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[Whisper] Refactor forced_decoder_ids & prompt ids #28687

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merged 30 commits into from
Jan 31, 2024

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patrickvonplaten
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@patrickvonplaten patrickvonplaten commented Jan 24, 2024

What does this PR do?

This PR refactors forced_decoder_ids making sure that we now always pass prompted ids as decoder_input_ids into generate for Whisper. The whole idea of forcing ids instead of just passing them as initial tokens was a bad design choice and we should try to move away from it.

In addition, Whisper prompting is improved by:

  • Not allowing prompt_ids to be passed as a numpy array
  • Enable prompt_ids for long-form generation with two modes:
    • a) prompt only the first segment
    • b) prompt every segment

While a) is the only supported case in the original Whisper repo b) can be very useful as can be seen in the added slow test here.

This is the final code PR regarding Whisper for Transformers. In the next weeks focus will be put on writing nice docs, tutorials and blog posts.

@patrickvonplaten patrickvonplaten marked this pull request as draft January 24, 2024 22:10
timestamps = torch.zeros_like(generate_outputs.sequences, dtype=torch.float32)
# make sure timestamps are as long as weights
input_length = weight_length or cross_attentions[0].shape[2]
timestamps = torch.zeros_like(generate_outputs.sequences, dtype=torch.float32)[:, : input_length + 1]
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Now that we don't use forced_decoder_ids anymore for whisper generate -> we need to potentially cut the length of timestamps according to the actual length of the input

outputs = super().generate(
input_features,
generation_config=generation_config,
logits_processor=logits_processor,
stopping_criteria=stopping_criteria,
prefix_allowed_tokens_fn=prefix_allowed_tokens_fn,
synced_gpus=synced_gpus,
decoder_input_ids=decoder_input_ids,
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We now directly pass the prompt tokens also in short-form generate

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Very nice!

# let's make sure we don't pass `None` tokens as prompt tokens
init_tokens = [t for t in init_tokens if t is not None]

return init_tokens
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this function is heavily rewritten to make sure that forced_decoder_ids + specified task and/or language create the correct init_tokens prompt conditioning.

@@ -1162,6 +1251,25 @@ def _set_thresholds_and_condition(
else getattr(generation_config, "condition_on_prev_tokens", None)
)

@staticmethod
def _set_prompt_condition_type(generation_config, prompt_condition_type):
allowed_cond_types = ["first-segment", "all-segments"]
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We have to types of prompt_conditioning for long-form:

    1. We condition only the first segment on the prompt
    1. We condition all segments on the prompt

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@patrickvonplaten patrickvonplaten Jan 26, 2024

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The original OAI whisper codebase only has i., but ii. has some very nice advantages in certain scenarios.

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Looks good!

@@ -1256,11 +1334,12 @@ def _retrieve_logit_processors(

if is_shortform and generation_config.forced_decoder_ids is not None:
forced_tokens_proc = ForceTokensLogitsProcessor(generation_config.forced_decoder_ids)
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We're leaving the ForceTokensLogitsProcessor here for backwards compatibility for short-form. But it should be removed in 4.39.

@@ -1460,11 +1461,8 @@ def test_slow_unfinished_sequence(self):
self.assertEqual(
out,
{
"chunks": [
{"text": "", "timestamp": (18.94, 0.02)},
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This didn't make sense before as the audio is only 4 seconds long. Seems like changing from forced_decoder_inputs to decoder_input_ids correts this actually.

@@ -1258,7 +1258,7 @@ def test_generate_with_prompt_ids_and_task_and_language(self):
config, input_dict = self.model_tester.prepare_config_and_inputs_for_common()
model = WhisperForConditionalGeneration(config).eval().to(torch_device)
input_features = input_dict["input_features"]
prompt_ids = np.arange(5)
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Previously we allowed passing numpy arrays into model.generate(...) which I think was not intentional and a bug (see here: https://github.com/huggingface/transformers/pull/22496/files#r1467370182).

If people feel strongly I can make it backward compatible though inside generate, but we should definitely not allow passing numpy arrays into a nn.Module

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Good with me - agree that this is a "bug" that we can fix

