GitLab

Comparisons like
version.parse(torch.__version__) > version.parse("1.6")
are True for torch==1.6.0+cu101 or torch==1.6.0+cpu

version.parse(version.parse(torch.__version__).base_version) are preferred (and available in pytorch_utils.py

* Update pinned hhub version

* Make style

* support ONNX export of XDropout in deberta{,_v2}

* black

* copy to sew_d

* add test

* isort

* use pytest.mark.filterwarnings

* review comments

* Update pipeline word heuristic to work with whitespace in token offsets

This change checks for whitespace in the input string at either the
character preceding the token or in the first character of the token.
This works with tokenizers that return offsets excluding whitespace
between words or with offsets including whitespace.

fixes #18111

starting

* Use smaller model, ensure expected tokenization

* Re-run CI (please squash)

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

* improve generate docstring

* Remove 'defaults to None' comment

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

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

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

`torch.Tensor` creates an unitialized tensor (as via `torch.empty`), this leads to undeterministic behavior, poor initialization, and nans if you have unlucky init. The paper does not specify the initialization for bias terms, so I guess zero seems like a good choice - no bias initially. `torch.Tensor` is usually populated with zeros, so this fix will be close to the intended behavior:

```
>>> torch.Tensor(100, 100).sum()
tensor(0.)
>>> torch.Tensor(100, 100).sum()
tensor(nan)
>>> torch.Tensor(100, 100).sum()
tensor(0.)
```

* Added option for users to modify config parameter used by pytesseract during feature extraction

- Added optional 'tess_config' kwarg when setting up LayoutLMV2 processor that is used by pytesseract during feature extraction
- Eg. Can be used to modify psm values by setting tess_config to '--psm 7'
- Different psm values significantly influences the output of layoutlmv2

* Update src/transformers/models/layoutlmv2/feature_extraction_layoutlmv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/layoutlmv2/feature_extraction_layoutlmv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Updated variable names to be more explicit

* Fixed styles

* Added option for users to modify config parameter when calling pytesseract during feature extraction

- Added option to set "tesseract_config" parameter during LayoutLMV3 processor initialization
- Can be used to modify PSM values, eg. by setting tesseract_config="--psm 6"

* Removed  from function signature
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Rewrite push_to_hub to use upload_files

* Adapt the doc a bit

* Address review comments and clean doc

* Fix ROUGE add example check and update README

* Stay consistent in values

* add LUKE models for downstream tasks

* add new LUKE models to docs

* fix typos

* remove commented lines

* exclude None items from tuple return values

* Add balanced strategies for device_map in from_pretrained

* Add safeguards for Accelerate version

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

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

Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

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

Fix #18385
I don't know whether `use_auth_token`, `cache_dir` and `local_files_only` should be passed to `(cls.slow_tokenizer_class)._from_pretrained`, but I guess it should.

renaming it

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

* Bloom model can now be traced

* Bloom traced model can be torch scripted and serialized

* Bloom can be traced with variable keyword arguments

* Enable XLNet support

* Disable XLNet for now

* Fix some doctests
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Preliminary work on tokenizers

* Quality + fix tests

* Treat processors

* Fix pad

* Remove all uses of  in tests, docs and examples

* Replace all as_target_tokenizer

* Fix tests

* Fix quality

* Update examples/flax/image-captioning/run_image_captioning_flax.py
Co-authored-by: amyeroberts <amy@huggingface.co>

* Style
Co-authored-by: amyeroberts <amy@huggingface.co>

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

Co-authored-by: Ankur Goyal <ankur@impira.com>

* start from 1.12, torch_ccl is renamed as oneccl_bindings_for_pytorch and should import it before use
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* add doc for perf_train_cpu_many
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

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

* Add files generated using transformer-cli add-new-model-like command

* Add changes for swinv2 attention and forward method

* Add fixes

* Add modifications for weight conversion and remaining args in swin model

* Add changes for patchmerging

* Add changes for SwinV2selfattention

* Update conversion script

* Add final fixes for the swin_v2 model

* Add changes for conversion script for pretrained window size case

* Add pretrained window size value from config in SwinV2Encoder class

* Make fixup

* Add swinv2 to models_not_in_readme to utils/check_copies.py

* Modify Swinv2v2 to Swin Transformer V2

* Remove copied from, to run make fixup command

* Add updates to swinv2tf from main branch

* Add pretrained_window_size to config, to make tests pass

* Add modified weights from nandwalritik profile for swinv2

* Update model weights from swinv2 from nandwalritik profile

* Add fix for build_pr_documentation CI fix

* Add fixes for weight conversion

* Add change to make input with padding work

* Add fixes for test cases

* Add few changes from swin to swinv2 to pass test cases

* Remove tests for tensorflow as swinv2 for TF is not added yet

* Overide test_pt_tf_model_equivalence function as TF implementation for swinv2 is not added yet

* Add modeling_tf_swinv2 to _ignore_modules as test file is removed for this one right now.

* Update docs url for swinv2 in README.md
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Undo changes for check_repo

* Update url in readme.md

* Remove overrided function to test pt_tf_model_equivalence

* Remove TF model imports for Swinv2 as its not implemented in this PR

* Add changes for index.mdx

* Add swinv2 papers link,abstract and contributors details

* Rename cpb_mlp to continous_position_bias_mlp

* Add tips for swinv2 model

* Update src/transformers/models/swinv2/configuration_swinv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/swinv2/configuration_swinv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Fix indentation for docstring example in src/transformers/models/swinv2/configuration_swinv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update import order in src/transformers/models/swinv2/configuration_swinv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Add copyright statements in weights conversion script.
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Remove Swinv2 from models_not_in_readme

* Reformat code

* Remove TF implementation file for swinv2

* Update start docstring.
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Add changes for docstring

* Update orgname for weights to microsoft

* Remove to_2tuple function

* Add copied from statements wherever applicable

* Add copied from to Swinv2ForMaskedImageModelling class

* Reformat code.
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Add unittest.skip(with reason.) for test_inputs_embeds test case.
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Add updates for test_modeling_swinv2.py

* Add @unittest.skip() annotation for clarity to create_and_test_config_common_properties function

* Add continuous_position_bias_mlp parameter to conversion script

* Add test for testing masked_image_modelling for swinv2

* Update Swinv2 to Swin Transformer v2 in docs/source/en/model_doc/swinv2.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update Swinv2 to Swin Transformer v2 in docs/source/en/model_doc/swinv2.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update docs/source/en/model_doc/swinv2.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update docs/source/en/model_doc/swinv2.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Add suggested changes

* Add copied from to forward methods of Swinv2Stage and Swinv2Encoder

* Add push_to_hub flag to weight conversion script

* Change order or Swinv2DropPath class

* Add id2label mapping for imagenet 21k

* Add updated url for SwinV2 functions and classes used in implementation

* Update input_feature dimensions format, mentioned in comments.
Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com>

* Add suggested changes for modeling_swin2.py

* Update docs

* Remove create_and_test_config_common_properties function, as test_model_common_attributes is sufficient.

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

* Add changes for making Nit objects in code style

* Add suggested changes

* Add suggested changes for test_modelling_swinv2

* make fix-copies

* Update docs/source/en/model_doc/swinv2.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* fix owlvit test assertion errors

* fix gpu test error

* remove redundant lines

* fix styling

* Fix sacremoses sof dependency for Transofmers XL

* Add function to the submodule init

* Remove all uses of six

* fix quality