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fix Whisper tests on GPU #23753

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merged 3 commits into from
May 30, 2023
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What does this PR do?

The daily CI showed that Whisper has new test failures, related to the recent merge of the prompting feature. This PR fixes those test failures.

The tests ran OK on CPU but failed on GPU because the input data wasn't moved to the GPU.

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  • This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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  • Did you make sure to update the documentation with your changes? Here are the
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    here are tips on formatting docstrings.
  • Did you write any new necessary tests?

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HuggingFaceDocBuilderDev commented May 25, 2023

The documentation is not available anymore as the PR was closed or merged.

@hollance
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hollance commented May 25, 2023

Also skipping a few tests in WhisperModelTest that were previously skipped in WhisperEncoderModelTest, see #22060

Although I just saw there's another open PR dealing with the same issue, so maybe none of these should be skipped: #22803

@hollance hollance requested a review from sgugger May 25, 2023 13:31
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Thanks for the fix, just one question on the model parallelism tests.

@@ -393,6 +393,18 @@ def test_inputs_embeds(self):
with torch.no_grad():
model(**inputs)[0]

@unittest.skip(reason="Some undefined behavior encountered with tiny versions of this model. Skip for now.")
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Were those failing before already or is it also linked to the recent PR?

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Looking through the daily-ci history I don't actually see any WhisperModelTest failures on test_model_parallelism, but test_cpu_offload and/or test_disk_offload do seem to fail occasionally. These tests were disabled in WhisperEncoderModelTest, so I also disabled them here. They seem to be unrelated to the prompting PR.

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Let's leave them as is then.

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OK, removed those tests. Feel free to merge at your leisure.

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LGTM - thanks for the torch device fixes @hollance!

@sgugger sgugger merged commit 2faa095 into huggingface:main May 30, 2023
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sgugger commented May 30, 2023

Thanks again!

mishig25 added a commit that referenced this pull request May 30, 2023
* Debug example code for MegaForCausalLM (#23382)

* Debug example code for MegaForCausalLM

set ignore_mismatched_sizes=True in model loading code

* Fix up

* Remove erroneous `img` closing tag (#23646)

See #23625

* Fix tensor device while attention_mask is not None (#23538)

* Fix tensor device while attention_mask is not None

* Fix tensor device while attention_mask is not None

* Fix accelerate logger bug (#23650)

* fix logger bug

* Update tests/mixed_int8/test_mixed_int8.py

Co-authored-by: Zachary Mueller <muellerzr@gmail.com>

* import `PartialState`

---------

Co-authored-by: Zachary Mueller <muellerzr@gmail.com>

* Muellerzr fix deepspeed (#23657)

* Fix deepspeed recursion

* Better fix

* Bugfix: LLaMA layer norm incorrectly changes input type and consumers lots of memory (#23535)

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

* make fix-copies

---------

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

* Fix wav2vec2 is_batched check to include 2-D numpy arrays (#23223)

* 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

---------

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

* changing the requirements to a cpu torch version that works (#23483)

* Fix SAM tests and use smaller checkpoints (#23656)

* Fix SAM tests and use smaller checkpoints

* Override test_model_from_pretrained to use sam-vit-base as well

* make fixup

* Update all no_trainer with skip_first_batches (#23664)

* Update workflow files (#23658)

* fix

* fix

---------

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

* [image-to-text pipeline] Add conditional text support + GIT (#23362)

* 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

* small fix to remove unused eos in processor when it's not used. (#23408)

* Bump requests from 2.27.1 to 2.31.0 in /examples/research_projects/decision_transformer (#23673)

Bump requests in /examples/research_projects/decision_transformer

Bumps [requests](https://github.com/psf/requests) from 2.27.1 to 2.31.0.
- [Release notes](https://github.com/psf/requests/releases)
- [Changelog](https://github.com/psf/requests/blob/main/HISTORY.md)
- [Commits](psf/requests@v2.27.1...v2.31.0)

---
updated-dependencies:
- dependency-name: requests
  dependency-type: direct:production
...

