe-tensors case, since the default is safe-tensors already
* Running fixup/fix-copies
* Adding accelerate annotations to tests
* move scaling to nn.Module
* let the test be here for now (need to fix)
* failing tests
* last failing models
* Revert commit 4c14817f38
* clean-up
* oops forgot
* codestyle
* raise NotImplemented when possible
* Update tests/test_modeling_common.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* skip tests in respective modeling files
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Adding SDPA support for BERT
* Using the proper input name for testing model input in inference()
* Adding documentation for SDPA in BERT model page
* Use the stable link for the documentation
* Adding a gate to only call .contiguous() for torch < 2.2.0
* Additions and fixes to the documentation
* Minor updates to documentation
* Adding extra requirements needed for the contiguous() bug
* Adding "Adapted from" in plcae of the "Copied from"
* Add benchmark speedup tables to the documentation
* Minor fixes to the documentation
* Use ClapText as a replacemenet for Bert in the Copied-From
* Some more fixes for the fix-copies references
* Overriding the test_eager_matches_sdpa_generate in bert tests to not load with low_cpu_mem_usage
[test all]
* Undo changes to separate test
* Refactored SDPA self attention code for KV projections
* Change use_sdpa to attn_implementation
* Fix test_sdpa_can_dispatch_on_flash by preparing input (required for MultipleChoice models)
* feat: multidevice for resnet
* feat: yes! resnet
* fix: compare all elements in tuple
* feat: support for regnet
* feat: support for convnextv2
* feat: support for bit
* feat: support for cvt
* feat: add support for focalnet
* feat: support for yolos
* feat: support for glpn
* feat: support for imagegpt
* feat: support for levit
* feat: support for mgp_str
* feat: support for mobilnet_v1
* feat: support for mobilnet_v2
* feat: support for mobilevit
* feat: support for mobilevitv2
* feat: support for poolformer
* fix: copies
* fix: code quality check
* update: upstream changes from main
* fix: consistency check
* feat: support for sam
* feat: support for switchformer
* feat: support for swin
* feat: support for swinv2
* feat: support for timesformer
* feat: suport for trocr
* feat: support for upernet
* fix: check copies
* update: rerun CI
* update: rerun again, maybe
* update: one more rerun
---------
Co-authored-by: Jacky Lee <jackylee328@gmail.com>
* add tests for batching support
* Update src/transformers/models/fastspeech2_conformer/modeling_fastspeech2_conformer.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Update src/transformers/models/fastspeech2_conformer/modeling_fastspeech2_conformer.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* fixes and comments
* use cosine distance for conv models
* skip mra model testing
* Update tests/models/vilt/test_modeling_vilt.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* finzalize and make style
* check model type by input names
* Update tests/models/vilt/test_modeling_vilt.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* fixed batch size for all testers
* Revert "fixed batch size for all testers"
This reverts commit 525f3a0a05.
* add batch_size for all testers
* dict from model output
* do not skip layoutlm
* bring back some code from git revert
* Update tests/test_modeling_common.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/test_modeling_common.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* clean-up
* where did minus go in tolerance
* make whisper happy
* deal with consequences of losing minus
* deal with consequences of losing minus
* maskformer needs its own test for happiness
* fix more models
* tag flaky CV models from Amy's approval
* make codestyle
---------
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Revert "Add tie_weights() to LM heads and set bias in set_output_embeddings() (#28948)"
This reverts commit 725f4ad1cc.
* Revert "Patch to skip failing `test_save_load_low_cpu_mem_usage` tests (#29043)"
This reverts commit 4156f517ce.
* Add tie_weights() to LM heads and set bias in set_output_embeddings()
The bias were not tied correctly in some LM heads, and this change should fix that.