@slow
def test_whisper_longform_single_batch_prev_cond(self):
# fmt: off
EXPECTED_TEXT = [""" Mr. Quilter is the apostle of the middle classes, and we are glad to welcome his gospel. Nor is Mr. Quilter's manner less interesting than his matter. He tells us that at this festive season of the year, with Christmas and roast beef looming before us, similes drawn from eating and its results occur most readily to the mind. He has grieved doubts whether Sir Frederick Layton's work is really Greek after all, and can discover in it but little of rocky Ithaca. Linnell's pictures are a sort of up-gards and atom paintings, and Mason's exquisite itals are as national as a jingo poem. Mr. Birk at Foster's landscapes smile at one much in the same way that Mr. Carker used to flash his teeth. When Mr. John Collier gives his sitter a cheerful slap in the back, before he says like a shampooer and a Turkish bath, next man it is obviously unnecessary for us to point out how luminous these criticisms are, how delicate an expression. On the general principles of art, Mr. Quilter writes with equal lucidity. He tells us is of a different quality to mathematics, and finish in art is adding more effect. As for etchings, there are two kinds, British and foreign. He laments most bitterly the divorce that has been made between decorative art and what we usually call pictures. Makes a customary appeal to the last judgment and reminds us that in the great days of art Michelangelo was the furnishing upholsterer. Near the fire, any ornaments Fred brought home from India on the mental board. In fact, he is quite severe on Mr. Ruskin for not recognizing that a picture should denote the frailty of man, and remarks was pleasing courtesy in felicitous grace that many faces are feeling. Unfortunately his own work never does get good. Mr. Quilter has missed his chance, for he has failed even to make himself the tupper of painting. By Harry Quilter M. A. A man said to the universe, Sir, I exist. Sweat covered Breon's body trickling into the tight-lowing cloth that was the only german he wore. The cut on his chest still dripping blood. The ache of his overstrained eyes, even the soaring arena around him with thousands of spectators, retroveilities not worth thinking about. His instant panic was followed by a small sharp blow high on his chest. One minute, a voice said, and a time buzzer sounded. A minute is not a very large measure of time, and his body needed every fraction of it. The buzzers were triggered as muscles into complete relaxation. Only his heart and lungs worked on at a strong measured rate. He was in reverie, sliding along the borders of consciousness. The contestants in the twenties needed undisturbed rest. Therefore, nights in the dormitories were as quiet as death. Particularly so, on this last night, when only two of the little cubicles were occupied, the thousands of others standing with dark empty doors. The other voice snapped with a harsh urgency, clearly used to command. I'm here because the matter is of utmost importance, and brand is the one I must see. Now stand aside. The twenties, he must have drawn his gun because the intruder said quickly, but that away you're being a fool. But there was silence then, and still wondering, Breon was once more asleep. Ten seconds, he asked the handler who was needing his aching muscles. A red-haired mountain of a man with an apparently inexhaustible store of energy. There could be little art in this last and final round of fencing. Just thrust and parry and victory to the stronger. Your man who entered the twenties had his own training tricks. They were appeared to be an immediate association with the death trauma, as if the two were inextricably linked into one. The strength that enables someone in a trance to hold his body stiff and unsupported except at two points, the head and heels. This is physically impossible when conscious. Breon's death was in some ways easier than defeat. Breon's softly spoke the auto-hypnotic phrases that triggered the process. When the buzzer sounded, he pulled his foil from his second startled grasp and ran forward. Our role looked amazed at the sudden fury of the attack, then smiled. He thought it was the last burst of energy. He knew how close they both were to exhaustion. Breon saw something close to panic on his opponent's face when the man finally recognized his error. A wave of despair rolled out from our rogue. Breon sensed it and knew the fifth point was his. Then the powerful twist that's rested aside, in and under the guard, because he was sleeping instead of conquering, the lovely rose princess has become a fiddle without a bow, while poor Shaggy sits there, accooing dove. He has gone and gone for good, answered Polychrome, who had managed to squeeze into the room beside the dragon, and had witnessed the occurrences with much interest. I have remained a prisoner only because I wished to be one. And with this, he stepped forward and burst the stout chains as easily as if they had been threads. The little girl had been asleep, but she heard the wraps and opened the door. The king has flooded disgrace, and your friends are asking for you. I begged Ruggido long ago to send him away, but he would not do so. I also offered to help your brother to escape, but he would not go. He eats and sleeps very steadily, replied the new king. I hope he doesn't work too hard, since Shaggy. He doesn't work at all. In fact, there's nothing he can do in these dominions, as well as our gnomes, whose numbers are so great that it worries us to keep them all busy. Not exactly, we've turned Calico. Where is my brother now, inquired Shaggy. In the metal forest. Where is that? The metal forest is in the great domed cavern, the largest and all-ard dominions, replied Calico. Calico hesitated. However, if we look sharp, we may be able to discover one of these secret ways. Oh no, I'm quite sure he didn't. That's funny, remarked Betsy thoughtfully. I don't believe Anne knew any magic, or she'd have worked it before. I do not know, confessed Shaggy. True, agreed Calico. Calico went to the big gong, and pounded on it, just as we're good to be used to do. But no one answered the summons. Having returned to the royal cavern, Calico first pounded the gong, and then sat in the throne, wearing Regidos discarded Ruby Crown, and holding in his hand to scepter, which Regidos had so often thrown at his head."""]
EXPECTED_TEXT = [""" Mr. Quilter is the apostle of the middle classes, and we are glad to welcome his gospel. Nor is Mr. Quilter's manner less interesting than his matter. He tells us that at this festive season of the year, with Christmas and roast beef looming before us, similes drawn from eating and its results occur most readily to the mind. He has grieved doubts whether Sir Frederick Layton's work is really Greek after all, and can discover in it but little of rocky Ithaca. Linnell's pictures are a sort of up-gards and atom paintings, and Mason's exquisite itals are as national as a jingo poem. Mr. Birk at Foster's landscapes smile at one much in the same way that Mr. Carker used to flash his teeth. When Mr. John Collier gives his sitter a cheerful slap in the back, before he says like a shampooer and a Turkish bath, next man it is obviously unnecessary for us to point out how luminous these criticisms are, how delicate an expression. On the general principles of art, Mr. Quilter writes with equal lucidity. He tells us is of a different quality to mathematics, and finish in art is adding more effect. As for etchings, there are two kinds, British and foreign. He laments most bitterly the divorce that has been made between decorative art and what we usually call pictures. Makes a customary appeal to the last judgment and reminds us that in the great days of art Michelangelo was the furnishing upholsterer. Near the fire, any ornaments Fred brought home from India on the mental board. In fact, he is quite severe on Mr. Ruskin for not recognizing that a picture should denote the frailty of man, and remarks was pleasing courtesy in felicitous grace that many faces are feeling. Unfortunately his own work never does get good. Mr. Quilter has missed his chance, for he has failed even to make himself the tupper of painting. By Harry Quilter M. A. A man said to the universe, Sir, I exist. Sweat covered Breon's body trickling into the tight-lowing cloth that was the only german he wore. The cut on his chest still dripping blood. The ache of his overstrained eyes, even the soaring arena around him with thousands of spectators, retroveilities not worth thinking about. His instant panic was followed by a small sharp blow high on his chest. One minute, a voice said, and a time buzzer sounded. A minute is not a very large measure of time, and his body needed every fraction of it. The buzzers were triggered as muscles into complete relaxation. Only his heart and lungs worked on at a strong measured rate. He was in reverie, sliding along the borders of consciousness. The contestants in the twenties needed undisturbed rest. Therefore, nights in the dormitories were as quiet as death. Particularly so, on this last night, when only two of the little cubicles were occupied, the thousands of others standing with dark empty doors. The other voice snapped with a harsh urgency, clearly used to command. I'm here because the matter is of utmost importance, and brand is the one I must see. Now stand aside. The twenties, he must have drawn his gun because the intruder said quickly, but that away you're being a fool. But there was silence then, and still wondering, Breon was once more asleep. Ten seconds, he asked the handler who was needing his aching muscles. A red-haired mountain of a man with an apparently inexhaustible store of energy. There could be little art in this last and final round of fencing. Just thrust and parry and victory to the stronger. Your man who entered the twenties had his own training tricks. They were appeared to be an immediate association with the death trauma, as if the two were inextricably linked into one. The strength that enables someone in a trance to hold his body stiff and unsupported except at two points, the head and heels. This is physically impossible when conscious. Breon's death was in some ways easier than defeat. Breon's softly spoke the auto-hypnotic phrases that triggered the process. When the buzzer sounded, he pulled his foil from his second startled grasp and ran forward. Our role looked amazed at the sudden fury of the attack, then smiled. He thought it was the last burst of energy. He knew how close they both were to exhaustion. Breon saw something close to panic on his opponent's face when the man finally recognized his error. A wave of despair rolled out from our rogue. Breon sensed it and knew the fifth point was his. Then the powerful twist that's rested aside, in and under the guard, because he was sleeping instead of conquering, the lovely rose princess has become a fiddle without a bow, while poor Shaggy sits there, accooing dove. He has gone and gone for good, answered Polychrome, who had managed to squeeze into the room beside the dragon, and had witnessed the occurrences with much interest. I have remained a prisoner only because I wished to be one. And with this, he stepped forward and burst the stout chains as easily as if they had been threads. The little girl had been asleep, but she heard the wraps and opened the door. The king has flooded disgrace, and your friends are asking for you. I begged Ruggido long ago to send him away, but he would not do so. I also offered to help your brother to escape, but he would not go. He eats and sleeps very steadily, replied the new king. I hope he doesn't work too hard, since Shaggy. He doesn't work at all. In fact, there's nothing he can do in these dominions, as well as our gnomes, whose numbers are so great that it worries us to keep them all busy. Not exactly, we've turned Calico. Where is my brother now, inquired Shaggy. In the metal forest. Where is that? The metal forest is in the great domed cavern, the largest and all-ard dominions, replied Calico. Calico hesitated. However, if we look sharp, we may be able to discover one of these secret ways. Oh no, I'm quite sure he didn't. That's funny, remarked Betsy thoughtfully. I don't believe Anne knew any magic, or she'd have worked it before. I do not know, confessed Shaggy. True, agreed Calico. Calico went to the big gong and pounded on it, just as we're good to be used to do, but no one answered the summons. Having returned to the royal cavern, Calico first pounded the gong and then sat in the throne, wearing Regidos discarded Ruby crown, and holding in his hand to scepter which Regidos had so often thrown at his head."""]
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Tiny punctuation change in the expected results coming from the inherant randomness when using temperature fallback

@patrickvonplaten patrickvonplaten changed the title [Whisper] Refactor forced_decoder_ids [Whisper] Refactor forced_decoder_ids & prompt ids Jan 26, 2024
Comment on lines +2193 to +2194
@slow
def test_whisper_longform_prompt_ids(self):
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This test shows the advantages of both first-segment and all-segments prompt ids for long-form generation.

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Very nice - this could go in our Whisper blog post / detailed long-form guide (or even the new lib)

@patrickvonplaten patrickvonplaten marked this pull request as ready for review January 26, 2024 08:59
@HuggingFaceDocBuilderDev

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

@patrickvonplaten patrickvonplaten merged commit 65a926e into main Jan 31, 2024
18 checks passed
@patrickvonplaten patrickvonplaten deleted the fix_prompt_ids_whisper branch January 31, 2024 12:02
KaifAhmad1 added a commit to KaifAhmad1/transformers that referenced this pull request Feb 20, 2024
…uggingface#29145 (#1)

* Add qwen2 (#29145)

* add config, modeling, and tokenization

* add auto and init

* update readme

* update readme

* update team name

* fixup

* fixup

* update config

* update code style

* update for fixup

* update for fixup

* update for fixup

* update for testing

* update for testing

* fix bug for config and tokenization

* fix bug for bos token

* not doctest

* debug tokenizer

* not doctest

* debug tokenization

* debug init for tokenizer

* fix style

* update init

* delete if in token auto

* add tokenizer doc

* add tokenizer in init

* Update dummy_tokenizers_objects.py

* update

* update

* debug

* Update tokenization_qwen2.py

* debug

* Update convert_slow_tokenizer.py

* add copies

* add copied from and make style

* update files map

* update test

* fix style

* fix merge reading and update tests

* fix tests

* fix tests

* fix style

* debug a variable in readme

* Update src/transformers/models/qwen2/configuration_qwen2.py

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

* update test and copied from

* fix style

* update qwen2 tokenization  and tests

* Update tokenization_qwen2.py

* delete the copied from after property

* fix style

* update tests

* update tests

* add copied from

* fix bugs

* update doc

* add warning for sliding window attention

* update qwen2 tokenization

* fix style

* Update src/transformers/models/qwen2/modeling_qwen2.py

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

* fix tokenizer fast

---------

Co-authored-by: Ren Xuancheng <jklj077@users.noreply.github.com>
Co-authored-by: renxuancheng.rxc <renxuancheng.rxc@alibaba-inc.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Fix SDPA tests (#28552)

* skip bf16 test if not supported by device

* fix

* fix bis

* use is_torch_bf16_available_on_device

* use is_torch_fp16_available_on_device

* fix & use public llama

* use 1b model

* fix flacky test

---------

Co-authored-by: Your Name <you@example.com>

* Allow to train dinov2 with different dtypes like bf16 (#28504)

I want to train dinov2 with bf16 but I get the following error in https://github.com/huggingface/transformers/blob/bc72b4e2cdcbc80d5f56731f35dbc9c18b4c8de6/src/transformers/models/dinov2/modeling_dinov2.py#L635:

```
RuntimeError: Input type (float) and bias type (c10::BFloat16) should be the same
```

Since the input dtype is torch.float32, the parameter dtype has to be torch.float32...