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Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* Bump requests from 2.22.0 to 2.31.0 in /examples/research_projects/visual_bert (#23670)

Bump requests in /examples/research_projects/visual_bert

Bumps [requests](https://github.com/psf/requests) from 2.22.0 to 2.31.0.
- [Release notes](https://github.com/psf/requests/releases)
- [Changelog](https://github.com/psf/requests/blob/main/HISTORY.md)
- [Commits](psf/requests@v2.22.0...v2.31.0)

---
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- dependency-name: requests
  dependency-type: direct:production
...

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Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* Bump requests from 2.22.0 to 2.31.0 in /examples/research_projects/lxmert (#23668)

Bump requests in /examples/research_projects/lxmert

Bumps [requests](https://github.com/psf/requests) from 2.22.0 to 2.31.0.
- [Release notes](https://github.com/psf/requests/releases)
- [Changelog](https://github.com/psf/requests/blob/main/HISTORY.md)
- [Commits](psf/requests@v2.22.0...v2.31.0)

---
updated-dependencies:
- dependency-name: requests
  dependency-type: direct:production
...

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Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* Add PerSAM [bis] (#23659)

* Add PerSAM args

* Make attn_sim optional

* Rename to attention_similarity

* Add docstrigns

* Improve docstrings

* Fix typo in a parameter name for open llama model (#23637)

* 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

* Fix PyTorch SAM tests (#23682)

fix

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

* Making `safetensors` a core dependency. (#23254)

* Making `safetensors` a core dependency.

To be merged later, I'm creating the PR so we can try it out.

* Update setup.py

* Remove duplicates.

* Even more redundant.

* 🌐 [i18n-KO] Translated `tasks/monocular_depth_estimation.mdx` to Korean (#23621)

docs: ko: `tasks/monocular_depth_estimation`

Co-authored-by: Hyeonseo Yun <0525yhs@gmail.com>
Co-authored-by: Sohyun Sim <96299403+sim-so@users.noreply.github.com>
Co-authored-by: Gabriel Yang <gabrielwithhappy@gmail.com>
Co-authored-by: Wonhyeong Seo <wonhseo@kakao.com>
Co-authored-by: Jungnerd <46880056+jungnerd@users.noreply.github.com>

* Fix a `BridgeTower` test (#23694)

fix

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

* [`SAM`] Fixes pipeline and adds a dummy pipeline test (#23684)

* add a dummy pipeline test

* change test name

* TF version compatibility fixes (#23663)

* 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

* [`Blip`] Fix blip doctest (#23698)

fix blip doctest

* is_batched fix for remaining 2-D numpy arrays (#23309)

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

* Tests

* Fix typo

* Incorporate comments from PR #23223

* Skip `TFCvtModelTest::test_keras_fit_mixed_precision` for now (#23699)

fix

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

* fix: load_best_model_at_end error when load_in_8bit is True (#23443)

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

* Fix some docs what layerdrop does (#23691)

* 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

---------

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

* add GPTJ/bloom/llama/opt into model list and enhance the jit support (#23291)

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

* 4-bit QLoRA via bitsandbytes (4-bit base model + LoRA) (#23479)

* 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>

* Paged Optimizer + Lion Optimizer for Trainer (#23217)

* 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.

