* neFLOs calculation, logging, and reloading (#1)

* testing distributed consecutive batches

* fixed AttributeError from DataParallel

* removed verbosity

* rotate with use_mtime=True

* removed print

* fixed interaction with gradient accumulation

* indent formatting

* distributed neflo counting

* fixed typo

* fixed typo

* mean distributed losses

* exporting log history

* moved a few functions

* floating_point_ops clarification for transformers with parameter-reuse

* code quality

* double import

* made flo estimation more task-agnostic

* only logging flos if computed

* code quality

* unused import

* Update src/transformers/trainer.py

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

* Update src/transformers/modeling_utils.py

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

* Sylvain review

* Update src/transformers/modeling_utils.py

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

* black

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

* ready for PR

* cleanup

* correct FSMT_PRETRAINED_MODEL_ARCHIVE_LIST

* fix

* perfectionism

* revert change from another PR

* odd, already committed this one

* non-interactive upload workaround

* backup the failed experiment

* store langs in config

* workaround for localizing model path

* doc clean up as in huggingface#6956

* style

* back out debug mode

* document: run_eval.py --num_beams 10

* remove unneeded constant

* typo

* re-use bart's Attention

* re-use EncoderLayer, DecoderLayer from bart

* refactor

* send to cuda and fp16

* cleanup

* revert (moved to another PR)

* better error message

* document run_eval --num_beams

* solve the problem of tokenizer finding the right files when model is local

* polish, remove hardcoded config

* add a note that the file is autogenerated to avoid losing changes

* prep for org change, remove unneeded code

* switch to model4.pt, update scores

* s/python/bash/

* missing init (but doesn't impact the finetuned model)

* cleanup

* major refactor (reuse-bart)

* new model, new expected weights

* cleanup

* cleanup

* full link

* fix model type

* merge porting notes

* style

* cleanup

* have to create a DecoderConfig object to handle vocab_size properly

* doc fix

* add note (not a public class)

* parametrize

* - add bleu scores integration tests

* skip test if sacrebleu is not installed

* cache heavy models/tokenizers

* some tweaks

* remove tokens that aren't used

* more purging

* simplify code

* switch to using decoder_start_token_id

* add doc

* Revert "major refactor (reuse-bart)"

This reverts commit 226dad1.

* decouple from bart

* remove unused code #1

* remove unused code #2

* remove unused code #3

* update instructions

* clean up

* move bleu eval to examples

* check import only once

* move data+gen script into files

* reuse via import

* take less space

* add prepare_seq2seq_batch (auto-tested)

* cleanup

* recode test to use json instead of yaml

* ignore keys not needed

* use the new -y in transformers-cli upload -y

* [xlm tok] config dict: fix str into int to match definition (huggingface#7034)

* [s2s] --eval_max_generate_length (huggingface#7018)

* Fix CI with change of name of nlp (huggingface#7054)

* nlp -> datasets

* More nlp -> datasets

* Woopsie

* More nlp -> datasets

* One last

* extending to support allen_nlp wmt models

- allow a specific checkpoint file to be passed
- more arg settings
- scripts for allen_nlp models

* sync with changes

* s/fsmt-wmt/wmt/ in model names

* s/fsmt-wmt/wmt/ in model names (p2)

* s/fsmt-wmt/wmt/ in model names (p3)

* switch to a better checkpoint

* typo

* make non-optional args such - adjust tests where possible or skip when there is no other choice

* consistency

* style

* adjust header

* cards moved (model rename)

* use best custom hparams

* update info

* remove old cards

* cleanup

* s/stas/facebook/

* update scores

* s/allen_nlp/allenai/

* url maps aren't needed

* typo

* move all the doc / build /eval generators to their own scripts

* cleanup

* Apply suggestions from code review

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

* Apply suggestions from code review

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

* fix indent

* duplicated line

* style

* use the correct add_start_docstrings

* oops

* resizing can't be done with the core approach, due to 2 dicts

* check that the arg is a list

* style

* style

Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

There is a tiny typo in the code "transformers/examples/language-modeling/run_mlm_wwm.py" at line 284. [Details.](huggingface#9012)

…5416)

* added classes to get started with constrained beam search

* in progress, think i can directly force tokens now but not yet with the round robin

* think now i have total control, now need to code the bank selection

* technically works as desired, need to optimize and fix design choices leading to undersirable outputs

