GitLab

moved labels to the same device as logits for BLOOM, GPT Neo, GPT NeoX, RoBERTa and VIT models (#22663)

moved labels to the same device as logits

add API warning

* Fix default attention mask size

* fixup

* add a test to make sure that even if attention mask are not provided, works

* style

* do not push special file

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

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

* Small nit,
Fixes #21986

* Update src/transformers/pipelines/__init__.py

* fix

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

* (feat): Move labels to the same device as logits

* Trigger CI

* Trigger CI

* Trigger CI

* (feat): Making changes for Blip2

fix fsdp

fix slow tests and doctests

add safety checker

* Add TFBlipForConditionalGeneration

* update pipeline_model_mapping

* Add import

* Revert changes in GPTSanJapaneseTest

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

fix broken link

* Add out_indices to backbones, deprecate out_features

* Update - can specify both out_features and out_indices but not both

* Add backbone mixin tests

* Test tidy up

* Add test_backbone for convnext

* Remove redefinition of method

* Update for Dinat and Nat backbones

* Update tests

* Smarter indexing

* Add checks on config creation for backbone

* PR comments

* Adding Llama FastTokenizer support.

- Requires https://github.com/huggingface/tokenizers/pull/1183 version
- Only support byte_fallback for llama, raise otherwise (safety net).
- Lots of questions are special tokens

How to test:

```python

from transformers.convert_slow_tokenizer import convert_slow_tokenizer
from transformers import AutoTokenizer
from tokenizers import Tokenizer

tokenizer = AutoTokenizer.from_pretrained("huggingface/llama-7b")

if False:
    new_tokenizer = Tokenizer.from_file("tok.json")
else:
    new_tokenizer = convert_slow_tokenizer(tokenizer)
    new_tokenizer.save("tok.json")

strings = [
    "This is a test",
    "生活的真谛是",
    "生活的真谛是[MASK]。",
    # XXX: This one is problematic because of special tokens
    # "<s> Something something",
]

for string in strings:
    encoded = tokenizer(string)["input_ids"]
    encoded2 = new_tokenizer.encode(string).ids

    assert encoded == encoded2, f"{encoded} != {encoded2}"

    decoded = tokenizer.decode(encoded)
    decoded2 = new_tokenizer.decode(encoded2)

    assert decoded.strip() == decoded2, f"{repr(decoded)} != {repr(decoded2)}"
```

The converter + some test script.

The test script.

Tmp save.

Adding Fast tokenizer + tests.

Adding the tokenization tests.

Correct combination.

Small fix.

Fixing tests.

Fixing with latest update.

Rebased.

fix copies + normalized added tokens  + copies.

Adding doc.

TMP.

Doc + split files.

Doc.

Versions + try import.

Fix Camembert + warnings -> Error.

Fix by ArthurZucker.

Not a decorator.

* Fixing comments.

* Adding more to docstring.

* Doc rewriting.

feat(model parallelism): moving the labels to the same device as the logits for gpt2 and bart (#22591)

* add deplot + matcha on `transformers`

* more docs

* correct path

* Update docs/source/en/model_doc/deplot.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* fix

* use auto processor

* Update docs/source/en/model_doc/matcha.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* make fixup

* Update docs/source/en/model_doc/deplot.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* add correct names

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Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Adding support for BPE merge creation from scores instead of ids.

* Revert warn -> raise.

* Update src/transformers/convert_slow_tokenizer.py

* Quality.

Fixes a typo in one of the BLIP pretrained checkpoint names

The logger prints a summary at the beginning of training that displays some info such as number of examples, number of parameters, total number of steps, etc. Those numbers can be quite large and difficult to read. I added a thousand separator to improve readability for the following:
- num_examples
- num_train_epochs
- per_device_train_batch_size
- total_train_batch_size
- max_steps
- num_trainable_params

* Re-enable skipped test and fix the hidden state shape issue

* Actually fix the bug instead of just doing something wrong

* Fix inverted conditional in TF common test!

* Make the same change in the PT tests file

* Make sure hidden states for GPT2 have the same output shape in PT/TF

* Minor fix to PT implementation of token classification loss

* Skip loss equivalence test for TFHubert because it keeps overflowing to inf

* Compute LM loss for TF the (weird) way it's computed in PT

* Skip loss equivalence test for Wav2Vec2 for the same reason as Hubert

* Fix - don't try to access the hidden states property when output is a tuple

* initial commit

* review changes

* post model PR merge

* updating doc

* corrected/clarified the code comment of find_pruneable_heads_and_indices

* have run make style

* Initial commit

* more stash commit

* Yet another stash commit

* yet more stash commit

* Mostly working except for docs / repo consistency

* Stop importing model list from torch file

* Add TF BLIP models to docs

* Add auto classes

* Move get_text_features and get_image_features

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

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

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

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

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

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

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

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

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

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

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

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

* Update src/transformers/models/blip/modeling_tf_blip.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

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

* Update src/transformers/models/blip/modeling_tf_blip_text.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

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

* Use channels_last convolutions in TF (better performance + compatibility)

* Remove _shape function

* Move multi-line statement to one line in PT + TF

* Specify tf.keras.layers instead of importing from it

* Remove test_gradient_checkpointing and empty test_training methods

* move some multi-line statements to one line

* Update docstring for generate

* Remove pruned heads set

* Remove self.seq_len_dim

* Fixed issues with loss computation, should resolve some tests. Also ensured that the PT version follows the config for output_attentions and output_hidden_states

* ensure original model follows config in more cases

* Skip the same cross-attention tests in the PT tests - didn't realize we did it twice!

* Add training args throughout the models and layers

* make fixup

* Fix docstring for inputs_embeds

* Add docstring for is_decoder

* Add docstrings to text models

* Remove redundant computation

* Add unpack_inputs / keras_serializable

* Add modeling_tf_blip to doctests

* Add config classes for keras serialization

* Changes to allow model porting with pt-to-tf

* Quick fix to decoder head and test tweaks

* Revert an issue with masking the embeddings outputs

* Allow missing keys in some equivalence tests (for unused layers)

* Add tf-pt equivalence tests back in

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

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

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

* make fixup

* Refactor invert_attention_mask out into tf_utils

* Re-enable cross-tests on the PT side too

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

* Soft error whisper.

* Fix format.

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Co-authored-by: Ubuntu <ubuntu@ip-172-31-34-94.taildb5d.ts.net>

Update modeling_utils.py

* implemented safetensors save/load

* remove duplicated file

* added tests

* more tests

* style fix

* fix tf tests

* change to list comprehension
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* review fixes + safe load for sharded checkpoint

* style fix

* remove rogue import

* remove partial to avoid undefined exception

* use naming alias instead of safetensors.torch

* fix safe sharding in tests

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

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

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

* minor corrections

* style

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

* fix the prefix tokens

* update fast and test values

* add legacy behaviour
Co-authored-by: sgugger <sylvain.gugger@gmail.com>

* update disclaimer, linkissue PR and behaviral changes

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <hi@lysand.re>

* styling

* make a quote

* quote this time

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Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Lysandre Debut <hi@lysand.re>

[Roformer] Fixing a bug in RoFormerEncoder where it was ignoring the length of past_key_values when generating as a decoder (#22416)

* fix RoFormerEncoder postion embedding when generate as decoder

* make fixup

* add test case for check generate with past key values

* remove duplicating code

* Fix OPTForQuestionAnswering doc string

for more adequate model answer decoding

* black style fix

* doc-builder style

* [setup] drop deprecated `distutils` usage

* drop deprecated `distutils.util.strtobool` usage

* fix import order

* reformat docstring by `doc-builder`