GitLab

* 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>

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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

* fix

* fix

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

* fix

* fix

* fix

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

* CI with layers=2

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

* Edit err message and comment in

* put back 80M comment

* Fix last models for common tests that are too big.

* Remove print statement

* Make more test models tiny

* Make more test models tiny

* More models

* More models

* First models

* Conditional DETR

* Treat DETR models, skip others

* Skip LayoutLMv2 as well

* Fix last tests

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

* 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

Revert "Fix gradient checkpointing + fp16 autocast for most models (#24247)"

This reverts commit 285a4801.

* fix gc bug

* continue PoC on OPT

* fixes

* :exploding_head:

* fix tests

* remove pytest.mark

* fixup

* forward contrib credits from discussions

* forward contrib credits from discussions

* reverting changes on untouched files.

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Co-authored-by: zhaoqf123 <zhaoqf123@users.noreply.github.com>
Co-authored-by: 7eu7d7 <7eu7d7@users.noreply.github.com>

* 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

* [automodel] fix torch_dtype=auto in from_pretrained

* add test

* fix logic

* Update src/transformers/models/auto/auto_factory.py
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>

* Test hf_hub 0.14.0rc1

* fix mocked tests

* package version

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Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>
Co-authored-by: testbot <lucainp@hf.co>

* 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

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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 !

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

* [Safetensors] Add explicit  flag to from pretrained

* add test

* remove @

* 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>

* Remove set_access_token usage + fail tests if FutureWarning

* do not fail on FutureWarning in CI

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Co-authored-by: testbot <lucainp@hf.co>

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

* add `accelerate` marker

* add to docs

* Update docs/source/en/testing.mdx

* uint8 -> bool

* fix copies

* style

* update test modeling commen when checking attention buffers

* style

* use logical not on random mask instead of subtraction with 1

* remove torch uint8

* quality

* remove modified modeling utils

* Update based on review
Co-authored-by: sgugger <sylvain.gugger@gmail.com>

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Co-authored-by: sgugger <sylvain.gugger@gmail.com>

[from_pretrained] extend `torch_dtype="auto"` to look up `config.torch_dtype` first, expand docs (#21524)

* [from_pretrained] expand on torch_dtype entry

* fold 4 into 1

* style

* support torch_dtype='config' plus tests

* style

* oops

* fold config into auto, fix bug

* fix check

* better log

* better log

* clean up

* [Variant] Make sure variant files are not incorrectly deleted

* Apply suggestions from code review

* fix

* Enforce single model initialization

* Add OneFormer example for problem 3

* Do it the Stas way

* Actually rename the uses...

* Rewrite test

* Try to change the test this way

* Fix all init slow/fast tests

* Break connection

* Fix more tests

* Fix test for initialization

* Remove custom test

* Quality

* Fix last failing tests

* The end?

begone slow tests

* Result of black 23.1

* Update target to Python 3.7

* Switch flake8 to ruff

* Configure isort

* Configure isort

* Apply isort with line limit

* Put the right black version

* adapt black in check copies

* Fix copies

* Bump onnx in /examples/research_projects/decision_transformer

Bumps [onnx](https://github.com/onnx/onnx) from 1.11.0 to 1.13.0.
- [Release notes](https://github.com/onnx/onnx/releases)
- [Changelog](https://github.com/onnx/onnx/blob/main/docs/Changelog.md)
- [Commits](https://github.com/onnx/onnx/compare/v1.11.0...v1.13.0

)

---
updated-dependencies:
- dependency-name: onnx
  dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>

* adapt

* finish

* Update examples/research_projects/decision_transformer/requirements.txt

* up

* add tests

* Apply suggestions from code review
Co-authored-by: Lucain <lucainp@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* fix test

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Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Lucain <lucainp@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* update

* update all

* clean up

* make quality

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

Fixed issue #21039 and added test for low_cpu_mem_usage

* torch.jit._state

* Fix past CI

* Fix for perceiver

* Fix REALM

* Fix for Bloom

* Fix for SwinMode

* Fix for TrajectoryTransformerModel

* Fix for test_wav2vec2_with_lm

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