@LZHgrla and I checked the code of clip vision encoder and found there is an automatic dtype transformation (https://github.com/huggingface/transformers/blob/bc72b4e2cdcbc80d5f56731f35dbc9c18b4c8de6/src/transformers/models/clip/modeling_clip.py#L181-L182).

So I add similar automatic dtype transformation to modeling_dinov2.py.

* Fix Switch Transformers When sparse_step = 1 (#28564)

Fix sparse_step = 1

I case sparse_step = 1, the current code will not work.

* Save `Processor` (#27761)

* save processor

* Update tests/models/auto/test_processor_auto.py

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

* Update tests/test_processing_common.py

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

* fix

---------

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

* Use `weights_only` only if torch >= 1.13 (#28506)

* fix

* fix

* fix

---------

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

* [`Core Tokenization`] Support a fix for spm fast models (#26678)

* fix

* last attempt

* current work

* fix forward compatibility

* save all special tokens

* current state

* revert additional changes

* updates

* remove tokenizer.model

* add a test and the fix

* nit

* revert one more break

* fix typefield issue

* quality

* more tests

* fix fields for FC

* more nits?

* new additional changes

* how

* some updates

* the fix

* where do we stand

* nits

* nits

* revert unrelated changes

* nits nits nits

* styling

* don't break llama just yet

* revert llama changes

* safe arg check

* fixup

* Add a test for T5

* Necessary changes

* Tests passing, added tokens need to not be normalized. If the added tokens are normalized, it will the stripping which seems to be unwanted for a normal functioning

* Add even more tests, when normalization is set to True (which does not work :sweat: )

* Add even more tests, when normalization is set to True (which does not work :sweat: )

* Update to main

* nits

* fmt

* more and more test

* comments

* revert change as tests are failing

* make the test more readble

* nits

* refactor the test

* nit

* updates

* simplify

* style

* style

* style convert slow

* Update src/transformers/convert_slow_tokenizer.py

* chore: Fix multiple typos (#28574)

* Add new meta w2v2-conformer BERT-like model (#28165)

* first commit

* correct default value non causal

* update config and modeling code

* update converting checkpoint

* clean modeling and fix tests

* make style

* add new config parameters to docstring

* fix copied from statements

* Apply suggestions from code review

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

* make position_embeddings_type docstrings clearer

* clean converting script

* remove function not used

* clean modeling file

* apply suggestion for test file + add convert script to not_doctested

* modify tests according to review - cleaner logic and more tests

* Apply nit suggestions from code review

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

* add checker of valid position embeddings type

* instantiate new layer norm layer with the right eps

* fix freeze_feature_encoder since it can be None in some cases

* add test same output in convert script

* restore wav2vec2conformer and add new model

* create processor and FE + clean

* add new model code

* fix convert script and set default config parameters

* correct model id paths

* make style

* make fix-copies and cleaning files

* fix copied from statements

* complete .md and fixe copies

* clean convert script argument defaults

* fix config parameters docstrings

* fix config docstring

* add copied from and enrich FE tests

* fix copied from and repo-consistency

* add autotokenizer

* make test input length shorter and change docstring code

* fix docstrings and copied from

* add add_adapter to ASR training example

* make testing of adapters more robust

* adapt to multi adapter layers

* refactor input_values->input_features and remove w2v2-bert feature extractor

* remove pretraining model

* remove depreciated features and useless lines

* add copied from and ignore statements to modeling tests

* remove pretraining model #2

* change import in convert script

* change default in convert script

* update readme and remove useless line

* Update tests/models/wav2vec2_bert/test_processor_wav2vec2_bert.py

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

* refactor BERT to Bert for consistency

* remove useless ignore copy statement

* add persistent to buffer in rotary

* add eps in LayerNorm init and remove copied from

* add adapter activation parameters and add copied from statements

* Fix copied statements and add unitest.skip reasons

* add copied statement in test_processor

* refactor processor

* make style

* replace numpy random by torch rand

* remove expected output CTC

* improve converting script with processor class

* Apply suggestions from code review

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

* remove gumbel class

* remove tests related to previously deleted class

* Update src/transformers/models/wav2vec2_bert/configuration_wav2vec2_bert.py

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

* correct typos

* remove uused parameters

* update processor to takes both text and audio

* update checkpoints

* update expected output and add ctc expected output

* add label_attention_mask

* replace pt with np in processor tests

* fix typo

* revert to behaviour with labels_attention_mask

---------

Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Use `LoggingLevel` context manager in 3 tests (#28575)

* inside with LoggingLevel

* remove is_flaky

---------

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

* Fix the documentation checkpoint for xlm-roberta-xl (#28567)

* Fix the documentation checkpoint for xlm-roberta-xl

* Improve docstring consistency

* [ASR Pipe] Update init to set model type and subsequently call parent init method (#28486)

* add image processor arg

* super

* rm args

* [Whisper Tok] Move token ids to CPU when computing offsets (#28485)

* move token ids to cpu

* check for torch attr

* [Whisper] Fix audio classification with weighted layer sum (#28563)

* fix

* tests

* fix test

* Making CTC training example more general (#28582)

* add w2v2bert compatibility

* Update examples/pytorch/speech-recognition/run_speech_recognition_ctc.py

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

---------

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

* Don't save `processor_config.json` if a processor has no extra attribute  (#28584)

* not save if empty

* fix

* fix

* fix

* fix

* fix

---------

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

* v4.38.dev.0

* Add w2v2bert to pipeline (#28585)

* generalize asr pipeline to fbank models

* change w2v2 pipeline output

* Update test_pipelines_automatic_speech_recognition.py

* feat: Sequential beam search (#26304)

* [Whisper] Finalize batched SOTA long-form generation (#27658)

* finalize

* make fix copies whisper

* [Tests] Make sure that we don't run tests mulitple times

* Update src/transformers/models/whisper/modeling_whisper.py

* [Tests] Make sure that we don't run tests mulitple times

* fix more

* improve

* improve

* improve further

* improve more

* improve

* fix more

* git commit and git push

* fix more

* fix more

* fix more

* New try

* Fix more whisper stuff

* Improve

* correct more

* correct more

* correct more

* Fix some tests

* Add more tests

* correct more

* correct more

* correct more

* push

* correct more

* Fix more

* Better

* without dec mask

* correct more

* clean

* save intermediate

* Fix more

* Fix VAD for large-v2

* Save new

* Correct more

* make cleaner

* correct tests

* correct src

* Finish

* Fix more

* Fix more

* finish

* Fix edge cases

* fix return_dict_in_generate

* fix all tests

* make style

* add docstrings

* add docstrings

* Fix logit processor

* make style

* fix pipeline test

* fix more style

* Apply suggestions from code review

* apply feedback Sanchit

* correct more

* Apply suggestions from code review

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

* Apply suggestions from code review

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

* correct more

* correct more

* correct more

* Fix staticmethod

* correct more

* fix

* fix slow tests

* make style

* fix tokenizer test

* fix tokenizer test

* Apply suggestions from code review

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

* finish

* finish

* revert kwargs change

---------

Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Fix wrong xpu device in DistributedType.MULTI_XPU mode (#28386)

* remove elif xpu

* remove redudant code

* [SigLIP] Don't pad by default (#28578)

First draft

* [`Llava`] Fix convert_llava_weights_to_hf.py script (#28570)

* Update convert_llava_weights_to_hf.py

Fix call to `tokenizer.add_tokens`

* Add special_tokens to tokenizer.add_tokens in convert_vipllava_weights_to_hf.py

* Allow add_tokens for ESM (#28535)

* Allow non-special tokens to be added

* Add test, fix token adding code

* Revert changes to id_to_token and token_to_id

* Update the ESM tokenizer to be a bit more standardized

* Update src/transformers/models/esm/tokenization_esm.py

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

---------

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

* Fix `_speculative_sampling` implementation (#28508)

* RWKV: raise informative exception when attempting to manipulate `past_key_values` (#28600)

* Fix auxiliary loss related code in transformers (#28406)

* [DETA] fix freeze/unfreeze function

* Update src/transformers/models/deta/modeling_deta.py

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

* Update src/transformers/models/deta/modeling_deta.py

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

* add freeze/unfreeze test case in DETA

* fix type

* fix typo 2

* fix : enable aux and enc loss in training pipeline

* Add unsynced variables from original DETA for training

* modification for passing CI test

* make style

* make fix

* manual make fix

* change deta_modeling_test of configuration 'two_stage' default to TRUE and minor change of dist checking

* remove print

* divide configuration in DetaModel and DetaForObjectDetection

* image smaller size than 224 will give topk error

* pred_boxes and logits should be equivalent to two_stage_num_proposals

* add missing part in DetaConfig

* Update src/transformers/models/deta/modeling_deta.py

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

* add docstring in configure and prettify TO DO part

* change distribute related code to accelerate

* Update src/transformers/models/deta/configuration_deta.py

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

* Update tests/models/deta/test_modeling_deta.py

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

* protect importing accelerate

* change variable name to specific value

* wrong import

* fix aux_loss in conditional_detr

* add test aux_loss

* add aux_loss test in deta and table_transformer

* fix yolos since it doesn't have auxiliary function

* fix maskformer auxiliary_loss related code

* make style

* change param 'auxiliary_loss' to 'use_auxiliary_loss'

