GitLab

poolformer onnx
Co-authored-by: syed <syed.abdul@sandlogic.com>

* fix typo `onnx`

* fix test

* rembert onnx config

* formatting
Co-authored-by: Ho <erincho@bcd0745f972b.ant.amazon.com>

* Use tiny ONNX models

* Fix broken tests

* Add tiny perceiver

* Add tiny convbert

* add model files etc for MobileNetV2

rename files for MobileNetV1

initial implementation of MobileNetV1

fix conversion script

cleanup

write docs

tweaks

fix conversion script

extract hidden states

fix test cases

make fixup

fixup it all

remove main from doc link

fixes

fix tests

fix up

use google org

fix weird assert

* fixup

* use google organization for checkpoints

* add model files etc for MobileNetV2

* rename files for MobileNetV1

* initial implementation of MobileNetV1

* fix conversion script

* cleanup

* write docs

* tweaks

* fix conversion script

* extract hidden states

* fix test cases

* make fixup

* fixup it all

* rename V1 to V2

* fix checkpoints

* fixup

* implement first block + weight conversion

* add remaining layers

* add output stride and dilation

* fixup

* add tests

* add deeplabv3+ head

* a bit of fixup

* finish deeplab conversion

* add link to doc

* fix issue with JIT trace

in_height and in_width would be Tensor objects during JIT trace, which caused Core ML conversion to fail on the remainder op. By making them ints, the result of the padding calculation becomes a constant value.

* cleanup

* fix order of models

* fix rebase error

* remove main from doc link

* add image processor

* remove old feature extractor

* fix converter + other issues

* fixup

* fix unit test

* add to onnx tests (but these appear broken now)

* add post_process_semantic_segmentation

* use google org

* remove unused imports

* move args

* replace weird assert

* Added onnx config whisper

* added whisper support onnx

* add audio input data

* added whisper support onnx

* fixed the seqlength value

* Updated the whisper onnx ocnfig

* restore files to old version

* removed attention mask from inputs

* Updated get_dummy_input_onnxruntime docstring

* Updated relative imports and token generation

* update docstring

* add Onnx Config for ImageGPT

* add generate_dummy_inputs for onnx config

* add TYPE_CHECKING clause

* Update doc for generate_dummy_inputs
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Add onnx support for VisionEncoderDecoder

* Add onnx support for VisionEncoderDecoder

* Removed unused import

* Rename encoder hidden state
Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* Update docstrings and removed redundant code

* Added test function for enc-dec models

* Update doc string text
Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* fixed code style
Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* validate onnx models with a different input geometry than saved with

* only test working features for now

* simpler test skipping

* rm TODO

* expose batch_size/seq_length on vit

* skip certain name, feature, framework parameterizations known to fail validation

* Trigger CI

* Trigger CI

* swin transformer onnx support

* Updated image dimensions as dynamic
Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>
Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* Add ONNX support

* Make height and width dynamic axes
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

* groupvit to onnx

* dynamic shape for pixel values dim

* onnx conversion for owlvit

* .T to .t()

* dynamic shapes for pixel values

* Implement ONNX support for Longformer

Fix repo consistency check complaints

Fix value mismatches

Add pooler output for default model

Increase validation atol to accommodate multiple-choice error

Fix copies

Fix chunking for longer sequence lengths

Add future comment

* Fix issue in mask_invalid_locations

* Remove torch imports in configuration_longformer

* Change config access to fix LED

* Push opset version to support tril

* Work in review comments (mostly style)

* Add Longformer to ONNX tests

Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Update BLOOM parameter counts

* Update BLOOM parameter counts

* onnx config for clip

* default opset as 14

* changes from the original repo

* input values order fix

* outputs fix

* remove unused import

* ran make fix-copies

* black format

* review comments: forward ref, import fix, model change revert, .to cleanup

* make style

* formatting fixes

* revert groupvit

* comment for cast to int32

* comment fix

* make .T as .t() for onnx conversion

* ran make fix-copies

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

* fix copies

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

* update features

* MT5OnnxConfig added with updated with tests and docs

* fix imports

* fix onnc_config_cls for mt5

Co-authored-by: Thomas Chaigneau <thomas.deeptools.ai>

* feat: add the data2vec conf that are missing https://huggingface.co/docs/transformers/serialization

* fix: wrong config

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

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

* black

* copy to sew_d

* add test

* isort

* use pytest.mark.filterwarnings

* review comments

Co-authored-by: Guilhem Chéron <guilhemc@authentifier.com>

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

* add onnx support for BLOOM

* use TYPE_CHECKING for type annotations

* fix past_shape for bloom (different from gpt2)

* use logical_or instead of `+` for onnx support

* bigger `atol_for_validation` for larger bloom models

* copied -> taken because it's no longer an exact copy

* remove "copied from" comment
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Add ONNX support for LayoutLMv3

* Update docstrings

* Update empty description in docstring

* Fix imports and type hints

* add onnx support for debertav2

* debertav2 -> deberta-v2 in onnx features file

* remove causal lm

* add deberta-v2-xlarge to onnx tests

* use self.type().dtype() in xsoftmax
Co-authored-by: Jingya HUANG <44135271+JingyaHuang@users.noreply.github.com>

