GitLab

* [deepspeed zero3] need generate(synced_gpus=True, ...)

* fix

* rework per Sylvain's suggestion

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

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Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* check what tests fail

* Skip failing tests

* Skip failing tests

* Skip failing tests

* Skip failing tests

* clean up

* clean up

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Chunkable classification pipeline 

The TokenClassificationPipeline is now able to process sequences longer than 512. No matter the framework, the model, the tokenizer. We just have to pass process_all=True and a stride number (optional). The behavior remains the same if you don't pass these optional parameters. For overlapping parts when using stride above 0, we consider only the max scores for each overlapped token in all chunks where the token is.

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* update with latest black format

* update black format

* Update token_classification.py

* Update token_classification.py

* format correction

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update comments

* Update src/transformers/pipelines/token_classification.py
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* Update token_classification.py

Correct spaces, remove process_all and keep only stride. If stride is provided, the pipeline is applied to the whole text.

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update chunk aggregation

Update the chunk aggregation strategy based on entities aggregation.

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

Remove unnecessary pop from outputs dict

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update token_classification.py

* Update src/transformers/pipelines/token_classification.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* add chunking tests

* correct formating

* correct formatting

* correct model id for test chunking

* update scores with nested simplify

* Update test_pipelines_token_classification.py

* Update test_pipelines_token_classification.py

* update model to a tiny one

* Update test_pipelines_token_classification.py

* Adding smaller test for chunking.

* Fixup

* Update token_classification.py

* Update src/transformers/pipelines/token_classification.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/pipelines/token_classification.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

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Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Resolve incorrect type typo in trainer methods

* v1 all keys match

* clean up

* forward pass ok

* add correct image transform

* generate works, logits matching

* clean up

* more refactor

* revert

* revert

* clean up

* clean ups

* clean up

* refactor

* refactor

* fix doc

* fix tokenizer test

* fix toctree

* revert toctree

* oops

* few fixes

* replace to `pixel_embeds`

* make fixup

* test processing & feat extractor

* fix some tests

* more fixes

* make fixup

* clean up

* more clean up

* add a single slow test

* fix test

* make fixup

* fix

* fix authors

* fix toctree

* update docs

* add docstring

* revert change

* Update src/transformers/models/pix2struct/__init__.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix tokenizer

* fix processor test

* fix test

* make fixup

* refactor

* fix config

* Update src/transformers/models/pix2struct/image_processing_pix2struct.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* format

* fix

* Update src/transformers/models/pix2struct/image_processing_pix2struct.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* make fixup

* add docstring

* fix issues

* fix

* fix

* fix

* add slow test

* fix

* fix

* fix batched issue

* fix training issues

* fix ci test

* fix slow test

* fix conversion script

* remove unneeded classes

* fix slow test

* fix require backends

* fix masked fill

* revert

* fix softmax

* add large models support

* fix conditional generation

* few fixes

* add instructions

* rm unneeded file

* Update src/transformers/models/pix2struct/convert_pix2struct_original_pytorch_to_hf.py

* fix ci test

* fix ci test really

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* fix nit

* fix nits

* fix image processors nits

* docstring

* clean up

* fix nit

* fix tests

* docstring nit

* fix reshape

* Update src/transformers/models/pix2struct/image_processing_pix2struct.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* fix nit

* fix repetition

* refactor processor

* make patch size consistent

* refactor forward

* fix docstring

* fix max_patches issue

* update docstirng

* update docstring

* fix coped from

* add skip reasons

* few fixes

* Update src/transformers/models/pix2struct/image_processing_pix2struct.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* format

* fix doctests

* refactor and fix

* fix doc build issue

* fix processor test

* small fix conversion script

* replace correct weights

* make fixup

* fix some issues

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* revert config and fixes

* Update src/transformers/models/pix2struct/image_processing_pix2struct.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* more details

* fixes

* fix processor

* fix processor test

* fix

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* make fixup

* fix processor

* Update src/transformers/models/pix2struct/modeling_pix2struct.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* add copied