* change param 'auxiliary_loss' to 'use_auxiliary_loss' in tests

* make style & fix-copies, also revert yolos related parameter

* revert variable name 'use_auxiliary_loss' to 'auxiliary_loss' due to DetrConfig

* revert variable name in yolos

* revert maskformer

* add aux_loss test in maskformer

* make style

* Update src/transformers/models/yolos/configuration_yolos.py

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

---------

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* [`GPTNeoX`] Fix BC issue with 4.36 (#28602)

* fix dtype issue

* add a test

* update copied from mentions

* nits

* fixup

* fix copies

* Apply suggestions from code review

* Fix id2label assignment in run_classification.py (#28590)

* Add missing key to TFLayoutLM signature (#28640)

Fix missing bbox in LayoutLM signature

* Avoid root logger's level being changed (#28638)

* avoid root logger's level being changed

---------

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

* Add config tip to custom model docs (#28601)

Add tip to custom model docs

* Fix lr_scheduler in no_trainer training scripts (#27872)

* Fix lr_scheduler

* Fix lr scheduler

* [`Llava`] Update convert_llava_weights_to_hf.py script (#28617)

* Update convert_llava_weights_to_hf.py script

* Remove config update of adding padding to `vocab_size` and `text_config.vocab_size` which causes `ValueError` exception.
* Remove keys that ends with `inv_freq` from the state dict.
* Add examples and instructions for creating `model_state_dict.bin` that can be used by the script.

* Update convert_llava_weights_to_hf.py

* Update convert_vipllava_weights_to_hf.py

* [`GPTNeoX`] Fix GPTNeoX + Flash Attention 2 issue (#28645)

Update modeling_gpt_neox.py

* Update image_processing_deformable_detr.py (#28561)

* Update image_processing_deformable_detr.py

* Changes after running make fix-copies

* [`SigLIP`] Only import tokenizer if sentencepiece available (#28636)

Only import class if sp available

* Fix phi model doc checkpoint (#28581)

Co-authored-by: Pashmina Cameron <11311835+pashminacameron@users.noreply.github.com>

* get default device through `PartialState().default_device` as it has been officially released (#27256)

get default device through `PartialState().default_device` as it has
been officially released

* integrations: fix DVCLiveCallback model logging (#28653)

* Enable safetensors conversion from PyTorch to other frameworks without the torch requirement (#27599)

* Initial commit

* Requirements & tests

* Tests

* Tests

* Rogue import

* Rogue torch import

* Cleanup

* Apply suggestions from code review

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* bfloat16 management

* Sanchit's comments

* Import shield

* apply suggestions from code review

* correct bf16

* rebase

---------

Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: sanchit-gandhi <sanchit@huggingface.co>

* Enable instantiating model with pretrained backbone weights (#28214)

* Enable instantiating model with pretrained backbone weights

* Update tests so backbone checkpoint isn't passed in

* Remove doc updates until changes made in modeling code

* Clarify pretrained import

* Update configs - docs and validation check

* Update src/transformers/utils/backbone_utils.py

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

* Clarify exception message

* Update config init in tests

* Add test for when use_timm_backbone=True

* Small test updates

---------

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

* `tensor_size` - fix copy/paste error msg typo (#28660)

Fix copy/paste error msg typo

* Fix windows err with checkpoint race conditions (#28637)

Fix windows err

* add dataloader prefetch factor in training args and trainer (#28498)

* add dataloader prefetch factor in training args and trainer

* remove trailing spaces

* prevent dataloader_num_workers == 0 and dataloader_prefetch_factor != None

dataloader_prefetch_factor works only when data is loaded in a different process as the main one. This commit adds the necessary checks to avoid having prefetch_factor set when there is no such process.

* Remove whitespaces in empty line

* Update src/transformers/training_args.py

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

* Update src/transformers/training_args.py

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

* Update src/transformers/training_args.py

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

* Update src/transformers/training_args.py

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

---------

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

* Support single token decode for `CodeGenTokenizer` (#28628)

convert token id to list in .decode()

* Remove deprecated eager_serving fn (#28665)

* Remove deprecated eager_serving fn

* Fix the input_signature docstring while I'm here

* fix a hidden bug of `GenerationConfig`, now the `generation_config.json` can be loaded successfully (#28604)

* fix a hidden bug of GenerationConfig

* keep `sort_keys=True` to maintain visibility

* Update src/transformers/generation/configuration_utils.py

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

* Update configuration_utils.py

in case `obj` is a list, check the items in the list

---------

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

* Update README_es.md (#28612)

Fixing grammatical errors in the text

* Exclude the load balancing loss of padding tokens in Mixtral-8x7B (#28517)

* fix the function load_balancing_loss_func in Mixtral_Moe to include attention_mask

* format code using black and ruff

* skip computing mask if attention_mask=None

* add tests for load balancing loss Mixtral-Moe

* fix assert loss is different in mixtral_test

* fix pad_leng

* use assertNotAlmostEqual and print to debug

* remove print for debug

* minor updates

* reduce rtol and atol

* Use save_safetensor to disable safe serialization for XLA (#28669)

* Use save_safetensor to disable safe serialization for XLA

https://github.com/huggingface/transformers/issues/28438

* Style fixup

* Add back in generation types (#28681)

* [docs] DeepSpeed (#28542)

* config

* optim

* pre deploy

* deploy

* save weights, memory, troubleshoot, non-Trainer

* done

* Improved type hinting for all attention parameters (#28479)

* Changed type hinting for all attention inputs to 'Optional[Tuple[torch.FloatTensor,...]] = None'

* Fixed the ruff formatting issue

* fixed type hinting for all hidden_states to 'Optional[Tuple[torch.FloatTensor, ...]] = None'

* Changed type hinting in these 12 scripts modeling_dpr.py,modeling_nat.py,idefics/vision.py,modeling_tf_dpr.py,modeling_luke.py,modeling_swin.py,modeling_tf_swin.py,modeling_blip.py,modeling_tf_blip.py,modeling_donut_swin.py,modeling_dinat.py,modeling_swinv2.py

* test fail update

* fixed type hinting for these 15 scripts modeling_xlnet.py,modeling_tf_xlnet.py,modeling_led.py,modeling_tf_led.py,modleing_rwkv.py,modeling_dpt.py,modeling_tf_cvt.py,modeling_clip.py,modeling_flax_clip.py,modeling_tf_clip.py,modeling_longformer.py,modeling_tf_longformer.py,modeling_siglip.py,modeling_clap.py,modeling_git.py

* Changed type hinting in these 12 scripts modeling_dpr.py,modeling_nat.py,idefics/vision.py,modeling_tf_dpr.py,modeling_luke.py,modeling_swin.py,modeling_tf_swin.py,modeling_blip.py,modeling_tf_blip.py,modeling_donut_swin.py,modeling_dinat.py,modeling_swinv2.py

* test fail update

* Removed the myvenv file

* Fixed type hinting for these 8 scripts modeling_tvlt.py,modeling_sam.py,modeling_tf_sam.py,modeling_tvp.py,modeling_rag.py,modeling_tf_rag.py,modeling_tf_xlm.py,modeling_xlm.py

* improve efficient training on CPU documentation (#28646)

* update doc

* revert

* typo fix

* refine

* add dtypes

* Update docs/source/en/perf_train_cpu.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/perf_train_cpu.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/perf_train_cpu.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* no comma

* use avx512-vnni

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* [docs] Fix doc format (#28684)

* fix hfoptions

* revert changes to other files

* fix

* Add Depth Anything (#28654)

* First draft

* More improvements

* More improvements

* More improvements

* More improvements

* Add docs

* Remove file

* Add copied from

* Address comments

* Address comments

* Address comments

* Fix style

* Update docs

* Convert all checkpoints, add integration test

* Rename checkpoints

* Add pretrained backbone attributes

* Fix default config

* Address comment

* Add figure to docs

* Fix bug thanks to @xenova

* Update conversion script

* Fix integration test

* [`chore`] Add missing space in warning (#28695)

Add missing space in warning

* Improve Backbone API docs (#28666)

Update backbones.md

* Update question_answering.md (#28694)

fix typo:

from:

 "model = TFAutoModelForQuestionAnswering("distilbert-base-uncased")"

to:
model = TFAutoModelForQuestionAnswering.from_pretrained("distilbert-base-uncased")

* [`Vilt`] align input and model dtype in the ViltPatchEmbeddings forward pass  (#28633)

align dtype

* [`docs`] Improve visualization for vertical parallelism (#28583)

The documentation says "We refer to this Model parallelism as “Vertical” because of how models are typically visualized.", but then visualizes the model horizontally. This change visualizes the model indeed vertically.