* complete PR #1 without disjunctive decoding

* removed incorrect tests

* Delete k.txt

* Delete test.py

* Delete test.sh

* revert changes to test scripts

* genutils

* full implementation with testing, no disjunctive yet

* shifted docs

* passing all tests realistically ran locally

* removing accidentally included print statements

* fixed source of error in initial PR test

* fixing the get_device() vs device trap

* fixed documentation docstrings about constrained_beam_search

* fixed tests having failing for Speech2TextModel's floating point inputs

* fix cuda long tensor

* added examples and testing for them and founx & fixed a bug in beam_search and constrained_beam_search

* deleted accidentally added test halting code with assert False

* code reformat

* Update tests/test_generation_utils.py

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

* Update tests/test_generation_utils.py

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

* Update tests/test_generation_utils.py

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

* Update tests/test_generation_utils.py

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

* Update tests/test_generation_utils.py

* fixing based on comments on PR

* took out the testing code that should but work fails without the beam search moditification ; style changes

* fixing comments issues

* docstrings for ConstraintListState

* typo in PhrsalConstraint docstring

* docstrings improvements

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

)

* added classes to get started with constrained beam search

* in progress, think i can directly force tokens now but not yet with the round robin

* think now i have total control, now need to code the bank selection

* technically works as desired, need to optimize and fix design choices leading to undersirable outputs

* complete PR #1 without disjunctive decoding

* removed incorrect tests

* Delete k.txt

* Delete test.py

* Delete test.sh

* revert changes to test scripts

* genutils

* full implementation with testing, no disjunctive yet

* shifted docs

* passing all tests realistically ran locally

* removing accidentally included print statements

* fixed source of error in initial PR test

* fixing the get_device() vs device trap

* fixed documentation docstrings about constrained_beam_search

* fixed tests having failing for Speech2TextModel's floating point inputs

* fix cuda long tensor

* added examples and testing for them and founx & fixed a bug in beam_search and constrained_beam_search

* deleted accidentally added test halting code with assert False

* code reformat

* Update tests/test_generation_utils.py

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

* Update tests/test_generation_utils.py

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

* Update tests/test_generation_utils.py

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

* Update tests/test_generation_utils.py

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

* Update tests/test_generation_utils.py

* fixing based on comments on PR

* took out the testing code that should but work fails without the beam search moditification ; style changes

* fixing comments issues

* docstrings for ConstraintListState

* typo in PhrsalConstraint docstring

* docstrings improvements

* finished adding what is sort of an opinionated implementation of disjunctive generation, but it revealed errors in inner beam search logic during testing.

* fixed bug found in constrained beam search that used beam_idx that were not global across all the batches

* disjunctive constraint working 100% correctly

* passing all tests

* Accidentally included mlruns

* Update src/transformers/generation_beam_constraints.py

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

* Update src/transformers/generation_beam_constraints.py

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

* complete overhaul of type complexities and other nits

* strict type checks in generate()

* fixing second round of feedback by narsil

* fixed failing generation test because of type check overhaul

* generation test fail fix

* fixing test fails

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

* Resolve vptq conflict

* Rename spqr package to spqr_quant

* Get rid of aqlm mention

* Start working on tests

* Resolve ruff code checks

* Ruff format

* Isort

* Test updates

* Add gpu tag

* Rename to modules_to_not_convert

* Config update

* Docs and config update

* Docs and config update

* Update to update_torch_dtype

* spqr config parameter validation

* Ruff update

* Apply ruff fixes

* Test fixes

* Ruff update

* Mark tests as @slow again; Ruff; Docstring update

* Ruff

* Remove absolute path

* Resolve typo

* Remove redundandt log

* Check accelerate/spqr availability

* Ruff fix

* Check if the config contains proper shapes

* Ruff test

* Documentation update

* overview update

* Ruff checks

* Ruff code quality

* Make style

* Update docs/source/en/quantization/spqr.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update spqr.md

* Enable gptqmodel (huggingface#35012)

* gptqmodel

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix format

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* update readme

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* gptqmodel need use checkpoint_format (#1)

* gptqmodel need use checkpoint_format

* fix quantize

* Update quantization_config.py

* Update quantization_config.py

* Update quantization_config.py

---------

Co-authored-by: ZX-ModelCloud <zx@modelcloud.ai>
Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai>

* Revert quantizer_gptq.py (#2)

