GitLab

* renamed logging to hf_logging

* changed logging from hf_logging to logging and loggin to native_logging

* removed everything trying to fix import Trainer error

* adding imports again

* added custom add_handler function to logging.py

* make style

* added remove_handler

* added another conditional to assert

* Move tokenizer files in each repo

* Fix mBART50 tests

* Fix mBART tests

* Fix Marian tests

* Update templates

* s2t

* fix config

* conversion script

* fix import

* add tokenizer

* fix tok init

* fix tokenizer

* first version working

* fix embeds

* fix lm head

* remove extra heads

* fix convert script

* handle encoder attn mask

* style

* better enc attn mask

* override _prepare_attention_mask_for_generation

* handle attn_maks in encoder and decoder

* input_ids => input_features

* enable use_cache

* remove old code

* expand embeddings if needed

* remove logits bias

* masked_lm_loss => loss

* hack tokenizer to support feature processing

* fix model_input_names

* style

* fix error message

* doc

* remove inputs_embeds

* remove input_embeds

* remove unnecessary docstring

* quality

* SpeechToText => Speech2Text

* style

* remove shared_embeds

* subsample => conv

* remove Speech2TextTransformerDecoderWrapper

* update output_lengths formula

* fix table

* remove max_position_em...

* Add new GLUE example with no Trainer.

* Style

* Address review comments

Fixes an issue in `text-classification` where MNLI eval/test datasets are not being preprocessed. (#10621)

* Fix MNLI tests

* Linter fix

* Fix tests of TrainerCallback

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

* Hotfix fairscale FSDP

* Evaluation works

* Save on process zero

* added sm to ua

* update id

* removed id

* removed comments

* added env variable

* changed variable name

* make quality happy

* added sguggers feedback

* make styling happy and remove brackets

* added sm to ua

* update id

* removed id

* removed comments

* added env variable

* changed variable name

* make quality happy

* added sguggers feedback

* make styling happy and remove brackets

* save first version

* finish refactor

* finish refactor

* correct naming

* correct naming

* shorter names

* Update src/transformers/feature_extraction_common_utils.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* change name

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

* How to solve: Title level inconsistent

* list chars

* Pipeline tests should be slow

* Temporarily mark some tests as slow

* Temporarily mark Barthez tests as slow

* Create modeling_tf_dpr.py

* Add TFDPR

* Add back TFPegasus, TFMarian, TFMBart, TFBlenderBot

last commit accidentally deleted these 4 lines, so I recover them back

* Add TFDPR

* Add TFDPR

* clean up some comments, add TF input-style doc string

* Add TFDPR

* Make return_dict=False as default

* Fix return_dict bug (in .from_pretrained)

* Add get_input_embeddings()

* Create test_modeling_tf_dpr.py

The current version is already passed all 27 tests!
Please see the test run at : 
https://colab.research.google.com/drive/1czS_m9zy5k-iSJbzA_DP1k1xAAC_sdkf?usp=sharing



* fix quality

* delete init weights

* run fix copies

* fix repo consis

* del config_class, load_tf_weights

They shoud be 'pytorch only'

* add config_class back

after removing it, test failed ... so totally only removing "use_tf_weights = None" on Lysandre suggestion

* newline after .. note::

* import tf, np (Necessary for ModelIntegrationTest)

* slow_test from_pretrained with from_pt=True

At the moment we don't have TF weights (since we don't have official official TF model)
Previously, I did not run slow test, so I missed this bug

* Add simple TFDPRModelIntegrationTest

Note that this is just a test that TF and Pytorch gives approx. the same output.
However, I could not test with the official DPR repo's output yet

* upload correct tf model

* remove position_ids as missing keys

* create modeling_tf_rag

* add tests for tf

* add tf tests

* revert wrong pt commit

* further refactor

* further refactor

* refactor

* Update modeling_tf_rag.py

- input_processing
- fix prepare_input_for_generation (mostly fix generate bug)
- bring back from_pretrained hack in order to test generate

* delete colab pieces of code

* Show case of greedy "generate"

Temporarily change from beam_search test to greedy_search test to show case that TF and PT do get equivalent output.

* cosmetic update

* correct typos

* update

* push some progress

* make easy check

* fix rag save from pretrained

* Update src/transformers/modeling_tf_utils.py

* remove commented out lines

* delete unnecessary lines

* add simple test case for nq_checkpoint

Add nq_checkpoint test to show that current version without hack still fails

* temporarily put ugly hack back again

* Add TFRagSequenceForGeneration!!

* __init__.py , import TFRagSequenceForGeneration

* Add TFRagSequence tests!

* rag init.py - add TFRagSequenceForGeneration

* fix from_pretrained

* fix prepare_inputs_for_generation

* Beam search for RagToken!

