GitLab

* ConvBert

* added comment

* Updated

* Final_updates

* Update tokenization_convbert.py

* Update tokenization_convbert_fast.py

* Update tokenization_convbert.py

* Update tokenization_convbert.py

* Update tokenization_convbert_fast.py

* Update tokenization_convbert.py

* Update tokenization_convbert_fast.py

* Updates

* Updates

* Updated

* Final Updates

The link to https://github.com/vasudevgupta7/bigbird is vulnerable to repojacking (it redirects to the orignial project that changed name), you should change the link to the current name of the project. if you won't change the link, an attacker can open the linked repository and attacks users that trust your links

This PR aims to rectify the discrepancy between the training performances of HF and Timm ViT implementations.

- Initializes torch and flax ViT dense layer weights with trunc_normal instead of normal (consistent with the TF implementation.
- Initializes cls_token and positional_embeddings with trunc_normal
- Updates DeiT copy to reflect the changes

* Fix pipeline tests for Roberta-like tokenizers

* Fix fix

Ensures post_process_instance_segmentation and post_process_panoptic_segmentation methods return a tensor of shape (target_height, target_width) filled with -1 values if no segment with score > threshold is found.

* simplify loop

* add featur extractor

* add model

* start conversion

* add dropout

* initial commit of test files

* copnversion for all models

* update processor for correct padding

* update feature extraction

* update integration test logits match

* fmnt: off for the logits

* on the fly mel bank

* small nit

* update test

* update tokenizer

* nit feature extraction

* update

* update tokenizer test

* adds logit processor and update tokenizer to get supress tokens

* style

* clean convert

* revert to original modeling tf utils

* Update

* update

* nit

* clean convert file

* update tests and nits

* quality

* slow generation test

* ffn_dim to allow customization

* update readme

* add to toctreee

* start fixing integration tests

* update tests and code

* fix feature extractor

* fix config tests common

* update code to fix tests

* fix feature exctractor

* nit feature extraction

* update test for new feature extractor

* style

* add absrtact

* large logits wioth custom decoder input ids

* wraap around is otrch available

* fix feature extractor

* correct logits for whisper small.en

* nit

* fix encoder_attentino_mask

* some fixes

* remove unnecessary inputs

* nits

* add normalizer file

* update etst tokenization

* fix attention mask not defined

* Add model to README

* Fix doc tests

* fix generate

* remove uncoder attention mask useless

* update test modeling whisper

* update condfig to add second non supress tokens

* nits on feature exrtactor

* nit for test tokenizers

* update etsts

* update tests

* update tokenization test

* fixup

* invalidated hf token. Clean convert openai to whisper

* fix logit tests

* fixup

* clean merge

* revert toc_tree changes

* remove useless LogitProcessor

* Update whisper .mdx

* update config file doc

* update configuration docstring

* update test tokenization

* update test tokenization

* update tokenization whisper
Added copied from where needed

* update feature extraction

* nit test name

* style

* quality

* remove get suppress tokens and update non_speech tokens global variables

* Update src/transformers/models/whisper/feature_extraction_whisper.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* clean modeling whisper and test
Removed the attention mask arguments that are deprecated

* fix large test

* Add multilingual audio test, and translate test

* style

* fix larg multilingual test

* nits

* Update docs/source/en/model_doc/whisper.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* add copied from for attention layer

* remove attention masks in doc

* add english normalizer

* update tokenization test

* remove copied from in whisper attention : no bias in k_proj only

* wrap around dependencies in english normalizer

* style

* correct import generation logits

* for now, wrap feature extractor with torch

* Update src/transformers/models/whisper/convert_openai_whisper_to_tfms.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/whisper/configuration_whisper.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

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

* remove torch depencies for feature extraction and style

* fixup

* nit

* update logitds

* style

* nit

* nits and fix final tests

* add `is_more_itertools_available` to utils

* quality

* add begin supress tokens, supress tokens to generate args and config

* clean supressTokensLogitProcessor in generation logits

* Nit naming

* add supressTokensAtBegin

* udpate tests, supress tokens to None or correct values

* nit and style

* update RAG to fit test and generate_logit

* add copy pasted statment on english normalizer

* add arguments to config_common_kwargs

* Update src/transformers/generation_utils.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/generation_logits_process.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/whisper/configuration_whisper.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* revert changes based on reviews