* Moving test_save_and_load_low_cpu_mem_usage to ModelTesterMixin
* Adding _tie_weights() to MPNet and Vilt
* Skip test for low cpu mem usage for Deta/DeformableDetr since they cannot init on meta device
* Rename to test name to save_load to match the convention
* test that tied output embeddings aren't initialized on load
* don't initialize the output embeddings if we're going to tie them to the input embeddings
* 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>
* Skip nn.Module.reset_parameters
* Actually skip
* Check quality
* Maybe change all inits
* Fix init issues: only modify public functions
* Add a small test for now
* Style
* test updates
* style
* nice tes
* style
* make it even faster
* one more second
* remove fx icompatible
* Update tests/test_modeling_common.py
Co-authored-by: Lysandre Debut <hi@lysand.re>
* Update tests/test_modeling_common.py
Co-authored-by: Lysandre Debut <hi@lysand.re>
* skip
* fix quality
* protect the import
---------
Co-authored-by: Lysandre Debut <hi@lysand.re>
* add sdpa
* wip
* cleaning
* add ref
* yet more cleaning
* and more :)
* wip llama
* working llama
* add output_attentions=True support
* bigcode sdpa support
* fixes
* gpt-bigcode support, require torch>=2.1.1
* add falcon support
* fix conflicts falcon
* style
* fix attention_mask definition
* remove output_attentions from attnmaskconverter
* support whisper without removing any Copied from statement
* fix mbart default to eager renaming
* fix typo in falcon
* fix is_causal in SDPA
* check is_flash_attn_2_available in the models init as well in case the model is not initialized through from_pretrained
* add warnings when falling back on the manual implementation
* precise doc
* wip replace _flash_attn_enabled by config.attn_implementation
* fix typo
* add tests
* style
* add a copy.deepcopy on the config in from_pretrained, as we do not want to modify it inplace
* obey to config.attn_implementation if a config is passed in from_pretrained
* fix is_torch_sdpa_available when torch is not installed
* remove dead code
* Update src/transformers/modeling_attn_mask_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/modeling_attn_mask_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/modeling_attn_mask_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/modeling_attn_mask_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/modeling_attn_mask_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/bart/modeling_bart.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* remove duplicate pretraining_tp code
* add dropout in llama
* precise comment on attn_mask
* add fmt: off for _unmask_unattended docstring
* precise num_masks comment
* nuke pretraining_tp in LlamaSDPAAttention following Arthur's suggestion
* cleanup modeling_utils
* backward compatibility
* fix style as requested
* style
* improve documentation
* test pass
* style
* add _unmask_unattended tests
* skip meaningless tests for idefics
* hard_check SDPA requirements when specifically requested
* standardize the use if XXX_ATTENTION_CLASSES
* fix SDPA bug with mem-efficient backend on CUDA when using fp32
* fix test
* rely on SDPA is_causal parameter to handle the causal mask in some cases
* fix FALCON_ATTENTION_CLASSES
* remove _flash_attn_2_enabled occurences
* fix test
* add OPT to the list of supported flash models
* improve test
* properly test on different SDPA backends, on different dtypes & properly handle separately the pad tokens in the test
* remove remaining _flash_attn_2_enabled occurence
* Update src/transformers/modeling_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/modeling_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/modeling_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/modeling_attn_mask_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update docs/source/en/perf_infer_gpu_one.md
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* remove use_attn_implementation
* fix docstring & slight bug
* make attn_implementation internal (_attn_implementation)
* typos
* fix tests
* deprecate use_flash_attention_2=True
* fix test
* add back llama that was removed by mistake
* fix tests
* remove _flash_attn_2_enabled occurences bis
* add check & test that passed attn_implementation is valid
* fix falcon torchscript export
* fix device of mask in tests
* add tip about torch.jit.trace and move bt doc below sdpa
* fix parameterized.expand order
* move tests from test_modeling_attn_mask_utils to test_modeling_utils as a relevant test class is already there
* update sdpaattention class with the new cache
* Update src/transformers/configuration_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/bark/modeling_bark.py
* address review comments
* WIP torch.jit.trace fix. left: test both eager & sdpa
* add test for torch.jit.trace for both eager/sdpa
* fix falcon with torch==2.0 that needs to use sdpa
* fix doc
* hopefully last fix
* fix key_value_length that has no default now in mask converter
* is it flacky?
* fix speculative decoding bug
* tests do pass
* fix following #27907
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Draft version of new KV Caching
This should allow Attention Sinks (https://github.com/tomaarsen/attention_sinks)
/ StreamingLLM (https://arxiv.org/abs/2309.17453) to be easily implemented
in a third-party or in transformers directly
* Address numerous PR suggestions
1. Move layer_idx from cache to ...Attention. Removes confusing set_layer_idx magic.
2. Always convert past_key_values to Cache instance at the start of ...Attention, removes all other isinstance calls.
3. Remove __bool__ and __getitem__ magic as they're confusing.
4. past_key_values.update(key, value, idx) now returns key, value.
5. Add use_legacy_cache flag, defaults to None, i.e. Falsey. This breaks generate for now, until 1) the cache is used is generate() or 2) use_legacy_cache is defaulted to True in generate() until we change it in another PR.
6. Separate key_cache and value_cache.
Some work is still needed to see if the SinkCache can conveniently be implemented with just one update method.
* Implement the SinkCache through backward+forward rotations
* Integrate (Sink)Cache with Llama FA2
* Set use_legacy_cache=True as default, allows for test passes
* Move from/to_legacy_cache to ...Model class
* Undo unnecessary newline change
* Remove copy utility from deprecated OpenLlama
* Match import style
* manual rebase with main
* Cache class working with generate (#1)
* Draft version of new KV Caching
This should allow Attention Sinks (https://github.com/tomaarsen/attention_sinks)
/ StreamingLLM (https://arxiv.org/abs/2309.17453) to be easily implemented
in a third-party or in transformers directly
* Address numerous PR suggestions
1. Move layer_idx from cache to ...Attention. Removes confusing set_layer_idx magic.
2. Always convert past_key_values to Cache instance at the start of ...Attention, removes all other isinstance calls.
3. Remove __bool__ and __getitem__ magic as they're confusing.
4. past_key_values.update(key, value, idx) now returns key, value.
