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Properly calculate the total train iterations and recalculate num epochs in no_trainer scripts (#17856)

* wip

* rebase

* all tests pass

* rebase

* ready for PR

* address comments

* fix styles

* add require_torch to pipeline test

* remove remote image to improve CI consistency

* address comments; fix tf/flax tests

* address comments; fix tf/flax tests

* fix tests; add alias

* repo consistency tests

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

* address comments

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

* merge

* wip

* wip

* wip

* most basic tests passes

* all tests pass now

* relative embedding

* wip

* running make fixup

* remove bert changes

* fix doc

* fix doc

* fix issues

* fix doc

* address comments

* fix CI

* remove redundant copied from

* address comments

* fix broken test
Co-authored-by: Sijun He <sijunhe@Sijuns-MacBook-Pro.local>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Adjust test arguments and use a new example test

As shown in the colab notebook I added the missing type hints for " CvtForImageClassification
CvtModel
"

* Fix tests that broke when models used batchnorm

* Initializing the model twice does not actually...
...give you the same weights each time.
I am good at machine learning.

* Fix speed regression

* few fixes:

- hardcode tokenizer padding side
- remove unused args

* few fixes:

- added new attribute on TokenizerTesterMixin
- added new slow test
- remove unused arg on tokenizer class

* make style

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

* make quality

* apply changes

- remove new attribute
- redefine test on the class

* add comments
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>

* add skeleton files

* fix cpu inference link

* add hint to make clear that single gpu section contains general info

* add new files to ToC

* update toctree to have subsection for performance

* add "coming soon" to the still empty sections

* fix missing title

* fix typo

* add reference to empty documents

* Apply suggestions from code review
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Apply suggestions from code review
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>

* Feat: add missing type hints for QDQBertModel

* fix: ran black and isort

* feat: Add missing output type for QDQBertModel

* feat: Add type hints for QDQBertLMHeadModel and models starting with QDQBertFor

* fix: add missing return type for QDQBertModel

* fix: remove wrong return type for QDQBertEmbeddings

* fix: readded config argument to load_tf_weights_in_qdqbert

* fix: add BertConfig type to BertEmbeddings config due t checko error in ci

* fix: removed config type hints to avoid copy checks

* Update modeling_yoso.py

* make fixup

* Update modeling_yoso.py

That should be it copied from previous PR

* add: check labels for detr object detection doctests

* add: check shapes

* add: add detr to documentation_tests.py

* fix: make fixup output

* fix: add a comment

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Offload fixes

* Add a test

* use create_commit

* better commit message and description

* touch setup.py to trigger cache update

* add hub version gating

Bumps [numpy](https://github.com/numpy/numpy) from 1.21.0 to 1.22.0.
- [Release notes](https://github.com/numpy/numpy/releases)
- [Changelog](https://github.com/numpy/numpy/blob/main/doc/HOWTO_RELEASE.rst)
- [Commits](https://github.com/numpy/numpy/compare/v1.21.0...v1.22.0

)

---
updated-dependencies:
- dependency-name: numpy
  dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

Bumps [numpy](https://github.com/numpy/numpy) from 1.21.0 to 1.22.0.
- [Release notes](https://github.com/numpy/numpy/releases)
- [Changelog](https://github.com/numpy/numpy/blob/main/doc/HOWTO_RELEASE.rst)
- [Commits](https://github.com/numpy/numpy/compare/v1.21.0...v1.22.0

)

---
updated-dependencies:
- dependency-name: numpy
  dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

Add logits_processor parameter, used by `generate`, to `Seq2SeqTrainer` methods `evaluate` and `predict` (#17805)

* Add logits_processor parameter, used by `generate`, to `Seq2SeqTrainer` methods `evaluate` and `predict`

* Add all generate parameters to `Seq2SeqTrainer`, and also to `QuestionAnsweringSeq2SeqTrainer` which overrides it

* Remove `self._num_beams` from trainer classes

* - Run fixup
- Fix "Constraint" not exposed
- Fix synced_gpus to actually read from param

* Use kwargs

* Copy kwargs before making changes to it

* Fix style issues unused imports

- Fix `top_k_top_p_filtering` not passing `filter_value` to
   `TopPLogitsWarper` causing any top-p filtered logits to be -inf
   instead of specified value

