GitLab

* fix_torch_device_generate_test

* remove @

* upload

* Apply suggestions from code review

* Apply suggestions from code review

* Apply suggestions from code review

* Update examples/flax/language-modeling/README.md

* add more info

* finish

* fix
Co-authored-by: Patrick von Platen <patrick@huggingface.co>

* Fix megatron_gpt2 attention block's causal mask.

* compatibility with checkpoints created with recent versions of Megatron-LM

* added integration test for the released Megatron-GPT2 model

* code style changes

* added option to megatron conversion script to read from config file
Co-authored-by: Guido Novati <gnovati@nvidia.com>

* Fix t5 error message

* Fix again

* Add from_pretrained to dummy timm

* Fix at the source

* Update utils/check_dummies.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Missing pretrained dummies

* Style
Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* first draft

* max_seq_length => block_size

* fix arg names

* fix typos

* fix loss calculation

* add max examples, fix  train eval steps, metrics

* optimizer mask

* fix perpelexity, metric logging

* fix logging

* data_collator = > data_loader

* refactor loss_fn

* support single GPU

* pass distributed to write_metric

* fix jitting

* fix single device training

* fix single device metrics

* close inner progress bars once finished

* add overwrite_cache arg

* ifx dataset caching issue

* add more logs

* few small fixes,

* address nicholas suggestions

* fix docstr

* address patricks suggestions

* make flake happy

* pass new new_dropout_rng to apply_gradients

* reset train metrics after every epoc

* remove distributed logis, small fixes

* fix_torch_device_generate_test

* remove @

* fix tests

* add relevant `desc` in examples

* require_version datasets>=1.8.0

* adding vit for flax

* added test for Flax-vit and some bug-fixes

* overrided methods where variable changes were necessary for flax_vit test

* added FlaxViTForImageClassification for test

* Update src/transformers/models/vit/modeling_flax_vit.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* made changes suggested in PR

* Adding jax-vit models for autoimport

* swapping num_channels and height,width dimension

* fixing the docstring for torch-like inputs for VIT

* add model to main init

* add docs

* doc, fix-copies

* docstrings

* small test fixes

* fix docs

* fix docstr

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* style
Co-authored-by: jayendra <jayendra@infocusp.in>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Fix a condition in test_generate_with_head_masking

* Fix usage of head_mask in bigbirg_pegasus

* Fix head masking for speech2text

* Resolve copy mismatch + drop unwanted print statement

* Fix the condition

* Pushing partially-complete new GLUE example

* First draft of the new TF GLUE example! Needs a little more testing to be sure but it's almost ready.

* Fix to the fit() call

* Bugfixes, making sure TPU and multi-GPU support is ready

* Remove logger line that depends on Pytorch

* Style pass

* Deleting old TF GLUE example

* Include label2id and id2label in the saved model config

* Don't clobber the existing model.config.label2id

* Style fixes

* Update examples/tensorflow/text-classification/run_glue.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Resize with kept aspect ratio

* Fixed failed test

* Overload center_crop and resize methods instead

* resize should handle non-PIL images

* update slow test

* Tensor => tensor
Co-authored-by: patil-suraj <surajp815@gmail.com>

* Add text_column_name and label_column_name to run_ner args

* Minor fix: grouping for text and label column name

* fix_torch_device_generate_test

* remove @

* fix tests

* Working quantizer forward

* Working quantizer forward

* Clean up unused model parts, test reproducibility

* Working quantizer forward

* Clean up unused model parts, test reproducibility

* Remove custom outputs from the shared ones

* correct conversion

* correct bug

* add first pretrain script

* save intermediate

* static shapes

* save intermediate

* finish first pretrain script version

* more refactor

* remove wanddb

* refactor more

* improve test

* correct perplexity compute bug

* finish model implementation

* add to docs

* finish docs

* finish pretraining script

* finish pretraining script

* remove wandb

* finish PR for merge

* finish config

* finish

* make deepspeed work

* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* apply suggestions

* fix flaky test
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* support more than 2 gpus

* style

* Squash all commits of modeling_detr_v7 branch into one

* Improve docs

* Fix tests

* Style

* Improve docs some more and fix most tests

* Fix slow tests of ViT, DeiT and DETR

* Improve replacement of batch norm

* Restructure timm backbone forward

* Make DetrForSegmentation support any timm backbone

* Fix name of output

* Address most comments by @LysandreJik

* Give better names for variables

* Conditional imports + timm in setup.py

* Address additional comments by @sgugger

* Make style, add require_timm and require_vision to testsé

* Remove train_backbone attribute of DetrConfig, add methods to freeze/unfreeze backbone

* Add png files to fixtures

* Fix type hint

* Add timm to workflows

* Add `BatchNorm2d` to the weight initialization

* Fix retain_grad test

* Replace model checkpoints by Facebook namespace

* Fix name of checkpoint in test

* Add user-friendly message when scipy is not available

* Address most comments by @patrickvonplaten

* Remove return_intermediate_layers attribute of DetrConfig and simplify Joiner

* Better initialization

* Scipy is necessary to get sklearn metrics

* Rename TimmBackbone to DetrTimmConvEncoder and rename DetrJoiner to DetrConvModel

* Make style

* Improve docs and add 2 community notebooks
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* wip

* wip - but working with https://github.com/microsoft/DeepSpeed/pull/1044

* cleanup

* workaround

* working 5/8 modes

* solve fp32 distributed zero3

* style

* sync

* sync

* rework

* deprecation

* cleanup

* https://github.com/microsoft/DeepSpeed/pull/1044

 pr was merged

* clean up

* add a guide

* more prose

* more prose

* fix

* more prose

* sub_group_size was too big

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* refactor

* bug fix

* make the true check explicit

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

* replace deprecated config

* sub_group_size was too big

* complete deprecation removal

* Add torch to requirements.txt in language-modeling

* Update examples/pytorch/language-modeling/requirements.txt
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Replace legacy torch.Tensor constructor with torch.{tensor, empty}

* Remove torch.Tensor in examples

* updated the original RAG implementation to be compatible with the latest PL version

* updated the requirements.txt file

* execute make style

* code quality test

* code quality

* conflix resolved in requirement.txt

* code quality

* changed the MyDDP class name to CustomDDP

* Fix scatter function to be compatible with torch-scatter 2.7.0

* Allow test again

* adds metric prefix.

* update tests to include prefix

* Adding optional argument group to HfArgumentParser

* Minor

* remove whitespace

* Minor styling

* fix_torch_device_generate_test

* remove @

* finish

* refactor

* add test

* fix test

* Attempt at simplification.

* Small fix.

* Fixing non existing AutoModel for TF.

* Naming.

* Remove extra condition.
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>

* Fixing bug that appears when using distilation (and potentially other uses).
During backward pass Pytorch complains with:
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation
This happens because the QA model code modifies the start_positions and end_positions input tensors, using clamp_ function: as a consequence the teacher and the student both modifies the inputs, and backward pass fails.

* Fixing all models QA clamp_ bug.

* fix_torch_device_generate_test

* remove @

* bump up jax lib