---------

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

* Export to ONNX doc refocused on using optimum, added tflite (#23434)

* doc refocused on using optimum, tflite

* minor updates to fix checks

* Apply suggestions from code review

Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>

* TFLite to separate page, added links

* Removed the onnx list builder

* make style

* Update docs/source/en/serialization.mdx

Co-authored-by: regisss <15324346+regisss@users.noreply.github.com>

---------

Co-authored-by: regisss <15324346+regisss@users.noreply.github.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

---------

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

* fix gptj could not jit.trace in GPU (#23317)

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

* Better TF docstring types (#23477)

* 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

* Minor awesome-transformers.md fixes (#23453)

Minor docs fixes

* TF SAM memory reduction (#23732)

* 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

* fix: delete duplicate sentences in `document_question_answering.mdx` (#23735)

fix: delete duplicate sentence

* fix: Whisper generate, move text_prompt_ids trim up for max_new_tokens calculation (#23724)

move text_prompt_ids trimming to top

* Overhaul TF serving signatures + dummy inputs (#23234)

* 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

* [Whisper] Reduce batch size in tests (#23736)

* 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

* Fix sagemaker DP/MP (#23681)

* 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

* Enable prompts on the Hub (#23662)

* Enable prompts on the Hub

* Update src/transformers/tools/prompts.py

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

* Address review comments

---------

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

* Remove the last few TF serving sigs (#23738)

Remove some more serving methods that (I think?) turned up while this PR was open

* Fix `pip install --upgrade accelerate` command in modeling_utils.py (#23747)

Fix command in modeling_utils.py

* Add LlamaIndex to awesome-transformers.md (#23484)

* Fix psuh_to_hub in Trainer when nothing needs pushing (#23751)

* Revamp test selection for the example tests (#23737)

* Revamp test selection for the example tests

* Rename old XLA test and fake modif in run_glue

* Fixes

* Fake Trainer modif

* Remove fake modifs

* [LongFormer] code nits, removed unused parameters  (#23749)

* remove unused parameters

* remove unused parameters in config

* Fix is_ninja_available() (#23752)

* Fix is_ninja_available()

search ninja using subprocess instead of importlib.

* Fix style

* Fix doc

* Fix style

* Bump tornado from 6.0.4 to 6.3.2 in /examples/research_projects/lxmert (#23766)

Bumps [tornado](https://github.com/tornadoweb/tornado) from 6.0.4 to 6.3.2.
- [Changelog](https://github.com/tornadoweb/tornado/blob/master/docs/releases.rst)
- [Commits](tornadoweb/tornado@v6.0.4...v6.3.2)

---
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- dependency-name: tornado
  dependency-type: direct:production
...

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Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* Bump tornado from 6.0.4 to 6.3.2 in /examples/research_projects/visual_bert (#23767)

Bump tornado in /examples/research_projects/visual_bert

Bumps [tornado](https://github.com/tornadoweb/tornado) from 6.0.4 to 6.3.2.
- [Changelog](https://github.com/tornadoweb/tornado/blob/master/docs/releases.rst)
- [Commits](tornadoweb/tornado@v6.0.4...v6.3.2)

---
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  dependency-type: direct:production
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* [`Nllb-Moe`] Fix nllb moe accelerate issue (#23758)

fix nllb moe accelerate issue

* [OPT] Doc nit, using fast is fine (#23789)

small doc nit

* Fix RWKV backward on GPU (#23774)

* Update trainer.mdx class_weights example (#23787)

class_weights tensor should follow model's device

* no_cuda does not take effect in non distributed environment (#23795)

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

* Fix no such file or directory error (#23783)

* Fix no such file or directory error

* Address comment

* Fix formatting issue

* Log the right train_batch_size if using auto_find_batch_size and also log the adjusted value seperately. (#23800)

* Log right bs

* Log

* Diff message

* Enable code-specific revision for code on the Hub (#23799)

* Enable code-specific revision for code on the Hub

* invalidate old revision

* [Time-Series] Autoformer model (#21891)

* ran `transformers-cli add-new-model-like`

* added `AutoformerLayernorm` and `AutoformerSeriesDecomposition`

* added `decomposition_layer` in `init` and `moving_avg` to config

* added `AutoformerAutoCorrelation` to encoder & decoder

* removed caninical self attention `AutoformerAttention`

* added arguments in config and model tester. Init works! 😁

* WIP autoformer attention with autocorrlation

* fixed `attn_weights` size

* wip time_delay_agg_training

* fixing sizes and debug time_delay_agg_training

* aggregation in training works! 😁

* `top_k_delays` -> `top_k_delays_index` and added `contiguous()`

* wip time_delay_agg_inference

* finish time_delay_agg_inference 😎

* added resize to autocorrelation

* bug fix: added the length of the output signal to `irfft`

* `attention_mask = None` in the decoder

* fixed test: changed attention expected size, `test_attention_outputs` works!