* Don't fail when `LocalEntryNotFoundError` during `processor_config.json` loading (#28709)

* fix

---------

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

* Fix duplicate & unnecessary flash attention warnings (#28557)

* fix duplicate & unnecessary flash warnings

* trigger ci

* warning_once

* if/else order

---------

Co-authored-by: Your Name <you@example.com>

* support PeftMixedModel signature inspect (#28321)

* support PeftMixedModel signature inspect

* import PeftMixedModel only peft>=0.7.0

* Update src/transformers/trainer.py

Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update src/transformers/trainer.py

Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update src/transformers/trainer.py

Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update src/transformers/trainer.py

Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update src/transformers/trainer.py

Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update src/transformers/trainer.py

Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* fix styling

* Update src/transformers/trainer.py

Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update src/transformers/trainer.py

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

* style fixup

* fix note

---------

Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix: corrected misleading log message in save_pretrained function (#28699)

* [`docs`] Update preprocessing.md (#28719)

* Update preprocessing.md

adjust ImageProcessor link to working target (same as in lower section of file)

* Update preprocessing.md

* Initialize _tqdm_active with hf_hub_utils.are_progress_bars_disabled(… (#28717)

Initialize _tqdm_active with hf_hub_utils.are_progress_bars_disabled() to respect HF_HUB_DISABLE_PROGRESS_BARS

It seems like enable_progress_bar() and disable_progress_bar() sync up with huggingface_hub, but the initial value is always True. This changes will make sure the user's preference is respected implicity on initialization.

* Fix `weights_only` (#28725)

fix

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

* Stop confusing the TF compiler with ModelOutput objects (#28712)

* Stop confusing the TF compiler with ModelOutput objects

* Stop confusing the TF compiler with ModelOutput objects

* fix: suppress `GatedRepoError` to use cache file (fix #28558). (#28566)

* fix: suppress `GatedRepoError` to use cache file (fix #28558).

* move condition_to_return parameter back to outside.

* Unpin pydantic (#28728)

* try pydantic v2

* try pydantic v2

---------

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

* [docs] Fix datasets in guides (#28715)

* change datasets

* fix

* [Flax] Update no init test for Flax v0.7.1 (#28735)

* Falcon: removed unused function (#28605)

* Generate: deprecate old src imports (#28607)

* [`Siglip`] protect from imports if sentencepiece not installed (#28737)

[Siglip] protect from imports if sentencepiece not installed

* Add serialization logic to pytree types (#27871)

* Add serialized type name to pytrees

* Modify context

* add serde test

* Fix `DepthEstimationPipeline`'s docstring (#28733)

* fix

* fix

* Fix

---------

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

* Fix input data file extension in examples (#28741)

* [Docs] Fix Typo in English & Japanese CLIP Model Documentation (TMBD -> TMDB) (#28751)

* [Docs] Fix Typo in English CLIP model_doc

* [Docs] Fix Typo in Japanese CLIP model_doc

* PatchtTST and PatchTSMixer fixes (#28083)

* :bug: fix .max bug

* remove prediction_length from regression output dimensions

* fix parameter names, fix output names, update tests

* ensure shape for PatchTST

* ensure output shape for PatchTSMixer

* update model, batch, and expected for regression distribution test

* update test expected

Signed-off-by: Wesley M. Gifford <wmgifford@us.ibm.com>

* Update tests/models/patchtst/test_modeling_patchtst.py

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

* Update tests/models/patchtst/test_modeling_patchtst.py

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

* Update tests/models/patchtst/test_modeling_patchtst.py

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

* Update src/transformers/models/patchtsmixer/modeling_patchtsmixer.py

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

* Update tests/models/patchtsmixer/test_modeling_patchtsmixer.py

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

* Update tests/models/patchtsmixer/test_modeling_patchtsmixer.py

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

* standardize on patch_length

Signed-off-by: Wesley M. Gifford <wmgifford@us.ibm.com>

* Update tests/models/patchtsmixer/test_modeling_patchtsmixer.py

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

* Update tests/models/patchtsmixer/test_modeling_patchtsmixer.py

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

* Make arguments more explicit

Signed-off-by: Wesley M. Gifford <wmgifford@us.ibm.com>

* adjust prepared inputs

Signed-off-by: Wesley M. Gifford <wmgifford@us.ibm.com>

---------

Signed-off-by: Wesley M. Gifford <wmgifford@us.ibm.com>
Co-authored-by: Wesley M. Gifford <wmgifford@us.ibm.com>
Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Enable Gradient Checkpointing in Deformable DETR (#28686)

* Enabled gradient checkpointing in Deformable DETR

* Enabled gradient checkpointing in Deformable DETR encoder

* Removed # Copied from headers in modeling_deta.py to break dependence on Deformable DETR code

* small doc update for CamemBERT (#28644)

* Pin pytest version <8.0.0 (#28758)

* Pin pytest version <8.0.0

* Update setup.py

* make deps_table_update

* Mark test_constrained_beam_search_generate as flaky (#28757)

* Make test_constrained_beam_search_generate as flaky

* Update tests/generation/test_utils.py

* Fix typo of `Block`. (#28727)

* [Whisper] Make tokenizer normalization public (#28136)

* [Whisper] Make tokenizer normalization public

* add to docs

* Support saving only PEFT adapter in checkpoints when using PEFT + FSDP (#28297)

* Update trainer.py

* Revert "Update trainer.py"

This reverts commit 0557e2cc9effa3a41304322032239a3874b948a7.

* Make trainer.py use adapter_only=True when using FSDP + PEFT

* Support load_best_model with adapter_only=True

* Ruff format

* Inspect function args for save_ load_ fsdp utility functions and only pass adapter_only=True if they support it

* Add French translation: french README.md (#28696)

* doc: french README

Signed-off-by: ThibaultLengagne <thibaultl@padok.fr>

* doc: Add Depth Anything

Signed-off-by: ThibaultLengagne <thibaultl@padok.fr>

* doc: Add french link in other docs

Signed-off-by: ThibaultLengagne <thibaultl@padok.fr>

* doc: Add missing links in fr docs

* doc: fix several mistakes in translation

Signed-off-by: ThibaultLengagne <thibaultl@padok.fr>

---------

Signed-off-by: ThibaultLengagne <thibaultl@padok.fr>
Co-authored-by: Sarapuce <alexandreh@padok.fr>

* Don't allow passing `load_in_8bit` and `load_in_4bit` at the same time (#28266)

* Update quantization_config.py

* Style

* Protect from setting directly

* add tests

* Update tests/quantization/bnb/test_4bit.py

Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

---------

Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Move CLIP _no_split_modules to CLIPPreTrainedModel (#27841)

Add _no_split_modules to CLIPModel

* `HfQuantizer` class for quantization-related stuff in `modeling_utils.py` (#26610)

* squashed earlier commits for easier rebase

* rm rebase leftovers

* 4bit save enabled @quantizers

* TMP gptq test use exllama

* fix AwqConfigTest::test_wrong_backend for A100

* quantizers AWQ fixes

* _load_pretrained_model low_cpu_mem_usage branch

* quantizers style

* remove require_low_cpu_mem_usage attr

* rm dtype arg from process_model_before_weight_loading

* rm config_origin from Q-config

* rm inspect from q_config

* fixed docstrings in QuantizationConfigParser

* logger.warning fix

* mv is_loaded_in_4(8)bit to BnbHFQuantizer

* is_accelerate_available error msg fix in quantizer

* split is_model_trainable in bnb quantizer class

* rm llm_int8_skip_modules as separate var in Q

* Q rm todo

* fwd ref to HFQuantizer in type hint

* rm note re optimum.gptq.GPTQQuantizer

* quantization_config in __init__ simplified

* replaced NonImplemented with  create_quantized_param

* rm load_in_4/8_bit deprecation warning

* QuantizationConfigParser refactoring

* awq-related minor changes

* awq-related changes

* awq config.modules_to_not_convert

* raise error if no q-method in q-config in args

* minor cleanup

* awq quantizer docstring

* combine common parts in bnb process_model_before_weight_loading

* revert test_gptq

* .process_model_ cleanup

* restore dict config warning

* removed typevars in quantizers.py

* cleanup post-rebase 16 jan

* QuantizationConfigParser classmethod refactor

* rework of handling of unexpected aux elements of bnb weights

* moved q-related stuff from save_pretrained to quantizers

* refactor v1

* more changes

* fix some tests

* remove it from main init

* ooops

* Apply suggestions from code review

Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* fix awq issues

* fix

* fix

* fix

* fix

* fix

* fix

* add docs

* Apply suggestions from code review

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Apply suggestions from code review

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

* Update docs/source/en/hf_quantizer.md

* address comments

* fix

* fixup

* Update src/transformers/modeling_utils.py

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

* Update src/transformers/modeling_utils.py

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

* address final comment

* update

* Update src/transformers/quantizers/base.py

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

* Update src/transformers/quantizers/auto.py

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

* fix

* add kwargs update

* fixup

* add `optimum_quantizer` attribute

* oops

* rm unneeded file

* fix doctests

---------

Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* [`HfQuantizer`] Move it to "Developper guides" (#28768)

