GitLab

* Restrain tokenizer.model_max_length default

* Fix indent

* Fix model templates and use less than 119 chars

* Missing new line

* Add decoder_head_mask for PyTorch T5 model

* Add decoder_head_mask args into T5Model and T5ForConditionalGeneration

* Slightly change the order of input args to be in accordance
with the convention from BART-based models introduced within the PR #9569.

* Make style for modeling_t5.py

* Add decoder_head_mask for TF T5 models

* Separate head_mask and decoder_head_mask args in TF T5 models

* Slightly change the order of input args to follow convention
of BART-based models updated in PR #9569

* Update test_forward_signature tests/test_modeling_tf_common.py
w.r.t. the changed order of input args

* Add FutureWarnings for T5 and TFT5 models

* Add FutureWarnings for T5 and TFT5 models warning a user that
input argument `head_mask` was split into two arguments -
`head_mask` and `decoder_head_mask`

* Add default behaviour - `decoder_head_mask` is set to copy
`head_mask`

* Fix T5 modeling and FutureWarning

* Make proper usage of head_mask and decoder_head_mask
in cross_attention

* Fix conditions for raising FutureWarning

* Reformat FutureWarning in T5 modeling

* Refactor the warning message

* New run_seq2seq script

* Add tests

* Mark as slow

* Update examples/seq2seq/run_seq2seq.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

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

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

* Address review comments
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Fix Flaubert and XLM

* Fix Flaubert and XLM

* Apply style

File "/share/apps/anaconda3/envs/my_env/lib/python3.7/site-packages/transformers/integrations.py", line 419, in __init__
    self._SummaryWriter = SummaryWriter
UnboundLocalError: local variable 'SummaryWriter' referenced before assignment

* Update past_key_values in gpt2 (#9391)

* Update generation_utils, and rename some items

* Update modeling_gpt2 to avoid an error in gradient_checkpointing

* Remove 'reorder_cache' from util and add variations to XLNet, TransfoXL, GPT-2

* Change the location of '_reorder_cache' in modeling files

* Add '_reorder_cache' in modeling_ctrl

* Fix a bug of my last commit in CTRL

* Add '_reorder_cache' to GPT2DoubleHeadsModel

* Manage 'use_cache' in config of test_modeling_gpt2

* Clean up the doc string

* Update src/transformers/models/gpt2/modeling_gpt2.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fix the doc string (GPT-2, CTRL)

* improve gradient_checkpointing_behavior
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Fix the attention_mask in DPRReaderTokenizer

* Add an integration test for DPRReader inference

* Run make style

* Add head_mask/decoder_head_mask for BART

This branch implement head_mask and decoder_head_mask
for BART-based models. Full list below:
- BART
- MBart
- Blenderbot
- BlenderbotSmall
- Marian
- Pegasus

Everything is accompanied with updated testing.

* Fix test_headmasking for BART models

* Fix text_headmasking for BART-like models
which has only 2 layers in each modules.
The condition
```
self.assertNotEqual(attentions[1][..., 0, :, :].flatten().sum().item(), 0.0)
```
is, therefore, invalid for encoder-decoder models considering
the `head_mask`
```
head_mask = torch.ones(
    self.model_tester.num_hidden_layers,
    self.model_tester.num_attention_heads,
    device=torch_device,
)
head_mask[0, 0] = 0
head_mask[-1, :-1] = 0
```
specified in the `test_headmasking` test/function.

* Adjust test_modeling_common.py to reflect T5 input args

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

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

* make style

* make fix-copies
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Ignore lm_head decoder bias warning

* Revert "Ignore lm_head decoder bias warning"

This reverts commit f25177a9da6ca898e351f46c8b1515971de5c670.

* predictions -> lm_head

* Add warning

* Remove unused import

* Fix missing call

* Fix missing call

* Completely remove token_type_ids

* Apply style

* Remove unused import

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

* fix tf led

* remove loop file

This reverts commit 3f40070c.

* [doc] install + 1-gpu deployment

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

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

* Upstream (and rename) sortish sampler

* Use proper sampler

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

* gradient accumulation for tftrainer

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

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

* conda build -> conda-build

* Syntax error

* conda build -> conda-build + 4.2.0

* Prepare to merge in `master`

* note on how to get to deps from shell

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

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

* Compliancy with tf-nightly

* Add more version + restore min version check

* Switch metrics in run_ner to datasets

* Add flag to return all metrics

* Upstream (and rename) sortish_sampler

* Revert "Upstream (and rename) sortish_sampler"

This reverts commit e07d0dcf650c2bae36da011dd76c77a8bb4feb0d.

* Fix Trainer with a parallel model

* More clean up