GitLab

* Check for use_sagemaker_dp

* Add a check for is_sagemaker_mp when setting _n_gpu again. Should be last broken thing

* Try explicit check?

* Quality

Fix the regex in `get_imports` to support multiline try blocks and excepts with specific exception types (#23725)

* fix and test get_imports for multiline try blocks, and excepts with specific errors

* fixup

* add some more tests

* add license

* Let's try autodetecting serving sigs

* Don't clobber existing sigs

* Change shapes for multiplechoice models

* Make default dummy inputs smarter too

* Fix missing f-string

* Let's YOLO a serving output too

* Read __class__.__name__ properly

* Don't just pass naked lists in there and expect it to be okay

* Code cleanup

* Update default serving sig

* Clearer error messages

* Further updates to the default serving output

* make fixup

* Update the serving output a bit more

* Cleanups and renames, raise errors appropriately when we can't infer inputs

* More renames

* we're building in a functional context again, yolo

* import DUMMY_INPUTS from the right place

* import DUMMY_INPUTS from the right place

* Support cross-attention in the dummies

* Support cross-attention in the dummies

* Complete removal of dummy/serving overrides in BERT

* Complete removal of dummy/serving overrides in RoBERTa

* Obliterate lots and lots of serving sig and dummy overrides

* merge type hint changes

* Fix for token_type_ids with vocab_size 1

* Add missing property decorator

* Fix T5 and hopefully some models that take conv inputs

* More signature pruning

* Fix T5's signature

* Fix Wav2Vec2 signature

* Fix LongformerForMultipleChoice input signature

* Fix BLIP and LED

* Better default serving output error handling

* Fix BART dummies

* Fix dummies for cross-attention, esp encoder-decoder models

* Fix visionencoderdecoder signature

* Fix BLIP serving output

* Small tweak to BART dummies

* Cleanup the ugly parameter inspection line that I used in a few places

* committed a breakpoint again

* Move the text_dims check

* Remove blip_text serving_output

* Add decoder_input_ids to the default input sig

* Remove all the manual overrides for encoder-decoder model signatures

* Tweak longformer/led input sigs

* Tweak default serving output

* output.keys() -> output

* make fixup

move text_prompt_ids trimming to top

* Extremely small change to TF SAM dummies to reduce memory usage on build

* remove debug breakpoint

* Debug print statement to track array sizes

* More debug shape printing

* More debug shape printing

* Now remove the debug shape printing

* make fixup

* make fixup

* Rework TF type hints to use | None instead of Optional[] for tf.Tensor

* Rework TF type hints to use | None instead of Optional[] for tf.Tensor

* Don't forget the imports

* Add the imports to tests too

* make fixup

* Refactor tests that depended on get_type_hints

* Better test refactor

* Fix an old hidden bug in the test_keras_fit input creation code

* Fix for the Deit tests

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

fix: use bool instead of uint8/byte in Deberta/DebertaV2/SEW-D to make it compatible with TensorRT (#23683)

* Use bool instead of uint8/byte in DebertaV2 to make it compatible with TensorRT

TensorRT cannot accept onnx graph with uint8/byte intermediate tensors. This PR uses bool tensors instead of unit8/byte tensors to make the exported onnx file can work with TensorRT.

* fix: use bool instead of uint8/byte in Deberta and SEW-D

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Co-authored-by: Yuxian Qiu <yuxianq@nvidia.com>

* Added lion and paged optimizers and made original tests pass.

* Added tests for paged and lion optimizers.

* Added and fixed optimizer tests.

* Style and quality checks.

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Co-authored-by: younesbelkada <younesbelkada@gmail.com>

* Added lion and paged optimizers and made original tests pass.

* Added tests for paged and lion optimizers.

* Added and fixed optimizer tests.

* Style and quality checks.

* Initial draft. Some tests fail.

* Fixed dtype bug.

* Fixed bug caused by torch_dtype='auto'.

* All test green for 8-bit and 4-bit layers.

* Added fix for fp32 layer norms and bf16 compute in LLaMA.

* Initial draft. Some tests fail.

* Fixed dtype bug.

* Fixed bug caused by torch_dtype='auto'.

* All test green for 8-bit and 4-bit layers.

* Added lion and paged optimizers and made original tests pass.

* Added tests for paged and lion optimizers.

* Added and fixed optimizer tests.

* Style and quality checks.

* Fixing issues for PR #23479.

* Added fix for fp32 layer norms and bf16 compute in LLaMA.

* Reverted variable name change.

* Initial draft. Some tests fail.

* Fixed dtype bug.

* Fixed bug caused by torch_dtype='auto'.

* All test green for 8-bit and 4-bit layers.

* Added lion and paged optimizers and made original tests pass.

* Added tests for paged and lion optimizers.

* Added and fixed optimizer tests.

* Style and quality checks.

* Added missing tests.

* Fixup changes.

* Added fixup changes.

* Missed some variables to rename.