Update _toctree.yml

* Use Conv1d for TDNN (#25728)

* use conv for tdnn

* run make fixup

* update TDNN

* add PEFT LoRA check

* propagate tdnn warnings to others

* add missing imports

* update TDNN in wav2vec2_bert

* add missing imports

* Fix transformers.utils.fx compatibility with torch<2.0 (#28774)

guard sdpa on torch>=2.0

* Further pin pytest version (in a temporary way) (#28780)

fix

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

* [`Backbone`] Use `load_backbone` instead of `AutoBackbone.from_config` (#28661)

* Enable instantiating model with pretrained backbone weights

* Remove doc updates until changes made in modeling code

* Use load_backbone instead

* Add use_timm_backbone to the model configs

* Add missing imports and arguments

* Update docstrings

* Make sure test is properly configured

* Include recent DPT updates

* Task-specific pipeline init args (#28439)

* Abstract out pipeline init args

* Address PR comments

* Reword

* BC PIPELINE_INIT_ARGS

* Remove old arguments

* Small fix

* Add tf_keras imports to prepare for Keras 3 (#28588)

* Port core files + ESM (because ESM code is odd)

* Search-replace in modelling code

* Fix up transfo_xl as well

* Fix other core files + tests (still need to add correct import to tests)

* Fix cookiecutter

* make fixup, fix imports in some more core files

* Auto-add imports to tests

* Cleanup, add imports to sagemaker tests

* Use correct exception for importing tf_keras

* Fixes in modeling_tf_utils

* make fixup

* Correct version parsing code

* Ensure the pipeline tests correctly revert to float32 after each test

* Ensure the pipeline tests correctly revert to float32 after each test

* More tf.keras -> keras

* Add dtype cast

* Better imports of tf_keras

* Add a cast for tf.assign, just in case

* Fix callback imports

* Pin Torch to <2.2.0 (#28785)

* Pin torch to <2.2.0

* Pin torchvision and torchaudio as well

* Playing around with versions to see if this helps

* twiddle something to restart the CI

* twiddle it back

* Try changing the natten version

* make fixup

* Revert "Try changing the natten version"

This reverts commit de0d6592c35dc39ae8b5a616c27285db28262d06.

* make fixup

* fix fix fix

* fix fix fix

---------

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

* [`bnb`] Fix bnb slow tests (#28788)

fix bnb slow tests

* Prevent MLflow exception from disrupting training (#28779)

Modified MLflow logging metrics from synchronous to asynchronous

Co-authored-by: codiceSpaghetti <alessio.ser@hotmail.it>

* don't initialize the output embeddings if we're going to tie them to input embeddings (#28192)

* test that tied output embeddings aren't initialized on load

* don't initialize the output embeddings if we're going to tie them to the input embeddings

* [`HFQuantizer`] Remove `check_packages_compatibility` logic (#28789)

remove `check_packages_compatibility` logic

* [Whisper] Refactor forced_decoder_ids & prompt ids (#28687)

* up

* Fix more

* Correct more

* Fix more tests

* fix fast tests

* Fix more

* fix more

* push all files

* finish all

* make style

* Fix timestamp wrap

* make style

* make style

* up

* up

* up

* Fix lang detection behavior

* Fix lang detection behavior

* Add lang detection test

* Fix lang detection behavior

* make style

* Update src/transformers/models/whisper/generation_whisper.py

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

* better error message

* make style tests

* add warning

---------

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

* Resolve DeepSpeed cannot resume training with PeftModel (#28746)

* fix: resolve deepspeed resume peft model issues

* chore: update something

* chore: update model instance pass into is peft model checks

* chore: remove hard code value to tests

* fix: format code

* canonical repos moves (#28795)

* canonical repos moves

* Style

---------

Co-authored-by: Lysandre <lysandre@huggingface.co>

* Wrap Keras methods to support BatchEncoding (#28734)

* Shim the Keras methods to support BatchEncoding

* Extract everything to a convert_batch_encoding function

* Convert BatchFeature too (thanks Amy)

* tf.keras -> keras

* Flax mistral (#26943)

* direct copy from llama work

* mistral modules forward pass working

* flax mistral forward pass with sliding window

* added tests

* added layer collection approach

* Revert "added layer collection approach"

This reverts commit 0e2905bf2236ec323163fc1a9f0c016b21aa8b8f.

* Revert "Revert "added layer collection approach""

This reverts commit fb17b6187ac5d16da7c461e1130514dc3d137a43.

* fixed attention outputs

* added mistral to init and auto

* fixed import name

* fixed layernorm weight dtype

* freeze initialized weights

* make sure conversion consideres bfloat16

* added backend

* added docstrings

* added cache

* fixed sliding window causal mask

* passes cache tests

* passed all tests

* applied make style

* removed commented out code

* applied fix-copies ignored other model changes

* applied make fix-copies

* removed unused functions

* passed generation integration test

* slow tests pass

* fixed slow tests

* changed default dtype from jax.numpy.float32 to float32 for docstring check

* skip cache test  for FlaxMistralForSequenceClassification since if pad_token_id in input_ids it doesn't score previous input_ids

* updated checkpoint since from_pt not included

* applied black style

* removed unused args

* Applied styling and fixup

* changed checkpoint for doc back

* fixed rf after adding it to hf hub

* Add dummy ckpt

* applied styling

* added tokenizer to new ckpt

* fixed slice format

* fix init and slice

* changed ref for placeholder TODO

* added copies from Llama

* applied styling

* applied fix-copies

* fixed docs

* update weight dtype reconversion for sharded weights

* removed Nullable input ids

* Removed unnecessary output attentions in Module

* added embedding weight initialziation

* removed unused past_key_values

* fixed deterministic

* Fixed RMS Norm and added copied from

* removed input_embeds

* applied make style

* removed nullable input ids from sequence classification model

* added copied from GPTJ

* added copied from Llama on FlaxMistralDecoderLayer

* added copied from to FlaxMistralPreTrainedModel methods

* fix test deprecation warning

* freeze gpt neox random_params and fix copies

* applied make style

* fixed doc issue

* skipped docstring test to allign # copied from

* applied make style

* removed FlaxMistralForSequenceClassification

* removed unused padding_idx

* removed more sequence classification

* removed sequence classification

* applied styling and consistency

* added copied from in tests

* removed sequence classification test logic

* applied styling

* applied make style

* removed freeze and fixed copies

* undo test change

* changed repeat_kv to tile

* fixed to key value groups

* updated copyright year

* split casual_mask

* empty to rerun failed pt_flax_equivalence test FlaxWav2Vec2ModelTest

* went back to 2023 for tests_pr_documentation_tests

* went back to 2024

* changed tile to repeat

* applied make style

* empty for retry on Wav2Vec2

* DeepSpeed: hardcode `torch.arange` dtype on `float` usage to avoid incorrect initialization (#28760)

* Add artifact name in job step to maintain job / artifact correspondence (#28682)

* avoid using job name

* apply to other files

---------

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

* Split daily CI using 2 level matrix (#28773)

* update / add new workflow files

* Add comment

* Use env.NUM_SLICES

* use scripts

* use scripts

* use scripts

* Fix

* using one script

* Fix

* remove unused file

* update

* fail-fast: false

* remove unused file

* fix

* fix

* use matrix

* inputs

* style

* update

* fix

* fix

* no model name

* add doc

* allow args

* style

* pass argument

---------

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

* [docs] Correct the statement in the docstirng of compute_transition_scores in generation/utils.py (#28786)

* Adding [T5/MT5/UMT5]ForTokenClassification (#28443)

* Adding [T5/MT5/UMT5]ForTokenClassification

* Add auto mappings for T5ForTokenClassification and variants

* Adding ForTokenClassification to the list of models

* Adding attention_mask param to the T5ForTokenClassification test

* Remove outdated comment in test

* Adding EncoderOnly and Token Classification tests for MT5 and UMT5

* Fix typo in umt5 string

* Add tests for all the existing MT5 models

* Fix wrong comment in dependency_versions_table

* Reverting change to common test for _keys_to_ignore_on_load_missing

The test is correctly picking up redundant keys in _keys_to_ignore_on_load_missing.

* Removing _keys_to_ignore_on_missing from MT5 since the key is not used in the model

* Add fix-copies to MT5ModelTest

* Make `is_torch_bf16_available_on_device` more strict (#28796)

fix

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

* Fix symbolic_trace with kv cache (#28724)

* fix symbolic_trace with kv cache

* comment & better test

* Add tip on setting tokenizer attributes (#28764)

* Add tip on setting tokenizer attributes

* Grammar

* Remove the bit that was causing doc builds to fail

* enable graident checkpointing in DetaObjectDetection and add tests in Swin/Donut_Swin (#28615)

* enable graident checkpointing in DetaObjectDetection

* fix missing part in original DETA

* make style

* make fix-copies

* Revert "make fix-copies"

This reverts commit 4041c86c29248f1673e8173b677c20b5a4511358.

