GitLab

Fixes a typo in one of the BLIP pretrained checkpoint names

* Update run_speech_recognition_ctc.py

Make sure all processes wait until data is saved before loading the processor from the output_dit

* Make sure all processes wait until data is saved before loading the processor from the output_dit

* Update run_speech_recognition_ctc.py

* Update run_speech_recognition_seq2seq.py

Co-authored-by: gabrielwithappy <102908949+gabrielwithappy@users.noreply.github.com>

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

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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>

Add id2label and label2id to config in run_xnil

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

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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] migrate setup script to `pyproject.toml`

* [setup] cleanup configurations

* remove unused imports

* [setup] drop deprecated `distutils` usage

* drop deprecated `distutils.util.strtobool` usage

* fix import order

* reformat docstring by `doc-builder`

* enable PP for T5

* make fixup

* fix failing tests

[`Trainer`] Force `is_model_parallel` when model is loaded in multiple GPUs using `accelerate` (#22532)

* add `is_model_parallel` arg on Trainer

* add warning

* adapt from suggestions

* revert t5 changes

* remove commas

* adapt from suggestions

LayoutLMv3TokenizerFast produces empty 'Ġ' token with `offset_mapping = (0, 0)`.
Next token is wrongly assumed to also be beginning of word and isn't
correctly assigned `pad_token_label`.
Modify test with text that produce 'Ġ' token.
Remove copy check from LayoutLMv2TokenizerFast for `_batch_encode_plus`.

solves issue: #19978

`load_checkpoint()` silently fails because `".qkj_proj." in key` is always `False`, but will eventually cause an error at `model.load_state_dict(state_dict)`.

* haha text go brrr (but in gradio)

* added biogpt token classifier

* fix reviews

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

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

docs: ko: sagemaker.mdx

* draft

* update tokenization limma and conversion script

* more udpates

* initial commit

* style

* default pad to None

* draft tokenization tests

* update test

* update tokenization tests

* nits

* update

* versioning test

* major fix

* fix more testst

* finish fixing special masks

* last nit

* more nits

* add encode decode tests

* add more

* fix token type ids

* style

added > 0.5 to `past_observed_mask`