* revert trainer tests

* revert test trainer

* another revert

* fix tests and safety checkers

* protect import

* simplify a bit

* Update src/transformers/trainer.py

* few fixes

* add warning

* replace with `load_in_kbit = load_in_4bit or load_in_8bit`

* fix test

* fix tests

* this time fix tests

* safety checker

* add docs

* revert torch_dtype

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

* multiple fixes

* update docs

* version checks and multiple fixes

* replace `is_loaded_in_kbit`

* replace `load_in_kbit`

* change methods names

* better checks

* oops

* oops

* address final comments

---------
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fix some docs what layerdrop does

* Update src/transformers/models/data2vec/configuration_data2vec_audio.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fix more docs

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

Ref: https://github.com/huggingface/peft/issues/394
    Loading a quantized checkpoint into non-quantized Linear8bitLt is not supported.
    call module.cuda() before module.load_state_dict()

* Fix is_batched code to allow 2-D numpy arrays for audio

* Tests

* Fix typo

* Incorporate comments from PR #23223

fix blip doctest

* New TF version compatibility fixes

* Remove dummy print statement, move expand_1d

* Make a proper framework inference function

* Make a proper framework inference function

* ValueError -> TypeError

* add a dummy pipeline test

* change test name

* Update modeling_open_llama.py

Fix typo in `use_memorry_efficient_attention` parameter name

* Update configuration_open_llama.py

Fix typo in `use_memorry_efficient_attention` parameter name

* Update configuration_open_llama.py

Take care of backwards compatibility ensuring that the previous parameter name is taken into account if used

* Update configuration_open_llama.py

format to adjust the line length

* Update configuration_open_llama.py

proper code formatting using `make fixup`

* Update configuration_open_llama.py

pop the argument not to let it be set later down the line

* Add PerSAM args

* Make attn_sim optional

* Rename to attention_similarity

* Add docstrigns

* Improve docstrings

* First draft

* Remove print statements

* Add conditional generation

* Add more tests

* Remove scripts

* Remove BLIP specific linkes

* Add support for pix2struct

* Add fast test

* Address comment

* Fix style

* Fix wav2vec2 is_batched check to include 2-D numpy arrays

* address comment

* Add tests

* oops

* oops

* Switch to np array
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* Switch to np array

* condition merge

* Specify mono channel only in comment

* oops, add other comment too

* make style

* Switch list check from falsiness to empty

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Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* Fixed bug where LLaMA layer norm would change input type.

* make fix-copies

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Co-authored-by: younesbelkada <younesbelkada@gmail.com>

* Fix deepspeed recursion

* Better fix

* Fix tensor device while attention_mask is not None

* Fix tensor device while attention_mask is not None

* Debug example code for MegaForCausalLM

set ignore_mismatched_sizes=True in model loading code

* Fix up

* remove redundant shit right

* fix failing tests

* this time fix tests

* Fix: Change tensors to integers in torch.split() for torch.dynamo and torch.compile compatibility

* Applied the suggested fix to the utils/check_copies.py test

* Applied the suggested fix by changing the original function that gets copied

* Fix sagemaker/distributed state

* Fix correctly

* Bring back -1

* Bring back local rank for distributed check

* better version

* Cleanest option

Use config to set name and descriptiob if not present

* rwkv fix for 8bit inference

* add comment

* First commit

* Add auto-translation with GPT-4

* make fixup

* Add a functional layernorm for TF

* Add all the auxiliary imports etc.

* Add the extra processor and tests

* rebase to main

* Add all the needed fixes to the GPT code

* make fixup

* Make convolutions channels-last so they run on CPU

* make fixup

* Fix final issues

* Fix other models affected by test change

* Clarify comment on the sparse_prompt_embeddings check

* Refactor functional_layernorm, use shape_list in place of .shape in some places

* Remove deprecated torch-alike code

* Update tests/models/sam/test_modeling_tf_sam.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update tests/models/sam/test_modeling_tf_sam.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Refactor processor with common methods and separated private methods

* make fixup

* Quietly delete the file that didn't do anything (sorry Sylvain)

* Refactor the processor tests into one file

* make fixup

* Clean up some unnecessary indirection

* Fix TF mask postprocessing

* Add more processor equivalence tests

* Refactor generate_crop_boxes to use framework-neutral np code

* Make the serving output correctly conditional

* Fix error message line length

* Use dict keys rather than indices internally in both TF and PT SAM call/forward

* Return dicts internally in the call/forward methods

* Revert changes to common tests and just override check_pt_tf_outputs

* Revert changes to other model tests

* Clarify comments for functional layernorm

* Add missing transpose from PT code

* Removed unused copied from in PT code

* Remove overrides for tests that don't exist in TF

* Fix transpose and update tests for PT and TF to check pred_masks

* Add training flag

* Update tests to use TF checkpoints

* Update index.mdx

* Add missing cross-test decorator

* Remove optional extra asterisks

* Revert return_dict changes in PT code

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

* Remove None return annotations on init methods

* Update tests/models/sam/test_processor_sam.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Fix input_boxes shapes

* make fixup

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

Patched the optimizers

* initial working additions

* clean and rename, add cond stripping initial prompt to decode

* cleanup, edit create_initial_prompt_ids, add tests

* repo consistency, flip order of conditional

* fix error, move the processor fn to the tokenizer

* repo consistency, update test ids to corresponding tokenizer

* use convert_tokens_to_ids not get_vocab...

* use actual conditional in generate

* make sytle

* initial address comments

* initial working add new params to pipeline

* first draft of sequential generation for condition_on_previous_text

* add/update tests, make compatible with timestamps

* make compatible with diff. input kwargs and max length

* add None check

* add temperature check

* flip temp check operand

* refocusing to prev pr scope

* remove the params too

* make style

* edits, move max length incorporating prompt to whisper

* address comments

* remove asr pipeline prompt decoding, fix indexing

* address comments (more tests, validate prompt)

* un-comment out tests (from debug)

* remove old comment

* address comments

* fix typo

* remove timestamp token from test

* make style

* cleanup

* copy method to fast tokenizer, set max_new_tokens for test

* prompt_ids type just pt

* address Amy's comments

* make style

* Properly guard PyTorch stuff

* [all-test]

* [all-test] Fix model imports as well

* Making sure StoppingCriteria is always defined

* [all-test]

* fix

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

* Add local agent

* Document LocalAgent