* remove fix-copies of DetaDecoder

* enable swin gradient checkpointing

* fix gradient checkpointing in donut_swin

* add tests for deta/swin/donut

* Revert "fix gradient checkpointing in donut_swin"

This reverts commit 1cf345e34d3cc0e09eb800d9895805b1dd9b474d.

* change supports_gradient_checkpointing pipeline to PreTrainedModel

* Revert "add tests for deta/swin/donut"

This reverts commit 6056ffbb1eddc3cb3a99e4ebb231ae3edf295f5b.

* Revert "Revert "fix gradient checkpointing in donut_swin""

This reverts commit 24e25d0a14891241de58a0d86f817d0b5d2a341f.

* Simple revert

* enable deformable detr gradient checkpointing

* add gradient in encoder

* [docs] fix some bugs about parameter description (#28806)

Co-authored-by: p_spozzhang <p_spozzhang@tencent.com>

* Add models from deit (#28302)

* Add modelss

* Add 2 more models

* add models to tocrree

* Add modles

* Update docs/source/ja/model_doc/detr.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/ja/model_doc/deit.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/ja/model_doc/deplot.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* fix bugs

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* [docs] Backbone (#28739)

* backbones

* fix path

* fix paths

* fix code snippet

* fix links

* [docs] HfQuantizer (#28820)

* tidy

* fix path

* [Docs] Fix spelling and grammar mistakes (#28825)

* Fix typos and grammar mistakes in docs and examples

* Fix typos in docstrings and comments

* Fix spelling of `tokenizer` in model tests

* Remove erroneous spaces in decorators

* Remove extra spaces in Markdown link texts

* Explicitly check if token ID's are None in TFBertTokenizer constructor (#28824)

Add an explicit none-check, since token ids can be 0

* Add missing None check for hf_quantizer (#28804)

* Add missing None check for hf_quantizer

* Add test, fix logic.

* make style

* Switch test model to Mistral

* Comment

* Update tests/test_modeling_utils.py

---------

Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Fix issues caused by natten (#28834)

try

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

* fix / skip (for now) some tests before switch to torch 2.2 (#28838)

* fix / skip some tests before we can switch to torch 2.2

* style

---------

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

* Use `-v` for `pytest` on CircleCI  (#28840)

use -v in pytest

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

* Reduce GPU memory usage when using FSDP+PEFT (#28830)

support FSDP+PEFT

* Mark `test_encoder_decoder_model_generate` for `vision_encoder_deocder` as flaky (#28842)

Mark test as flaky

* Bump dash from 2.3.0 to 2.15.0 in /examples/research_projects/decision_transformer (#28845)

Bump dash in /examples/research_projects/decision_transformer

Bumps [dash](https://github.com/plotly/dash) from 2.3.0 to 2.15.0.
- [Release notes](https://github.com/plotly/dash/releases)
- [Changelog](https://github.com/plotly/dash/blob/dev/CHANGELOG.md)
- [Commits](https://github.com/plotly/dash/compare/v2.3.0...v2.15.0)

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

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

* Support custom scheduler in deepspeed training (#26831)

Reuse trainer.create_scheduler to create scheduler for deepspeed

* [Docs] Fix bad doc: replace save with logging (#28855)

Fix bad doc: replace save with logging

* Ability to override clean_code_for_run (#28783)

* Add clean_code_for_run function

* Call clean_code_for_run from agent method

* [WIP] 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>

---------

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

* [`Doc`] update contribution guidelines (#28858)

update guidelines

* Correct wav2vec2-bert inputs_to_logits_ratio (#28821)

* Correct wav2vec2-bert inputs_to_logits_ratio

* correct ratio

* correct ratio, clean asr pipeline

* refactor on one line

* Image Feature Extraction pipeline (#28216)

* Draft pipeline

* Fixup

* Fix docstrings

* Update doctest

* Update pipeline_model_mapping

* Update docstring

* Update tests

* Update src/transformers/pipelines/image_feature_extraction.py

Co-authored-by: Omar Sanseviero <osanseviero@gmail.com>

* Fix docstrings - review comments

* Remove pipeline mapping for composite vision models

* Add to pipeline tests

* Remove for flava (multimodal)

* safe pil import

* Add requirements for pipeline run

* Account for super slow efficientnet

* Review comments

* Fix tests

* Swap order of kwargs

* Use build_pipeline_init_args

* Add back FE pipeline for Vilt

* Include image_processor_kwargs in docstring

* Mark test as flaky

* Update TODO

* Update tests/pipelines/test_pipelines_image_feature_extraction.py

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

* Add license header

---------

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

* ClearMLCallback enhancements: support multiple runs and handle logging better (#28559)

* add clearml tracker

* support multiple train runs

* remove bad code

* add UI entries for config/hparams overrides

* handle models in different tasks

* run ruff format

* tidy code based on code review

---------

Co-authored-by: Eugen Ajechiloae <eugenajechiloae@gmail.com>

* Do not use mtime for checkpoint rotation. (#28862)

Resolve https://github.com/huggingface/transformers/issues/26961

* Adds LlamaForQuestionAnswering class in modeling_llama.py along with AutoModel Support  (#28777)

* This is a test commit

* testing commit

* final commit with some changes

* Removed copy statement

* Fixed formatting issues

* Fixed error added past_key_values in the forward method

* Fixed a trailing whitespace. Damn the formatting rules are strict

* Added the copy statement

* Bump cryptography from 41.0.2 to 42.0.0 in /examples/research_projects/decision_transformer (#28879)

Bump cryptography in /examples/research_projects/decision_transformer

Bumps [cryptography](https://github.com/pyca/cryptography) from 41.0.2 to 42.0.0.
- [Changelog](https://github.com/pyca/cryptography/blob/main/CHANGELOG.rst)
- [Commits](https://github.com/pyca/cryptography/compare/41.0.2...42.0.0)

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

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

* [Docs] Update project names and links in awesome-transformers (#28878)

Update project names and repository links in awesome-transformers

* Fix LongT5ForConditionalGeneration initialization of lm_head (#28873)

* Raise error when using `save_only_model` with `load_best_model_at_end` for DeepSpeed/FSDP (#28866)

* Raise error when using `save_only_model` with `load_best_model_at_end` for DeepSpeed/FSDP

* Update trainer.py

* Fix `FastSpeech2ConformerModelTest` and skip it on CPU (#28888)

* fix

* fix

---------

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

* Revert "[WIP] Hard error when ignoring tensors." (#28898)

Revert "[WIP] Hard error when ignoring tensors. (#27484)"

This reverts commit 2da28c4b41bba23969a8afe97c3dfdcbc47a57dc.

* unpin torch (#28892)

* unpin torch

* check

* check

* check

---------

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

* Explicit server error on gated model (#28894)

* [Docs] Fix backticks in inline code and documentation links (#28875)

Fix backticks in code blocks and documentation links

* Hotfix - make `torchaudio` get the correct version in `torch_and_flax_job` (#28899)

* check

* check

* check

---------

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

* [Docs] Add missing language options and fix broken links (#28852)

* Add missing entries to the language selector

* Add links to the Colab and AWS Studio notebooks for ONNX

* Use anchor links in CONTRIBUTING.md

* Fix broken hyperlinks due to spaces

* Fix links to OpenAI research articles

* Remove confusing footnote symbols from author names, as they are also considered invalid markup

* fix: Fixed the documentation for `logging_first_step` by removing "evaluate" (#28884)

Fixed the documentation for logging_first_step by removing evaluate.

* fix Starcoder FA2 implementation (#28891)

* Fix Keras scheduler import so it works for older versions of Keras (#28895)

Fix our schedule import so it works for older versions of Keras

* ⚠️ Raise `Exception` when trying to generate 0 tokens ⚠️ (#28621)

* change warning to exception

* Update src/transformers/generation/utils.py

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* validate `max_new_tokens` > 0 in `GenerationConfig`

* fix truncation test parameterization in `TextGenerationPipelineTests`

---------

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update the cache number (#28905)

* fix

* fix

* fix

---------

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

* Add npu device for pipeline (#28885)

add npu device for pipeline

Co-authored-by: unit_test <test@unit.com>

* [Docs] Fix placement of tilde character (#28913)

Fix placement of tilde character

* [Docs] Revert translation of '@slow' decorator (#28912)

* Fix utf-8 yaml load for marian conversion to pytorch in Windows (#28618)

Fix utf-8 yaml in marian conversion

* [`Core generation`] Adds support for static KV cache (#27931)

Co-authored-by: fxmarty <9808326+fxmarty@users.noreply.github.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Remove dead TF loading code (#28926)

Remove dead code

* fix: torch.int32 instead of torch.torch.int32 (#28883)

* pass kwargs in stopping criteria list (#28927)

* Support batched input for decoder start ids (#28887)

* support batched input for decoder start ids

* Fix typos

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* minor changes

* fix: decoder_start_id as list

* empty commit

* empty commit

* empty commit

* empty commit

* empty commit

* empty commit

* empty commit

* empty commit

* empty commit

---------

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* [Docs] Fix broken links and syntax issues (#28918)

* Fix model documentation links in attention.md

* Fix external link syntax

* Fix target anchor names of section links

* Fix copyright statement comments

* Fix documentation headings

* Fix max_position_embeddings default value for llama2 to 4096 #28241 (#28754)

* Changed max_position_embeddings default value from 2048 to 4096

* force push

* Fixed formatting issues. Fixed missing argument in write_model.