5. Add use_legacy_cache flag, defaults to None, i.e. Falsey. This breaks generate for now, until 1) the cache is used is generate() or 2) use_legacy_cache is defaulted to True in generate() until we change it in another PR.
6. Separate key_cache and value_cache.
Some work is still needed to see if the SinkCache can conveniently be implemented with just one update method.
* Integrate (Sink)Cache with Llama FA2
* Move from/to_legacy_cache to ...Model class
* Undo unnecessary newline change
* Match import style
* working generate
* Add tests; Simplify code; Apply changes to Mistral and Persimmon
* fix rebase mess
* a few more manual fixes
* last manual fix
* propagate changes to phi
* upgrade test
* add use_legacy_cache docstring; beef up tests
* reintroduce unwanted deletes
---------
Co-authored-by: Tom Aarsen <Cubiegamedev@gmail.com>
* move import
* add default to model_kwargs.get('use_legacy_cache')
* correct failing test
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* apply PR suggestions
* fix failing test
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Tom Aarsen <37621491+tomaarsen@users.noreply.github.com>
* PR comments
* tmp commit
* add docstrings
* more tests, more docstrings, add to docs
* derp
* tmp commit
* tmp dbg
* more dbg
* fix beam search bug
* cache can be a list of tuples in some models
* fix group beam search
* all but sinkcache integration tests
* fix sink cache and add hard integration test
* now also compatible with input_embeds input
* PR comments
* add Cache support to Phi+FA2
* make fixup
---------
Co-authored-by: Joao Gante <joao@huggingface.co>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* 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>
* 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>
* 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 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 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>
* Fix GPTNeoX beam search when using parallelize
* Fix beam search idx device when using model parallel
* remove onnx related stuff
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* fix: move test_beam_search_on_multi_gpu to GenerationTesterMixin
* fix: add right item to _no_split_modules of MegaPreTrainedModel
* fix: add num_beams within parallelized beam_search test
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>
* fix
* revert cahnges and update resizing of embedding layer
* use wraning
* fixup
* more styling nits
* fix all tests that overload the embedding tests
* 👀👀 remove breakpoint
* remove useless overload + overload correctly where needed
* resize lm head with new vocab size
* reverse not necessary changes
* style
* fix CIs!
* fix last CI tests, adapt bark and Marian
* fixup
* 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
* First test
* Add info for all models
* style
* Repo consistency
* Fix last model and cleanup prints
* Repo consistency
* Use consistent function for detecting tied weights
* Fix inverted conditional in TF common test!
* Make the same change in the PT tests file
* Make sure hidden states for GPT2 have the same output shape in PT/TF
* Minor fix to PT implementation of token classification loss
* Skip loss equivalence test for TFHubert because it keeps overflowing to inf
* Compute LM loss for TF the (weird) way it's computed in PT
* Skip loss equivalence test for Wav2Vec2 for the same reason as Hubert
* Fix - don't try to access the hidden states property when output is a tuple
* Initial commit
* more stash commit
* Yet another stash commit
* yet more stash commit
* Mostly working except for docs / repo consistency
* Stop importing model list from torch file
* Add TF BLIP models to docs
* Add auto classes
* Move get_text_features and get_image_features
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip_text.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/blip/test_modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/blip/test_modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Update tests/models/blip/test_modeling_tf_blip_text.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip_text.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Use channels_last convolutions in TF (better performance + compatibility)
* Remove _shape function
* Move multi-line statement to one line in PT + TF
* Specify tf.keras.layers instead of importing from it
* Remove test_gradient_checkpointing and empty test_training methods
* move some multi-line statements to one line
* Update docstring for generate
* Remove pruned heads set
* Remove self.seq_len_dim
* Fixed issues with loss computation, should resolve some tests. Also ensured that the PT version follows the config for output_attentions and output_hidden_states
* ensure original model follows config in more cases
* Skip the same cross-attention tests in the PT tests - didn't realize we did it twice!
* Add training args throughout the models and layers
* make fixup
* Fix docstring for inputs_embeds
* Add docstring for is_decoder
* Add docstrings to text models
* Remove redundant computation
* Add unpack_inputs / keras_serializable
* Add modeling_tf_blip to doctests
* Add config classes for keras serialization
* Changes to allow model porting with pt-to-tf
* Quick fix to decoder head and test tweaks
* Revert an issue with masking the embeddings outputs
* Allow missing keys in some equivalence tests (for unused layers)
* Add tf-pt equivalence tests back in
* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip_text.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/blip/modeling_tf_blip_text.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* make fixup
* Refactor invert_attention_mask out into tf_utils
* Re-enable cross-tests on the PT side too
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Making sure we can use safetensors to serialize all the time.
* Expanding the tests for increased coverage.
* Update the test.
* Getting current state of affairs.
* Tentative fix.
* Fixing black version.
* Fixing the worst offenders.
* Try to modify less files.
* Fixing blip_2 (Weird solution right now).
* Fixing deta.
* Fix blip ?
* Missing extra newline.
* No deta modification.
* Adding some comments.
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Addressing comments.
* Addressing comments.
* creating warn_once.
* Warning_once !
---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