 - Add corresponding test

* Improve error message Union not allowed

* make style

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

* Add final_layer_norm to OPT model

* Add JAX and TF version

* Fix Keras name

* Woops

* Allow for non breaking change

* Apply suggestions from code review

* add tests
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* initial commit

* update modeeling tf utils

* quality

* clean and update args

* update

* remove potential bug

* code quality

* update

* update max shard

* update tests for sharding from pretrained

* fix remaining test

* make style

* h5py if tf available

* update and fix test

* fix test

* style

* modified push to hub to support shard for TF

* quick fix

* update code

* merge branch main and style

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

* update based on reviews

* update doc

* update and style

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

* Update based on reviews

* fix typo

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

* rename to check_pt_flax_outputs

* update check_pt_flax_outputs

* use 5e-5 for BigBird PT/Flax test
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Prepare CI for v0.8.0

* pin hfh (revert before merge)

* Revert "pin hfh (revert before merge)"

This reverts commit a0103140e1c77b810ffcb735192968bc03be3e1f.

* Test rc3

* Test latest rc

* Unpin to the RC
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>

* added use_backbone_pretrained

* style fixes

* update

* Update detr.mdx

* Update detr.mdx

* Update detr.mdx

* update using doc py

* Update detr.mdx

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

* Fix docstrings and variable names

* Rename x to something better

* Improve messages

* Fix docstrings and add test for greyscale images
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

* deduplication draft

* update style

* update style test

* dummy test main

* rename modules

* rename functions

* return extremes in deduplicate_clusters

* update style

* cast str for gzip

* update doc string

* time processing

* use dataset map to compute minhash

* fill value for short token

* remove da map method

* update style

* use share object to multiprocess

* update style

* use f-string and minor fix
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
Co-authored-by: Loubna Ben Allal <44069155+loubnabnl@users.noreply.github.com>

* update style

* use module parameters

* change ds_dedup to ds_filter

* save ds_dedup

* mv test to script tests

* make jaccard threshold a parameter of deduplicate_dataset

* update style

* add doc strings

* update style

* add doc string for DuplicationIndex

* save files into data dir

* update readme

* Update examples/research_projects/codeparrot/README.md
Co-authored-by: Loubna Ben Allal <44069155+loubnabnl@users.noreply.github.com>

* make near deduplication optional

* move near deduplication in README

* Update examples/research_projects/codeparrot/README.md
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>

* use f string
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
Co-authored-by: Loubna Ben Allal <44069155+loubnabnl@users.noreply.github.com>

* add onnx support for debertav2

* debertav2 -> deberta-v2 in onnx features file

* remove causal lm

* add deberta-v2-xlarge to onnx tests

* use self.type().dtype() in xsoftmax
Co-authored-by: Jingya HUANG <44135271+JingyaHuang@users.noreply.github.com>

* remove hack for deberta

* remove unused imports

* Update src/transformers/models/deberta_v2/configuration_deberta_v2.py
Co-authored-by: Jingya HUANG <44135271+JingyaHuang@users.noreply.github.com>

* use generate dummy inputs

* linter

* add imports

* add support for deberta v1 as well

* deberta does not support multiple choice

* Update src/transformers/models/deberta/configuration_deberta.py
Co-authored-by: Jingya HUANG <44135271+JingyaHuang@users.noreply.github.com>

* Update src/transformers/models/deberta_v2/configuration_deberta_v2.py
Co-authored-by: Jingya HUANG <44135271+JingyaHuang@users.noreply.github.com>

* one line ordered dict

* fire build
Co-authored-by: Jingya HUANG <44135271+JingyaHuang@users.noreply.github.com>

* Add UL2
Co-authored-by: Daniel Hesslow <Daniel.Hesslow@gmail.com>

* Correct naming

* sort better

* up

* apply sylvains suggestion

On line 180, `torch.tensor(-1.0, xxx)` gives the error "TypeError: 'float' object cannot be interpreted as an integer" 
This is because the dtype here is `int64`.  For `dtype=int64`, this needs to simply be `-1`.  
This impacts the long-t5-tglogbal-x model.  It does not impact the long-t5-local-x version which does not appear to call this line.