* minor clean up

* add tf.cast in TFRagModel

* More tf.cast

* Add all remaining tests (still have issues)

* delete all T5 related

* make style

* fix load weight prefix

* fix bart

* fix return_dict for tf_rag

make all tests pass .. Hooray

* fix some tests

* fix code quality

* fix qualtiy check

* finish tests tf rag

* add tf rag to docs

* remove TFT5 from docstring
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* remove TFT5 from docstring
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Delete outdated comments
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* improve doc strings

* add generative model classes

* fix adjust token logic

* refactor generate for TFRag

* using shape_list, not _get_shape
Co-authored-by: Julien Plu <plu.julien@gmail.com>

* axis=[1]->axis=1

* delete NEED_HELP comment

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

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

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

* Indicating model is in a developing state in docstrings

As suggested by Julien

* small last changes

* apply sylvains suggestions

* finish tf rag
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: patrickvonplaten <patrick@huggingface.co>
Co-authored-by: Julien Plu <plu.julien@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Check layer types for Optimizer construction

* Duplicate class

This reverts commit b35e7b68.

This reverts commit a8ec52ef.

* batch 1

* this is tpu

* deebert attempt

* the rest

* reverted changes of logging and saving metrics

* added max_sample arguments

* fixed code

* white space diff

* reformetting code

* reformatted code

* fix sharded ddp enum

* test fixes

* stronger validation + apex breaks other tests

* more readable test

* add all the missing places

* one more nltk

* better exception check

* revert

* Fix version control with anchors

* Simplify

* Fix Marian decoding

Tokenizer's decode and batch_decode now accepts a new argument (use_source_tokenizer) which indicates whether the source spm should be used to decode ids. This is useful for Marian models specificallly when decoding source input ids.

* Adapt docstrings
Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>

* Enable torch 1.8.0 in GPU CI

* Disable torch-scatter

* fix tests

* emb should be a parameter

* fix positional embeddings

* fix make_weights

* don't save pos embeds

* add comment to describe the clamping

* m2m_100

* no layernorm_embedding

* sinusoidal positional embeddings

* update pos embeddings

* add default config values

* tokenizer

* add conversion script

* fix config

* fix pos embed

* remove _float_tensor

* update tokenizer

* update lang codes

* handle lang codes

* fix pos embeds

* fix spm key

* put embedding weights on device

* remove qa and seq classification heads

* fix convert script

* lang codes pn one line

* fix embeds

* fix tokenizer

* fix tokenizer

* add fast tokenizer

* style

* M2M100MT => M2M100

* fix copyright, style

* tokenizer converter

* vocab file

* remove fast tokenizer

* fix embeds

* fix tokenizer

* fix tests

* add tokenizer tests

* add integration test

* quality

* fix model name

* fix test

* doc

* doc

* fix doc

* add copied from statements

* fix tokenizer tests

* apply review suggestions

* fix urls

* fix shift_tokens_right

* apply review suggestions

* fix

* fix doc

* add lang code to id

* remove unused function

* update checkpoint names

* fix copy

* fix tokenizer

* fix checkpoint names

* fix merge issue

* style

* offline mode start

* add specific values

* fix fallback

* add test

* better values check and range

* test that actually works

* document the offline mode

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

* more strict check

* cleaner test

* pt-only test

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

* Refactor checkpoint name in ALBERT and ALBERT_tf

* Refactor checkpoint name in BART and BART_tf

* Refactor checkpoint name in BERT generation

* Refactor checkpoint name in Blenderbot_tf

* Refactor checkpoint name in Blenderbot_small_tf

* Refactor checkpoint name in ConvBERT AND CONVBERT_TF

* Refactor checkpoint name in CTRL AND CTRL_TF

* Refactor checkpoint name in DistilBERT AND DistilBERT_TF

* Refactor checkpoint name in DistilBERT redo

* Refactor checkpoint name in Electra and Electra_tf

* Refactor checkpoint name in FlauBERT and FlauBERT_tf

* Refactor checkpoint name in FSMT

* Refactor checkpoint name in GPT2 and GPT2_tf

* Refactor checkpoint name in IBERT

* Refactor checkpoint name in LED and LED_tf

* Refactor checkpoint name in Longformer and Longformer_tf

* Refactor checkpoint name in Lxmert and Lxmert_tf

* Refactor checkpoint name in Marian_tf

* Refactor checkpoint name in MBART and MBART_tf

* Refactor checkpoint name in MobileBERT and MobileBERT_tf

* Refactor checkpoint name in mpnet and mpnet_tf

* Refactor checkpoint name in openai and openai_tf

* Refactor checkpoint name in pegasus_tf

* Refactor checkpoint name in reformer

* Refactor checkpoint name in Roberta and Roberta_tf

* Refactor checkpoint name in SqueezeBert

* Refactor checkpoint name in Transformer_xl and Transformer_xl_tf

* Refactor checkpoint name in XLM and XLM_tf

* Refactor checkpoint name in XLNET and XLNET_tf

* Refactor checkpoint name in BERT_tf

* run make tests, style, quality, fixup