* remove hack for deberta

* remove unused imports

* Update src/transformers/models/deberta_v2/configuration_deberta_v2.py
Co-authored-by: Jingya HUANG <44135271+JingyaHuang@users.noreply.github.com>

* use generate dummy inputs

* linter

* add imports

* add support for deberta v1 as well

* deberta does not support multiple choice

* Update src/transformers/models/deberta/configuration_deberta.py
Co-authored-by: Jingya HUANG <44135271+JingyaHuang@users.noreply.github.com>

* Update src/transformers/models/deberta_v2/configuration_deberta_v2.py
Co-authored-by: Jingya HUANG <44135271+JingyaHuang@users.noreply.github.com>

* one line ordered dict

* fire build
Co-authored-by: Jingya HUANG <44135271+JingyaHuang@users.noreply.github.com>

* Initial commit

* Make some fixes

* Make PT model full forward pass

* Drop TF & Flax implementation, fix copies etc

* Add Flax model and update some corresponding stuff

* Drop some TF things

* Update config and flax local attn

* Add encoder_attention_type to config

* .

* Update docs

* Do some cleansing

* Fix some issues -> make style; add some docs

* Fix position_bias + mask addition + Update tests

* Fix repo consistency

* Fix model consistency by removing flax operation over attn_mask

* [WIP] Add PT TGlobal LongT5

* .

* [WIP] Add flax tglobal model

* [WIP] Update flax model to use the right attention type in the encoder

* Fix flax tglobal model forward pass

* Make the use of global_relative_attention_bias

* Add test suites for TGlobal model

* Fix minor bugs, clean code

* Fix pt-flax equivalence though not convinced with correctness

* Fix LocalAttn implementation to match the original impl. + update READMEs

* Few updates

* Update: [Flax] improve large model init and loading #16148

* Add ckpt conversion script accoring to #16853 + handle torch device placement

* Minor updates to conversion script.

* Typo: AutoModelForSeq2SeqLM -> FlaxAutoModelForSeq2SeqLM

* gpu support + dtype fix

* Apply some suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* * Remove (de)parallelize stuff
* Edit shape comments
* Update README.md
* make fix-copies

* Remove caching logic for local & tglobal attention

* Apply another batch of suggestions from code review

* Add missing checkpoints
* Format converting scripts
* Drop (de)parallelize links from longT5 mdx

* Fix converting script + revert config file change

* Revert "Remove caching logic for local & tglobal attention"

This reverts commit 2a619828f6ddc3e65bd9bb1725a12b77fa883a46.

* Stash caching logic in Flax model

* Make side relative bias used always

* Drop caching logic in PT model

* Return side bias as it was

* Drop all remaining model parallel logic

* Remove clamp statements

* Move test files to the proper place

* Update docs with new version of hf-doc-builder

* Fix test imports

* Make some minor improvements

* Add missing checkpoints to docs
* Make TGlobal model compatible with torch.onnx.export
* Replace some np.ndarray with jnp.ndarray

* Fix TGlobal for ONNX conversion + update docs

* fix _make_global_fixed_block_ids and masked neg  value

* update flax model

* style and quality

* fix imports

* remove load_tf_weights_in_longt5 from init and fix copies

* add slow test for TGlobal model

* typo fix

* Drop obsolete is_parallelizable and one warning

* Update __init__ files to fix repo-consistency

* fix pipeline test

* Fix some device placements

* [wip]: Update tests -- need to generate summaries to update expected_summary

* Fix quality

* Update LongT5 model card

* Update (slow) summarization tests

* make style

* rename checkpoitns

* finish

* fix flax tests
Co-authored-by: phungvanduy <pvduy23@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: patil-suraj <surajp815@gmail.com>

* Add ONNX support for ResNet

* Add ONNX test

* make fix-copies

* Start adding perceiver support for ONNX

* Fix pad token bug for fast tokenizers

* Fix formatting

* Make get_preprocesor more opinionated (processor priority, otherwise tokenizer/feature extractor)

* Clean docs format

* Minor cleanup following @sgugger's comments

* Fix typo in docs

* Fix another docs typo

* Fix one more typo in docs

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

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

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

* add onnx config for SqueezeBert

* add test for onnx config for SqueezeBert

* add automatically updated doc for onnx config for SqueezeBert

* Update src/transformers/onnx/features.py
Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* Update src/transformers/models/squeezebert/configuration_squeezebert.py
Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>
Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* Add onnx configuration for xlm

* Add supported features for xlm

* Add xlm to models exportable with onnx

* Add xlm architecture to test file

* Modify docs

* Make code quality fixes

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* Black preview

* Fixup too!

* Fix check copies

* Use the same version as the CI

* Bump black

* update docs of length_penalty

* Revert "update docs of length_penalty"

This reverts commit 466bf4800b75ec29bd2ff75bad8e8973bd98d01c.

* add mobilebert onnx config

* address suggestions

* Update auto.mdx

* Update __init__.py

* Update features.py