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Replace assert by ValueError of src/transformers/models/electra/modeling_{electra,tf_electra}.py and all other models that had copies (#13955)

* Replace all assert by ValueError in src/transformers/models/electra

* Reformat with black to pass check_code_quality test

* Change some assert to ValueError of modeling_bert & modeling_tf_albert

* Change some assert in multiples models

* Change multiples models assertion to ValueError in order to validate
  check_code_style test and models template test.

* Black reformat

* Change some more asserts in multiples models

* Change assert to ValueError in modeling_layoutlm.py to fix copy error in code_style_check

* Add proper message to ValueError in modeling_tf_albert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Simplify logic in models/bert/modeling_bert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Add ValueError message to models/convbert/modeling_tf_convbert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Add error message for ValueError to modeling_tf_electra.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Simplify logic in models/tapas/modeling_tapas.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Simplify logic in models/electra/modeling_electra.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Add ValueError message in src/transformers/models/bert/modeling_tf_bert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Simplify logic in src/transformers/models/rembert/modeling_rembert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Simplify logic in src/transformers/models/albert/modeling_albert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

[Gradient checkpoining] Correct disabling `find_unused_parameters` in Trainer when gradient checkpointing is enabled (#13961)

* up

* correct test

* Honor existing attention mask in tokenzier.pad

* Fix initialization of attention mask

* Roll the implem on all subclasses

* Fix tests

* Raise ValueError exception instead of assert

* Remove f unnecessary f-strings

* Remove unused f-strings

* up

* Update src/transformers/generation_stopping_criteria.py

* finish

* Added `framework` attribute

* Update modeling_utils.py

* Update modeling_flax_utils.py

* Update modeling_tf_utils.py

* Update modeling_utils.py

* Update modeling_tf_utils.py

* Update modeling_tf_utils.py

* Update modeling_flax_utils.py

* Update modeling_tf_utils.py

* Update modeling_utils.py

* Update modeling_utils.py

* Update modeling_tf_utils.py

* Update modeling_flax_utils.py

* string -> str

* Update modeling_tf_utils.py

* string -> str

* fixup

* make flake happy
Co-authored-by: patil-suraj <surajp815@gmail.com>

* Adding support for tokens being suffixes or part of each other.

* Better test name.

* Implement img seg pipeline

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

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

* Update output shape with individual masks

* Rm dev change

* Remove loops in test
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* [trainer] memory metrics: add memory at start

* fix for no-gpu

* Fix issues with LED model

* Style pass

* Bugfixes

* correct attentions as well
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* up

* overwrite hubert

* Fix logging_nan_inf_filter in torch_xla mode

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

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

* enabling using past_key_values together with labels when training in T5ForConditionalGeneration

* test

* Enable past_key_values in T5ForconditionalGeneration while training.

* delete comments

Fixes #13846

Co-authored-by: Pierre Snell <pierre.snell@botpress.com>
Co-authored-by: Pierre Snell <pierre.snell@botpress.com>

* Tmp.

* Fixing BC for question answering with long context.

* Capping model_max_length to avoid tf overflow.

* Bad workaround bugged roberta.

* Fixing name.

* Allow dataset to be an optional argument for (Distributed)LengthGroupedSampler

* Fix

* Symbolic trace dynamic axes support for BERT like models (albert, bert, distilbert, mobilebert, electra, megatron-bert)
* Sanity checks before tracing that make sure the model to trace is supported
* Adapted to PyTorch 1.9
Co-authored-by: Michael Benayoun <michael@huggingface.co>

* Improve error message when loading models from Hub

* Adjust error message wording

* Fixing empty prompts for text-generation when BOS exists.

* Fixing odd case with Pegasus.

* Fixing Bert is Assertion Error.

* Update Tatoeba conversion

* update no_* argument

Changes the order so that the no_* argument is created after the original argument AND sets the default for this no_* argument to False

* import copy

* update test

* make style

* Use kwargs to set default=False

* make style

* Add layer-wise scaling

* Add reorder & upcasting argument

* Add OpenAI GPT-2 weight initialization scheme

* start `layer_idx` count at zero for consistency

* disentangle attn and reordered and upscaled attn function

* rename `scale_attn_by_layer` to `scale_attn_by_layer_id`

* make autocast from amp compatible with pytorch<1.6

* fix docstring

* style fixes

* Add fixes from PR feedback, style tweaks

* Fix doc whitespace

* Reformat

* First pass scale_attn_by_layer_idx and reorder_and_upcast_attn tests

* Rename scale_attn_by_layer_idx, add tip

* Remove extra newline

* add test for weight initialization

* update code format

* add assert check weights are fp32

* remove assert

* Fix incorrect merge

* Fix shape mismatch in baddbmm

* Add generation test for Mistral flags
Co-authored-by: leandro <leandro.vonwerra@spoud.io>
Co-authored-by: Keshav Santhanam <keshav2@stanford.edu>
Co-authored-by: J38 <jebolton@stanford.edu>