* removed unnecessary code

* apply AutoformerLayernorm in final norm in enc & dec

* added series decomposition to the encoder

* added series decomp to decoder, with inputs

* added trend todos

* added autoformer to README

* added to index

* added autoformer.mdx

* remove scaling and init attention_mask in the decoder

* make style

* fix copies

* make fix-copies

* inital fix-copies

* fix from #22076

* make style

* fix class names

* added trend

* added d_model and projection layers

* added `trend_projection` source, and decomp layer init

* added trend & seasonal init for decoder input

* AutoformerModel cannot be copied as it has the decomp layer too

* encoder can be copied from time series transformer

* fixed generation and made distrb. out more robust

* use context window to calculate decomposition

* use the context_window for decomposition

* use output_params helper

* clean up AutoformerAttention

* subsequences_length off by 1

* make fix copies

* fix test

* added init for nn.Conv1d

* fix IGNORE_NON_TESTED

* added model_doc

* fix ruff

* ignore tests

* remove dup

* fix SPECIAL_CASES_TO_ALLOW

* do not copy due to conv1d weight init

* remove unused imports

* added short summary

* added label_length and made the model non-autoregressive

* added params docs

* better doc for `factor`

* fix tests

* renamed `moving_avg` to `moving_average`

* renamed `factor` to `autocorrelation_factor`

* make style

* Update src/transformers/models/autoformer/configuration_autoformer.py

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

* Update src/transformers/models/autoformer/configuration_autoformer.py

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

* fix configurations

* fix integration tests

* Update src/transformers/models/autoformer/configuration_autoformer.py

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

* fixing `lags_sequence` doc

* Revert "fixing `lags_sequence` doc"

This reverts commit 21e3491.

* Update src/transformers/models/autoformer/modeling_autoformer.py

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

* Update src/transformers/models/autoformer/modeling_autoformer.py

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

* Update src/transformers/models/autoformer/modeling_autoformer.py

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* Apply suggestions from code review

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

* Update src/transformers/models/autoformer/configuration_autoformer.py

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

* model layers now take the config

* added `layer_norm_eps` to the config

* Update src/transformers/models/autoformer/modeling_autoformer.py

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

* added `config.layer_norm_eps` to AutoformerLayernorm

* added `config.layer_norm_eps` to all layernorm layers

* Update src/transformers/models/autoformer/configuration_autoformer.py

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* Update src/transformers/models/autoformer/configuration_autoformer.py

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* Update src/transformers/models/autoformer/configuration_autoformer.py

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* Update src/transformers/models/autoformer/configuration_autoformer.py

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* fix variable names

* added inital pretrained model

* added use_cache docstring

* doc strings for trend and use_cache

* fix order of args

* imports on one line

* fixed get_lagged_subsequences docs

* add docstring for create_network_inputs

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* fix signature

* use AutoformerModelOutput dataclass

* fix pretrain config

* no need as default exists

* subclass ModelOutput

* remove layer_norm_eps config

* fix test_model_outputs_equivalence test

* test hidden_states_output

* make fix-copies

* Update src/transformers/models/autoformer/configuration_autoformer.py

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* removed unused attr

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* Update src/transformers/models/autoformer/modeling_autoformer.py

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* Update src/transformers/models/autoformer/modeling_autoformer.py

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* Update src/transformers/models/autoformer/modeling_autoformer.py

