* enable graident checkpointing in DetaObjectDetection
* fix missing part in original DETA
* make style
* make fix-copies
* Revert "make fix-copies"
This reverts commit 4041c86c29248f1673e8173b677c20b5a4511358.
* remove fix-copies of DetaDecoder
* enable swin gradient checkpointing
* fix gradient checkpointing in donut_swin
* add tests for deta/swin/donut
* Revert "fix gradient checkpointing in donut_swin"
This reverts commit 1cf345e34d3cc0e09eb800d9895805b1dd9b474d.
* change supports_gradient_checkpointing pipeline to PreTrainedModel
* Revert "add tests for deta/swin/donut"
This reverts commit 6056ffbb1eddc3cb3a99e4ebb231ae3edf295f5b.
* Revert "Revert "fix gradient checkpointing in donut_swin""
This reverts commit 24e25d0a14891241de58a0d86f817d0b5d2a341f.
* Simple revert
* enable deformable detr gradient checkpointing
* add gradient in encoder
* add cuda_custom_kernel function in MSDA
* make style and fix input of DetaMSDA
* make fix-copies
* remove n_levels in input of DetaMSDA
* minor changes
* refactor custom_cuda_kernel like yoso format
0507e69d34/src/transformers/models/yoso/modeling_yoso.py (L53)
* wow I was scared!
* fix everything
* nits
* make it BC?
* add todo
* nits
* is_tracing should still be used to pass tracing tests
* nits
* some nits to make sure genration works with static cache uncompiled
* fix sdpa
* fix FA2 for both static and dynamic in a better way?
* style
* fix-copies
* fix fix copies
* fix sequential beam searcg
* style
* use `keys_to_ignore`
* nit
* correct dtype inference when init
* :( the fix for FA2 is still not optimal to investigate!
* styling
* nits
* nit
* this might work better
* add comment
* Update src/transformers/models/llama/modeling_llama.py
* "position_ids" -> "cache_position"
* style
* nit
* Remove changes that should no be propagatted just yet
* Apply suggestions from code review
* Styling
* make sure we raise an errir for static cache with FA2 enabled
* move to the bottom of the signature
* style
* Update src/transformers/models/llama/modeling_llama.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
* Update src/transformers/models/llama/modeling_llama.py
* nit in the name
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Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
* Initial commit
* Add guards for the global mesh
* Address more comments
* Move the dataloader into integrations/tpu.py
* Fix linters
* Make karg more explicitly
* Remove the move device logic
* Fix the CI
* Fix linters
* Re-enable checkpointing
* 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
* Update the processing so bbox coords are adjusted for padding
* Just pad masks
* Tidy up, add tests
* Better tests
* Fix yolos and mark as slow for pycocotols
* Fix yolos - return_tensors
* Clarify padding and normalization behaviour
* add sudachi_projection option
* Upgrade sudachipy>=0.6.8
* add a test case for sudachi_projection
* Compatible with older versions of SudachiPy
* make fixup
* make style
* error message for unidic download
* revert jumanpp test cases
* format options for sudachi_projection
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* format options for sudachi_split_mode and sudachi_dict_type
* comment
* add tests for full_tokenizer kwargs
* pass projection arg directly
* require_sudachi_projection
* make style
* revert upgrade sudachipy
* check is_sudachi_projection_available()
* revert dependency_version_table and bugfix
* style format
* simply raise ImportError
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* simply raise ImportError
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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* refactor with addedtokens decoder
* style
* get rid of lang code to id
* style
* keep some things for BC
* update tests
* add the mask token at the end of the vocab
* nits
* nits
* fix final tests
* style
* nits
* Update src/transformers/models/nllb/tokenization_nllb_fast.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* nits
* style?
* Update src/transformers/convert_slow_tokenizer.py
* make it a tad bit more custom
* ruff please stop
Co-Authored by avidale
<dale.david@mail.ru>
* Update
Co-authored-by: avidale
<dale.david@mail.ru>
* Update
Co-authored-by: avidale <dale.david@mail.ru>
* oupts
* ouft
* nites
* test
* fix the remaining failing tests
* style
* fix failing test
* ficx other test
* temp dir + test the raw init
* update test
* style
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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Convert torch_dtype as str to actual torch data type (i.e. "float16" to torch.float16)
* Check if passed torch_dtype is an attribute in torch
* Update src/transformers/pipelines/__init__.py
Check type via isinstance
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Translate README.md to German
* Add links to README_de.md
* Remove invisible characters in README
* Change to a formal tone and fix punctuation marks
* Changed max_position_embeddings default value from 2048 to 4096
* force push
* Fixed formatting issues. Fixed missing argument in write_model.
* Reverted to the default value 2048 in the Llama config. Added comments for the llama_version argument.
* Fixed issue with default value value of max_position_embeddings in docstring
* Updated help message for llama versions
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