* Reverted to the default value 2048 in the Llama config. Added comments for the llama_version argument.

* Fixed issue with default value value of max_position_embeddings in docstring

* Updated help message for llama versions

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

---------

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

* Fix a wrong link to CONTRIBUTING.md section in PR template (#28941)

* Fix type annotations on neftune_noise_alpha and fsdp_config TrainingArguments parameters (#28942)

* [i18n-de] Translate README.md to German (#28933)

* Translate README.md to German

* Add links to README_de.md

* Remove invisible characters in README

* Change to a formal tone and fix punctuation marks

* [Nougat] Fix pipeline (#28242)

* Fix pipeline

* Remove print statements

* Address comments

* Address issue

* Remove unused imports

* [Docs] Update README and default pipelines (#28864)

* Update README and docs

* Update README

* Update README

* Convert `torch_dtype` as `str` to actual torch data type (i.e. "float16" …to `torch.float16`) (#28208)

* Convert torch_dtype as str to actual torch data type (i.e. "float16" to torch.float16)

* Check if passed torch_dtype is an attribute in torch

* Update src/transformers/pipelines/__init__.py

Check type via isinstance

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

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

* [`pipelines`] updated docstring with vqa alias (#28951)

updated docstring with vqa alias

* Tests: tag `test_save_load_fast_init_from_base` as flaky (#28930)

* Updated requirements for image-classification samples: datasets>=2.14.0 (#28974)

Updated datasets requirements. Need a package version >= 2.14.0

* Always initialize tied output_embeddings if it has a bias term (#28947)

Continue to initialize tied output_embeddings if it has a bias term

The bias term is not tied, and so will need to be initialized accordingly.

* Clean up staging tmp checkpoint directory (#28848)

clean up remaining tmp checkpoint dir

Signed-off-by: woshiyyya <xiaoyunxuan1998@gmail.com>

* [Docs] Add language identifiers to fenced code blocks (#28955)

Add language identifiers to code blocks

* [Docs] Add video section (#28958)

Add video section

* [i18n-de] Translate CONTRIBUTING.md to German (#28954)

* Translate contributing.md to German

* Fix formatting issues in contributing.md

* Address review comments

* Fix capitalization

* [`NllbTokenizer`] refactor with added tokens decoder (#27717)

* refactor with addedtokens decoder

* style

* get rid of lang code to id

* style

* keep some things for BC

* update tests

* add the mask token at the end of the vocab

* nits

* nits

* fix final tests

* style

* nits

* Update src/transformers/models/nllb/tokenization_nllb_fast.py

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

* nits

* style?

* Update src/transformers/convert_slow_tokenizer.py

* make it a tad bit more custom

* ruff please stop
Co-Authored by avidale

<dale.david@mail.ru>

* Update
Co-authored-by: avidale
<dale.david@mail.ru>

* Update
Co-authored-by: avidale <dale.david@mail.ru>

* oupts

* ouft

* nites

* test

* fix the remaining failing tests

* style

* fix failing test

* ficx other test

* temp dir + test the raw init

* update test

* style

---------

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

* Add sudachi_projection option to BertJapaneseTokenizer (#28503)

* add sudachi_projection option

* Upgrade sudachipy>=0.6.8

* add a test case for sudachi_projection

* Compatible with older versions of SudachiPy

* make fixup

* make style

* error message for unidic download

* revert jumanpp test cases

* format options for sudachi_projection

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

* format options for sudachi_split_mode and sudachi_dict_type

* comment

* add tests for full_tokenizer kwargs

* pass projection arg directly

* require_sudachi_projection

* make style

* revert upgrade sudachipy

* check is_sudachi_projection_available()

* revert dependency_version_table and bugfix

* style format

* simply raise ImportError

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

* simply raise ImportError

---------

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

* Static Cache: load models with MQA or GQA (#28975)

* Update configuration_llama.py: fixed broken link (#28946)

* Update co…
@canberk17
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Hi there @patrickvonplaten I started getting the following error when I tried finetune whisper-tiny model, which points me to this PR here :

Due to a bug fix in #28687 transcription using a multilingual Whisper will default to language detection followed by transcription instead of translation to English.This might be a breaking change for your use case. If you want to instead always translate your audio to English, make sure to pass language='en'.

ValueError: Multiple languages detected when trying to predict the most likely target language for transcription. It is currently not supported to transcribe to different languages in a single batch. Please make sure to either force a single language by passing language='...' or make sure all input audio is of the same language.

I am simply following the instructions here by @sanchit-gandhi :
https://huggingface.co/blog/fine-tune-whisper#prepare-environment

I used exactly the same code here ( https://colab.research.google.com/drive/1Ffd2ZnaaRfM02A0QiW08blufw0qFdlIu?usp=sharing ) previously to push same model (https://huggingface.co/ckandemir/whisper-tiny-tr) ,and this week I wanted to experiment with different parameters started getting the the error above, I was wondering if you could help me understand the issue here.

@sanchit-gandhi
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Hey @canberk17 - this can be fixed by specifying the language in the generation_config as follows:

model.generation_config.language = "<|hi|>"  # for hindi
model.generation_config.task = "transcribe"

Provided you run these two lines before calling trainer.train(), you'll de-activate automatic language detection during inference and be able to run the code as before. I'll update the blog post + Colab to reflect these changes!

@canberk17
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Hi @sanchit-gandhi , thank you so much for clarifying !

@Kimahriman
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I just started hitting the

ValueError: Multiple languages detected when trying to predict the most likely target language for transcription. It is currently not supported to transcribe to different languages in a single batch. Please make sure to either force a single language by passing language='...' or make sure all input audio is of the same language.

error as well due to the change in behavior. Setting language='en' seems to fix this, however when using return_language=True I now get all the returned languages as English, and not the source language(s) that I was getting previously. Is that expected?

@Kimahriman
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Okay I think I get it now, since you're tracking init_tokens as a list of tokens, you're just requiring all items in a batch to have the same language somewhat arbitrarily. Any plans to address that? That's a pretty major breaking change that prevents batched inference on mixed language audio, especially when Whisper is our method for detecting the audio language. Can the language tokens just be tracked as a batch tensor instead of a single token, and that would fix the whole issue?

What I can't figure out is exactly how this worked before. I see the forced_decoder_ids gets a (1, None) entry for the language token, but I can't see where the None is handled when creating the init_tokens. I see it might get handled in the ForceTokensLogitsProcessor? But it seems like it would err out when creating the decoder_input_ids.

@RitchieP
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Hey @canberk17 - this can be fixed by specifying the language in the generation_config as follows:

model.generation_config.language = "<|hi|>"  # for hindi
model.generation_config.task = "transcribe"

Provided you run these two lines before calling trainer.train(), you'll de-activate automatic language detection during inference and be able to run the code as before. I'll update the blog post + Colab to reflect these changes!

Hi @sanchit-gandhi , I tried implementing this method, but when I ran trainer.train(), whenever it reaches the evaluation step, it tells me this message.

You have passed task=transcribe, but also have set forced_decoder_ids to [[1, None], [2, 50359]] which creates a conflict. forced_decoder_ids will be ignored in favor of task=transcribe.

Any idea why this is happening?

itazap pushed a commit that referenced this pull request May 14, 2024
* up

* Fix more

* Correct more

* Fix more tests

* fix fast tests

* Fix more

* fix more

* push all files

* finish all

* make style

* Fix timestamp wrap

* make style

* make style

* up

* up

* up

* Fix lang detection behavior

* Fix lang detection behavior

* Add lang detection test

* Fix lang detection behavior

* make style

* Update src/transformers/models/whisper/generation_whisper.py

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

* better error message

* make style tests

* add warning

---------

Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
kooqooo referenced this pull request in future-tomorrow-work-experience-project/stt-fine-tuning Jun 9, 2024
@MonolithFoundation
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ValueError: A custom logits processor of type <class 'transformers.generation.logits_process.ForceTokensLogitsProcessor'> with values <transformers.generation.logits_process.ForceTokensLogitsProcessor object at 0x7f4230cfac50> has been passed to .generate(), but it has already been created with the values <transformers.generation.logits_process.ForceTokensLogitsProcessor object at 0x7f422829c510>. <transformers.generation.logits_process.ForceTokensLogitsProcessor object at 0x7f422829c510> has been created by passing the corresponding arguments to generate or by the model's config default values. If you just want to change the default values of logits processor consider passing them as arguments to .generate() instead of using a custom logits processor.

what's the way to use it now?

@ArthurZucker
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Hey! Could you open a new issue with a repro? 🤗

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