* update doc and nits

* more nits

* last nits

* update test configuration common

* add BART name in decoder attention mask documentation

* Update src/transformers/models/whisper/modeling_whisper.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* style

* nit

* nit

* add english.json file to git

* nits on documentation

* nit

* nits

* last styling

* add main toctree file

* remove sentence piece dependency

* clean init file

* fix tokenizer that has no dependencies on sentencepiece

* update whisper init file, nit

* remove english.json file

* add get decoder prompt id

* revert changes and add forced logit processor

* nit

* clean normalizer

* remove protected

* update

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

* update based on review

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

* add batched tests
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: NielsRogge <niels.rogge1@gmail.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Ensures post_process_instance_segmentation and post_process_panoptic_segmentation methods return a tensor of shape (target_height, target_width) filled with -1 values if no segment with score > threshold is found.

* removes roberta and bert config dependencies from longformer

* adds copied from statements

* fixes style

* removes excessive comments and replace bert with longformer in a couple places

* fixes style

* Add a build_from_serving_sig_and_dummies method and replace all calls like model(model.dummy_inputs) with it.

* make fixup

* Remove the overridden save() as this is no longer necessary

* Also call _set_save_spec(), the last missing piece

* Ensure we set the save spec when loading from config too

* Turn this whole thing into a one-line PR

* Turn this whole thing into a one-line PR

* Turn this whole thing into a one-line PR
Co-authored-by: Your Name <you@example.com>

* change `BloomConfig` docstring

- slightly change the docstring of the `BloomConfig`
- Use correct default vocab size
- Use correct default `hidden_dim`, `n_head`

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

* Update src/transformers/models/bloom/configuration_bloom.py
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>

* make style
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>

* copies over roberta tokenizer to longformertokenizer since they are both identical

* adds Copied from patterns to pass copy check

* add sudachipy and jumanpp tokenizers for bert_japanese

* use ImportError instead of ModuleNotFoundError in SudachiTokenizer and JumanppTokenizer

* put test cases of test_tokenization_bert_japanese in one line

* add require_sudachi and require_jumanpp decorator for testing

* add sudachi and pyknp(jumanpp) to dependencies

* remove sudachi_dict_small and sudachi_dict_full from dependencies

* empty commit for ci

Co-authored-by: Mustapha AJEGHRIR <mustapha.ajeghrir@kleegroup.com>

* remove XLMTokenizer inheritance from FlaubertTokenizer

* remove XLMTokenizer inheritance from FlaubertTokenizer

* remove XLMTokenizer inheritance from FlaubertTokenizer

* remove XLMTokenizer inheritance from FlaubertTokenizer: fixed styling

* removed repo-consistensy issue

* removed interdependency of BERTTokenizer in tokenization of prophetnet

* fix: style

- Improves MaskFormer docs, corrects minor typos
- Restructures MaskFormerFeatureExtractor.post_process_panoptic_segmentation for better readability, adds target_sizes argument for optional resizing
- Adds post_process_semantic_segmentation and post_process_instance_segmentation methods.
- Adds a deprecation warning to post_process_segmentation method in favour of post_process_instance_segmentation

* removing XLMConfig inheritance from FlaubertConfig

* removing XLMConfig inheritance from FlaubertConfig

* Fixed styling issue

* Update configuration_flaubert.py
Co-authored-by: Druhin Abrol <druhinabrol@192.168.1.6>

* Remove interdependency from OpenAI tokenizer

* Adjust import order for linter

* Clamping hidden state values to allow FP16

* Reformating

* Adding missing if condition

* Update src/transformers/models/longt5/modeling_longt5.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update src/transformers/models/longt5/modeling_longt5.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update src/transformers/models/longt5/modeling_longt5.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

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

* add bloom for question answering

- attempt to add Bloom for question answering
- adapted from `GPTJForQuestionAnswering`
- Fixed `num_labels` to `2` for common tests
- Added a bit of docstring
- All common tests pass

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

* revert changes related to `num_labels`
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* removing BertConfig inheritance

* fix missing arguments

in stale.yml

* Added type hints for TF: rag model

* TFModelInputType added in place of TF.Tensor

* reformatting by black

* Update modeling_tf_led.py

* Update modeling_tf_led.py

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