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* Update src/transformers/models/autoformer/modeling_autoformer.py

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* Update src/transformers/models/autoformer/modeling_autoformer.py

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* Update src/transformers/models/autoformer/modeling_autoformer.py

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* use AutoFormerDecoderOutput

* fix formatting

* fix formatting

---------

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* add type hint in pipeline model argument (#23740)

* add type hint in pipeline model argument

* add pretrainedmodel and tfpretainedmodel type hint

* make type hints string

* TF SAM shape flexibility fixes (#23842)

SAM shape flexibility fixes for compilation

* fix Whisper tests on GPU (#23753)

* move input features to GPU

* skip these tests because undefined behavior

* unskip tests

* 🌐 [i18n-KO] Translated `fast_tokenizers.mdx` to Korean (#22956)

* docs: ko: fast_tokenizer.mdx

content - translated

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* Update docs/source/ko/fast_tokenizers.mdx

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* Update docs/source/ko/fast_tokenizers.mdx

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* Update docs/source/ko/fast_tokenizers.mdx

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* Update docs/source/ko/fast_tokenizers.mdx

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* Update docs/source/ko/fast_tokenizers.mdx

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* Update docs/source/ko/fast_tokenizers.mdx

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* Update docs/source/ko/fast_tokenizers.mdx

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* Update fast_tokenizers.mdx

* Update fast_tokenizers.mdx

* Update fast_tokenizers.mdx

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---------

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* [i18n-KO] Translated video_classification.mdx to Korean (#23026)

* task/video_classification translated

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* Update docs/source/ko/tasks/video_classification.mdx

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* Update docs/source/ko/tasks/video_classification.mdx

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* Update docs/source/ko/tasks/video_classification.mdx

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* Update docs/source/ko/tasks/video_classification.mdx

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* Update docs/source/ko/tasks/video_classification.mdx

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* Update docs/source/ko/tasks/video_classification.mdx

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* Update docs/source/ko/tasks/video_classification.mdx

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* Apply suggestions from code review

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* Update video_classification.mdx

* Update _toctree.yml

* Update _toctree.yml

* Update _toctree.yml

* Update _toctree.yml

---------

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* 🌐 [i18n-KO] Translated `troubleshooting.mdx` to Korean (#23166)

* docs: ko: troubleshooting.mdx

* revised: fix _toctree.yml #23112

* feat: nmt draft `troubleshooting.mdx`

* fix: manual edits `troubleshooting.mdx`

* revised: resolve suggestions troubleshooting.mdx

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---------

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* Adds a FlyteCallback (#23759)

* initial flyte callback

* lint

* logs should still be saved to Flyte even if pandas isn't install (unlikely)

* cr - flyte team

* add docs for Flytecallback

* fix doc string - cr sgugger

* Apply suggestions from code review

cr - sgugger fix doc strings

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---------

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* Update collating_graphormer.py (#23862)

* [LlamaTokenizerFast] nit update `post_processor` on the fly (#23855)

* Update the processor when changing add_eos and add_bos

* fixup

* update

* add a test

* fix failing tests

* fixup

* #23388 Issue: Update RoBERTa configuration (#23863)

* [from_pretrained] imporve the error message when `_no_split_modules` is not defined (#23861)

* Better warning

* Update src/transformers/modeling_utils.py

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* format line

---------

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---------

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sheonhan pushed a commit to sheonhan/transformers that referenced this pull request Jun 1, 2023
* move input features to GPU

* skip these tests because undefined behavior

* unskip tests
gojiteji pushed a commit to gojiteji/transformers that referenced this pull request Jun 5, 2023
* move input features to GPU

* skip these tests because undefined behavior

* unskip tests
novice03 pushed a commit to novice03/transformers that referenced this pull request Jun 23, 2023
* move input features to GPU

* skip these tests because undefined behavior

* unskip tests
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