* make fixup

* fix copies

* update docstring

* refactor

* fix docstring

* fix conversion script

* fix vqa issue

* replace to `flattened_patches`

* nit

* fix numpy issue

* fix image processors

* add batched vqa support

* fix vqa conversion

* make fixup

* fix conversion script

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* make fixup

* add correct docstring

* update docstring

* fix module level + channel dim

* use `make_list_of_images`

* refactor

* correct docstring

* fix authors

* remove `data_format`

* add header text test

* Apply suggestions from code review
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* make fixup

* add checkpoints

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* tmp commit

* beef up llama tests

* Export TF generate with a TF tokenizer

* remove unused lines

Enforce  for device_map strategies

Fixed bug to calculate correct xpath_sub_list in MarkupLMTokenizer. Earlier xpath_sub_list was same as xpath_tags_list
Co-authored-by: dusejat <dusejat@amazon.com>

* Revert "[GPT-J] add deprecation warning (#21869)"

This reverts commit fb76994c.

* Fix position embeddings for GPT-J and CodeGen

* Address review comments from @gante

* Fix "Copied from" comment referencing wrong function

* Fix copy/paste mistake

* Fix training path

* Hopefully make torch.fx happy

* Move position_ids long cast

* Revert "Hopefully make torch.fx happy"

This reverts commit e41a6f4cad3ff441124c7457b19cfb630d4ca025.

* Changes to help with torch.fx tracing

* Linter fix

* Correct position_ids tensor type hint

* Work-around torch.fx tracing issue

* Get the changes to work with torch.fx

* Address review comment from @michaelbenayoun

* Another small adjustment

* Add explanatory comment; small code tidyup

allow only test_file in pytorch and flax summarization

* add low_cpu_mem_usage option in run_clm.py example which will benefit LLM loading
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* update all the example and README under language-modeling
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

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Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* Add MaskedImageModelingOutput

* update

* update

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* [deepspeed] offload + non-cpuadam optimizer exception doc

* deps

* time to say goodbye, torch 1.7 and 1.8

* clean up torch_int_div

* clean up is_torch_less_than_1_8-9

* update

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

Add translation

* fix more doctests

* fix style

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* all doctests

* Skip failed tests

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Make sure CVT can be trained using mixed precision

* Add test for keras-fit with mixed-precision

* Update tests/models/cvt/test_modeling_tf_cvt.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

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Co-authored-by: gcuder <Gerald.Cuder@iacapps.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* Fixed modules_to_not_convert default value

* Fixed modules_to_not_convert docstring

* Update src/transformers/utils/bitsandbytes.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/utils/bitsandbytes.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* ["lm_head"] if modules_to_not_convert is None

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Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Add bool_masked_pos to forward docstrings

* Add note about mask ratio - videomae

* Fix up

* Fix indenting

* added an example of pad_to_multiple_of

* make style

* addressed feedback

Move torch.compile() wrapping after DDP/FSDP wrapping to ensure correct graph breaks during training (#22279)

* Proper map location for optimizer load

* What happened to my code?

* Update LLaMA conversion script

* Doc

* Fix the weight size for the 13B checkpoint

* Update src/transformers/models/llama/convert_llama_weights_to_hf.py
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>

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Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>

fix grad ckpt bug of llama

Update training_args.py

* added translated files

added perf_train_cpu and perf_train_cpu_many

* updated toctree

* updated toctree

* added file

perf_infer_cpu.medx

* italian translation perf_infer_cpu.mdx

[Docs] fix typos
Co-authored-by: yesinkim <yesinkim@yesinkimui-MacBookAir.local>

Update training_args.py

A nightly install is not required anymore for `torch.compile`.

[trainer] param count for zero3

push

Revert "Use `dash==2.8.1` for now for daily CI (#22227)"

This reverts commit 53218671.

* Add kernel size to NATTEN's QK arguments.

The new NATTEN 0.14.5 supports PyTorch 2.0, but also adds an additional
argument to the QK operation to allow optional RPBs.

This ends up failing NATTEN tests.

This commit adds NATTEN back to circleci and adds the arguments to get
it working again.

* Force NATTEN >= 0.14.5