GitLab

* add tests with multiple eos_token_ids

* make math.prod instead of sum

* make fixup

* fix long and also use np.prod since math.prod does not exist <python 3.8

* make fixup

* add prod util

* use prod util instead of np.prod

* make fixup

* previous .long location

* use tensor ops

* remove prod

* remove prod

* update device

* make fixup

* fix none

* Remove mentions of flake8/isort

* Clean up inits

* Deall with all other inits

* Last special rule for dummy files

* fix past renamed to past_key_value

* update more `past`that were ski^êd

* fixup

* remove changes made to rag

* refactor `_reorder_cache` to use `past_key_values`

* fix git `prepare_inputs_for_generation` to pass tests when false is needed in use_cache

* Result of black 23.1

* Update target to Python 3.7

* Switch flake8 to ruff

* Configure isort

* Configure isort

* Apply isort with line limit

* Put the right black version

* adapt black in check copies

* Fix copies

input_ids_seq_length doesn't exist in the GenerationConfig, it exists as local variable in the function.

Setting exponential_decay_length_penalty therefore results in an error:
`AttributeError: 'GenerationConfig' object has no attribute 'input_ids_seq_length'`

This simple change fixes this issue, and the exponential_decay_length_penalty works as expected.

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

* Let huggingface_hub manage token retrieval

* flake8

* code quality

* adapt in every PushToHubMixin children

* add explicit return type

* another patch

* fix timestamp test modeling

* let it be negative when the token is None

* add small patch

* update tests, forced decoder ids is not prioritary against generation config

* fix two new tests

Currently, it incorrectly states that the exponential_decay_length_penalty tuple parameter is optional.

Also changed the corresponding type hint to be more specific.

* update whisper logit processor

* add generate for whisper

* remove part of the whisper specific code from pipeline

* update logit processes

* major update

* enforce first timestamp

* update generate

* add more tests

* update new decoding strategy

* Apply suggestions from code review

* update docstring

* fixup

* default config will not have multilingual ar

* update expected tokenizer size, see pull on the hub for whisper-tiny

* add additional kwargs handling

* fix issue when serializing

* correct order of kwargs removal for serialization in from dict

* add `dict_torch_dtype_to_str` in case a dtype is needed for generation

* add condition when adding the kwargs : not from config

* Add comment based on review
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* add test function

* default None when poping arg
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

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

* Add hallucination penalty

* Make quality changes

* Inverse penalty

* Fix imports & quality

* Fix name spelling issue

* set encoder_repetition_penalty and fix quality

* Fix failing test

* Add to config_common_kwargs

* Fix modelling_rag error

* Update src/transformers/generation_logits_process.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Remove breakpoint

* Make style fixes

* Update encoder_repetition_penalty default value

* Merge latest main changes

* Make fixup changes

* Add EncoderRepetitionPenaltyLogitsProcessor to generation/__init__.py

* Fix repo-inconsistency

* Remove venv

* Remove tensorflow-macos & add tests

* Add documentation

* Fix quality issues

* move encoder_repetition_penalty to config

* Update src/transformers/configuration_utils.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update src/transformers/generation/configuration_utils.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Remove encoder_repetition_penalty from tests

* Fix type error

* Fix format error
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Add epsilon- and eta-sampling.

Add epsilon- and eta-sampling, following the official code from https://github.com/john-hewitt/truncation-sampling and adapting to be more configurable, as required by Huggingface transformers.

* Add unit tests for epsilon- and eta-sampling.

* Black: fix code formatting.

* Fix docstring spacing.

* Clean up newlines.

* Fix implementation bugs and their associated tests.

* Remove epsilon- and eta-sampling parameters from PretrainedConfig.

* Clarify and clean up the documentation.

* Remove parameters for PretrainedConfig test.