* revert quantizer_gptq.py change

* pass **kwargs

* limit gptqmodel and optimum version

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix format

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix warning

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix version check

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* revert unrelated changes

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* enable gptqmodel tests

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix requires gptq

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* Fix Transformer compat (#3)

* revert quantizer_gptq.py change

* pass **kwargs

* add meta info

* cleanup

* cleanup

* Update quantization_config.py

* hf_select_quant_linear pass checkpoint_format and meta

* fix GPTQTestCUDA

* Update test_gptq.py

* gptqmodel.hf_select_quant_linear() now does not select ExllamaV2

* cleanup

* add backend

* cleanup

* cleanup

* no need check exllama version

* Update quantization_config.py

* lower checkpoint_format and backend

* check none

* cleanup

* Update quantization_config.py

* fix self.use_exllama == False

* spell

* fix unittest

* fix unittest

---------

Co-authored-by: LRL <lrl@lbx.dev>
Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai>

* fix format

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix format again

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* update gptqmodel version (huggingface#6)

* update gptqmodel version

* update gptqmodel version

* fix unit test (#5)

* update gptqmodel version

* update gptqmodel version

* "not self.use_exllama" is not equivalent to "self.use_exllama==False"

* fix unittest

* update gptqmodel version

* backend is loading_attibutes (huggingface#7)

* fix format and tests

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix memory check

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix device mismatch

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix result check

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* Update src/transformers/quantizers/quantizer_gptq.py

Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* Update src/transformers/quantizers/quantizer_gptq.py

Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* Update src/transformers/quantizers/quantizer_gptq.py

Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* update tests

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* review: update docs (huggingface#10)

* review: update docs (huggingface#12)

* review: update docs

* fix typo

* update tests for gptqmodel

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* update document (huggingface#9)

* update overview.md

* cleanup

* Update overview.md

* Update overview.md

* Update overview.md

* update gptq.md

* Update gptq.md

* Update gptq.md

* Update gptq.md

* Update gptq.md

* Update gptq.md

* Update gptq.md

---------

Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai>

* typo

* doc note for asymmetric quant

* typo with apple silicon(e)

* typo for marlin

* column name revert: review

* doc rocm support

* Update docs/source/en/quantization/gptq.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/quantization/gptq.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/quantization/gptq.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/quantization/gptq.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/quantization/overview.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Update docs/source/en/quantization/overview.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

---------

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
Co-authored-by: LRL-ModelCloud <165116337+LRL-ModelCloud@users.noreply.github.com>
Co-authored-by: ZX-ModelCloud <zx@modelcloud.ai>
Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai>
Co-authored-by: ZX-ModelCloud <165115237+ZX-ModelCloud@users.noreply.github.com>
Co-authored-by: LRL <lrl@lbx.dev>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Fix : Nemotron Processor in GGUF conversion (huggingface#35708)

* fixing nemotron processor

* make style

* Update docs/source/en/quantization/spqr.md

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Add missing TOC to doc

---------

Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: jiqing-feng <jiqing.feng@intel.com>
Co-authored-by: LRL-ModelCloud <165116337+LRL-ModelCloud@users.noreply.github.com>
Co-authored-by: ZX-ModelCloud <zx@modelcloud.ai>
Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai>
Co-authored-by: ZX-ModelCloud <165115237+ZX-ModelCloud@users.noreply.github.com>
Co-authored-by: LRL <lrl@lbx.dev>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

…uggingface#36457)

Fixed 2 issues regarding `tests/trainer/test_data_collator.py::TFDataCollatorIntegrationTest::test_all_mask_replacement`:
1. I got the error `RuntimeError: "bernoulli_tensor_cpu_p_" not implemented for 'Long'`. This is because the `mask_replacement_prob=1` and `torch.bernoulli` doesn't accept this type (which would be a `torch.long` dtype instead. I fixed this by manually casting the probability arguments in the `__post_init__` function of `DataCollatorForLanguageModeling`.
2. I also got the error `tensorflow.python.framework.errors_impl.InvalidArgumentError: cannot compute Equal as input #1(zero-based) was expected to be a int64 tensor but is a int32 tensor [Op:Equal]` due to the line `tf.reduce_all((batch["input_ids"] == inputs) | (batch["input_ids"] == tokenizer.mask_token_id))` in `test_data_collator.py`. This occurs because the type of the `inputs` variable is `tf.int32`. Solved this by manually casting it to `tf.int64` in the test, as the expected return type of `batch["input_ids"]` is `tf.int64`.