GitLab

* add bnb flag

* move maker

* add accelerator maker

updated examples/pytorch/language-modeling scripts and requirements.txt to require datasets>=2.14.0 (#30120)

updated requirements.txt and require_version() calls in examples/pytorch/language-modeling to require datasets>=2.14.0

* Make MLFlow version detection more robust and handles mlflow-skinny

* Make function name more clear and refactor the logic

* Further refactor

* add _torch_extract_fbank_features_batch function in feature_extractor_whisper

* reformat feature_extraction_whisper.py file

* handle batching in single function

* add gpu test & doc

* add batch test & device in each __call__

* add device arg in doc string

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Co-authored-by: vaibhav.aggarwal <vaibhav.aggarwal@sprinklr.com>

* clean-up whisper kwargs

* failing test

* fix

* fix

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

* Add docstrings and types for MambaCache

* Update src/transformers/models/mamba/modeling_mamba.py

* Update src/transformers/models/mamba/modeling_mamba.py

* Update src/transformers/models/mamba/modeling_mamba.py

* make fixup

* import copy in generation_whisper

* ruff

* Revert "make fixup"

This reverts commit c4fedd6f60e3b0f11974a11433bc130478829a5c.

* separate jobs

* separate jobs

* use channel name directly instead of ID

* use channel name directly instead of ID

* use channel name directly instead of ID

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

* [WIP] fix fx

* [WIP] fix fx

* [WIP] fix fx

* [WIP] fix fx

* [WIP] fix fx

* Apply changes to other models

* fix

* fix

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

Update quantizer_bnb_4bit.py: In the ValueError string there should be "....you need to set `llm_int8_enable_fp32_cpu_offload=True`...." instead of "`load_in_8bit_fp32_cpu_offload=True`". (#30013)

* Update quantizer_bnb_4bit.py

There is an mistake in ValueError on line 86 of quantizer_bnb_4bit.py. In the error string there should be "....you need to set `llm_int8_enable_fp32_cpu_offload=True`...." instead of "load_in_8bit_fp32_cpu_offload=True". I think you updated the BitsAndBytesConfig() arguments, but forgot to change the ValueError in quantizer_bnb_4bit.py.

* Update quantizer_bnb_4bit.py

Changed ValueError string "...you need to set load_in_8bit_fp32_cpu_offload=True..." to "....you need to set llm_int8_enable_fp32_cpu_offload=True...."

fix bnb test

* Add image processor to trainer

* Replace tokenizer=image_processor everywhere

* fix mixtral onnx export

* fix qwen model

* if output is tuple like facebook/hf-seamless-m4t-medium, waveform is the first element
Signed-off-by: Wang, Yi <yi.a.wang@intel.com>

* add test and fix batch issue
Signed-off-by: Wang, Yi <yi.a.wang@intel.com>

* add dict output support for seamless_m4t
Signed-off-by: Wang, Yi <yi.a.wang@intel.com>

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

skip test_encode_decode_fast_slow_all_tokens for now
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

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

* changes

* addressing comments

* smol fix

* Defaulted IdeficsProcessor padding to 'longest', removed manual padding

* make fixup

* Defaulted processor call to padding=False

* Add padding to processor call in IdeficsModelIntegrationTest as well

* Defaulted IdeficsProcessor padding to 'longest', removed manual padding

* make fixup

* Defaulted processor call to padding=False

* Add padding to processor call in IdeficsModelIntegrationTest as well

* redefaulted padding=longest again

* fixup/doc

* implement convert_mamba_ssm_checkpoint_to_pytorch

* Add test test_model_from_mamba_ssm_conversion

* moved convert_ssm_config_to_hf_config to inside mamba_ssm_available check

* fix skipif clause

* moved skips to inside test since skipif decorator isn't working for some reason

* Added validation

* removed test

* fixup

* only compare logits

* remove weight rename

* Update src/transformers/models/mamba/convert_mamba_ssm_checkpoint_to_pytorch.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* nits

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

feat: enable mult-idevice for efficientnet

* Docstring to note about zero init

* Check for accelerate

* Change conditional return

* Tweak

* Add new accelerate-specific zero3 check

* Fix import

* Revert to RTFM

* Update src/transformers/modeling_utils.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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

* fix

* sort imports

quick fix

new audio file

* fix vipllava generation

* consistent llava code

* revert llava tests changes

* Fix is_scores_logprobs in WhisperNoSpeechDetection

* Add test_whisper_longform_no_speech_detection

* Fix typo

* Fix generate_with_fallback **kwargs

* Change pop to get

* Delete keys from kwargs to prevent overriding generation_config

* Revert to passing kwargs by reference, but make a (shallow) copy

* dict -> copy.copy

* Add test_whisper_longform_multi_batch_beam

qwen2: fixed tokens starting with # in slow tokenizer; add tests
Co-authored-by: jklj077 <17811943+jklj077@users.noreply.github.com>

To address the issue of NaN logit outputs for certain combinations
of the `image_size`, `patch_size` and `depths` configuration
parameters, an assertion was made to ensure that the resulting
`window_size` field in the model's Self Attention class is greater
than 1, preventing divisions by zero in the normalization of
`relative_coords_table`.

Fix: #28675

* fix encodec onnx export for musicgen

* simplification

* fix quality

* better style

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

* fix norm

* fix logits processors doctests

* Hard error when ignoring tensors. (#27484)

* [WIP] Hard error when ignoring tensors.

* Better selection/error when saving a checkpoint.

- Find all names we should normally drop (those are in the transformers
  config)
- Find all disjoint tensors (for those we can safely trigger a copy to
  get rid of the sharing before saving)
- Clone those disjoint tensors getting rid of the issue
- Find all identical names (those should be declared in the config
  but we try to find them all anyway.)
- For all identical names:
  - If they are in the config, just ignore them everything is fine
  - If they are not, warn about them.
- For all remainder tensors which are shared yet neither identical NOR
  disjoint. raise a hard error.

* Adding a failing test on `main` that passes here.

* We don't need to keep the subfolder logic in this test.

* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Add small tests.

* Dead variable.

* Fixup.

* Fixing tied_Weights_keys on generic models.

* Fixup + T5 encoder/decoder tying (with different layers)

* Code quality.

* Dynamic member.

* trigger

* Fixing encoder name for other types of encoder/decoder combos.

* Fix scoping.

* Update .github/workflows/self-scheduled.yml
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Fixing the tied_weights after the call.

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Fix skip_special_tokens process for Wav2Vec2CTCTokenizer._decode

* Fix skip_special_tokens for Wav2Vec2CTCTokenizer._decode

* Exclude pad_token filtering since it is used as CTC-blank token

* Add small test for skip_special_tokens

* Update decoding test for added new token