* initial commit, refactoring the text generation api reference

* removed repetitive code examples

* Refactoring the text generation docs to reduce repetition

* make style

* add draft logit processor

* add template functions

* update timesapmt processor parameters

* draft script

* simplify code

* cleanup

* fixup and clean

* update pipeline

* style

* clean up previous idea

* add tokenization utils

* update tokenizer and asr output

* fit whisper type

* style and update test

* clean test

* style test

* update tests

* update error test

* udpate code (not based on review yet)

* update tokenization

* update asr pipeline

* update code

* cleanup and update test

* fmt

* remove text verificatino

* cleanup

* cleanup

* add model test

* update tests

* update code add docstring

* update code and add docstring

* fix pipeline tests

* add draft logit processor

add template functions

update timesapmt processor parameters

draft script

simplify code

cleanup

fixup and clean

update pipeline

style

clean up previous idea

add tokenization utils

update tokenizer and asr output

fit whisper type

style and update test

clean test

style test

update tests

update error test

udpate code (not based on review yet)

update tokenization

update asr pipeline

update code

cleanup and update test

fmt

remove text verificatino

cleanup

cleanup

add model test

update tests

update code add docstring

update code and add docstring

fix pipeline tests

* Small update.

* Fixup.

* Tmp.

* More support.

* Making `forced_decoder_ids` non mandatory for users to set.

* update and fix first bug

* properly process sequence right after merge if last

* tofo

* allow list inputs + compute begin index better

* start adding tests

* add the 3 edge cases

* style

* format sequences

* fixup

* update

* update

* style

* test passes, edge cases should be good

* update last value

* remove Trie

* update tests and expec ted values

* handle bigger chunk_length

* clean tests a bit

* refactor chunk iter and clean pipeline

* update tests

* style

* refactor chunk iter and clean pipeline

* upade

* resolve comments

* Apply suggestions from code review
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* take stride right into account

* update test expected values

* Update code based on review
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: sgugger <sylvain.gugger@gmail.com>

* Clarify and add missing typical_p docstring.

* Make the docstring easier to understand.

* Clarify typical_p docstring

Accept the suggestion by @stevhliu for paraphrasing the docstring.
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Use the same docstring as in GenerationConfig

Follow the suggestion suggested by @stevhliu in the pull request conversation.

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

The max of top_k and min_tokens_to_keep performed on every call can just be done once up-front.

Add `min_new_tokens` argument in generate() (implementation based on `MinNewTokensLengthLogitsProcessor`) (#21044)

add a new parameter min_new_tokens for generate()

* start cleanup

* more updates

* more models are affected

* more updates

* update generation utils

* style

* revert change that removed reorder cachce

* update generation utils

* style

* style

* remove reorder cache

* Add StopIdStoppingCriteria

* add a working test for stop id criteria

* add to global scope

* add stop_ids to generate

* add pipeline test

* use tokenizer encode in test

* add test to generation utils

* reformat

* fixup

* make-fix-copies

* rename to stop_token_id

* use stop_tokens instead

* add to text to text generation

* make fixup

* make repo-consistency

* Add support for list of ints for eos_token_id inside generation/utils.py

* Instead of having if elses, cast the eos_token_id into a List[int]

* Add List[int] support for logits_process.py

* add List[int] for beam_search.py

* add List[int] for forced_eos_token_id

* revert stop token id stopping criteria changes

* make fixup

* fix tests

* add eos_token_id to generation/utils.py and added tests test_utils.py

* add eos_token_id type hints and fix for pad tokens

* add comments

* remove some prints and remove forced false test

* fix

* put back test_stop_sequence_stopping_criteria

* remove unused import and make fixup

* add a none check

* update docstring

* add more docstring for list ints

* make fixup

* Enable `decoder_attention_mask` in `generate` function

* Make style corrections

* Run `make repo-consistency`

* Add integration test

* feat: add min new length logit processor

* test: add min new length logit processor

* docs: add MinNewTokensLengthLogitsProcessor

* feat: import MinNewTokensLengthLogitsProcessor

* fix: update pytorch dummy objects

* refactor & fix: rename attributes and var and get rid of dynamic attribute

* tests: align test with new interface

* docs: fix typo

* docs: minor clarification

* Empty-Commit

* empty commit

* run automated quality edits
Co-authored-by: Joao Gante <joao@huggingface.co>

* beam sample in beam search

* rag now works with the updated beam search

* delete legacy (non-XLA) generation code related to beam sample

correctly detect default max length

* fix doctests

* revert unwanted change