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  1. 14 Dec, 2021 1 commit
    • Nicolas Patry's avatar
      Fixing tests for Perceiver (#14739) · 546a91ab
      Nicolas Patry authored 
      * Adding some slow test to check for perceiver at least from a high level.

* Re-enabling fast tests for Perceiver ImageClassification.

* Perceiver might try to run without Tokenizer (Fast doesn't exist) and
with FeatureExtractor some text only pipelines.

* Oops.

* Adding a comment for `update_config_with_model_class`.

* Remove `model_architecture` to get `tiny_config`.

* Finalize rebase.

* Smarter way to handle undefined FastTokenizer.

* Remove old code.

* Addressing some nits.

* Don't instantiate `None`.
      546a91ab
  3. 13 Dec, 2021 1 commit
    • Lysandre Debut's avatar
      Fixing tests for Perceiver (#14745) · 3d66146a
      Lysandre Debut authored 
      

- Do not run image-classification pipeline (_CHECKPOINT_FOR_DOC uses the checkpoint for
langage, which cannot load a FeatureExtractor so current logic fails).
- Add a safeguard to not run tests when `tokenizer_class` or
`feature_extractor_class` **are** defined, but cannot be loaded
This happens for Perceiver for the "FastTokenizer" (which doesn't exist
so None) and FeatureExtractor (which does exist but cannot be loaded
because the checkpoint doesn't define one which is reasonable for the
said checkpoint)
- Added `get_vocab` function to `PerceiverTokenizer` since it is used by
`fill-mask` pipeline when the argument `targets` is used to narrow a
subset of possible values.
Co-authored-by: default avatarNicolas Patry <patry.nicolas@protonmail.com>
      3d66146a
  5. 08 Dec, 2021 1 commit
  7. 22 Nov, 2021 1 commit
  9. 19 Nov, 2021 1 commit
  11. 12 Nov, 2021 1 commit
    • Nicolas Patry's avatar
      Adding support for raw python `generator` in addition to `Dataset` for pipelines (#14352) · ed5d1551
      Nicolas Patry authored 
      * Adding support for raw python `generator` in addition to `Dataset`

The main goal is to ease the create of streaming data to the pipe.

`Dataset` is more involved and pytorch specific.

This PR, provides a way to use a python iterator too.
This enabled #14250 but can be proposed as a standalone PR.

```python
from transformers import pipeline

def read_data(filename):
    with open(filename, 'r') as f:
        for line in f:
            yield f

pipe = pipeline("text-classification")
for classified in pipe(read_data("large_file.txt")):
    print("Success ! ", classified)
```

The main caveat of this, is the interaction with `DataLoader` with
`num_workers>1`. When you have multiple workers, each receive a copy
of the generator (like `IterableDataset`). That means the naive Iterator
will fail since all workers iterate on all items of the generator.

There are ways to do clever "skipping", but it could be bad still
because all workers still do have to pass through all items of the
generator (they just ignore items they don't handle), depending on
the case it might be bad.

Using `num_workers=1` is the simplest fix and if the cost of loading
your data is small enough should be good enough. In the above example
trying to do smart tricks to skip some lines is unlikely to be a net
positive for instance.

If there are better ways to do "jumps" on some data, then using
`Dataset` is more advised (since then differents workers can just jump
themselves).

* Adding iterator support for `tf` too.
      ed5d1551
  13. 10 Nov, 2021 1 commit
  15. 03 Nov, 2021 1 commit
  17. 29 Oct, 2021 3 commits
  19. 14 Oct, 2021 1 commit
  21. 10 Sep, 2021 1 commit
    • Nicolas Patry's avatar
      [Large PR] Entire rework of pipelines. (#13308) · c63fcabf
      Nicolas Patry authored 
      

* Enabling dataset iteration on pipelines.

Enabling dataset iteration on pipelines.

Unifying parameters under `set_parameters` function.

Small fix.

Last fixes after rebase

Remove print.

Fixing text2text `generate_kwargs`

No more `self.max_length`.

Fixing tf only conversational.

Consistency in start/stop index over TF/PT.

Speeding up drastically on TF (nasty bug where max_length would increase
a ton.)

Adding test for support for non fast tokenizers.

Fixign GPU usage on zero-shot.

Fix working on Tf.

Update src/transformers/pipelines/base.py
Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>

Update src/transformers/pipelines/base.py
Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>

Small cleanup.

Remove all asserts + simple format.

* Fixing audio-classification for large PR.

* Overly explicity null checking.

* Encapsulating GPU/CPU pytorch manipulation directly within `base.py`.

* Removed internal state for parameters of the  pipeline.

Instead of overriding implicitly internal state, we moved
to real named arguments on every `preprocess`, `_forward`,
`postprocess` function.

Instead `_sanitize_parameters` will be used to split all kwargs
of both __init__ and __call__ into the 3 kinds of named parameters.

* Move import warnings.

* Small fixes.

* Quality.

* Another small fix, using the CI to debug faster.

* Last fixes.

* Last fix.

* Small cleanup of tensor moving.

* is not None.

* Adding a bunch of docs + a iteration test.

* Fixing doc style.

* KeyDataset = None guard.

* RRemoving the Cuda test for pipelines (was testing).

* Even more simple iteration test.

* Correct import .

* Long day.

* Fixes in docs.

* [WIP] migrating object detection.

* Fixed the target_size bug.

* Fixup.

* Bad variable name.

* Fixing `ensure_on_device` respects original ModelOutput.
      c63fcabf
  23. 27 Aug, 2021 2 commits
  25. 26 Aug, 2021 2 commits
  27. 13 Aug, 2021 1 commit
    • Nicolas Patry's avatar
      Moving fill-mask pipeline to new testing scheme (#12943) · d58926ab
      Nicolas Patry authored 
      * Fill mask pipelines test updates.

* Model eval !!

* Adding slow test with actual values.

* Making all tests pass (skipping quite a bit.)

* Doc styling.

* Better doc cleanup.

* Making an explicit test with no pad token tokenizer.

* Typo.
      d58926ab
  29. 29 Jul, 2021 1 commit
  31. 22 Jul, 2021 1 commit
    • Nicolas Patry's avatar
      Improving pipeline tests (#12784) · 795c1444
      Nicolas Patry authored 
      

* Proposal

* Testing pipelines slightly better.

- Overall same design
- Metaclass to get proper different tests instead of subTest (not well
supported by Pytest)
- Added ANY meta object to make output checking more readable.
- Skipping architectures either without tiny_config or without
architecture.

* Small fix.

* Fixing the tests in case of None value.

* Oups.

* Rebased with more architectures.

* Fixing reformer tests (no override anymore).

* Adding more options for model tester config.
Co-authored-by: default avatarLysandre <lysandre.debut@reseau.eseo.fr>
      795c1444
  33. 18 May, 2021 1 commit
  35. 25 Feb, 2021 1 commit
    • Patrick von Platen's avatar
      [PretrainedFeatureExtractor] + Wav2Vec2FeatureExtractor, Wav2Vec2Processor,... · cb38ffcc
      Patrick von Platen authored 
      [PretrainedFeatureExtractor] + Wav2Vec2FeatureExtractor, Wav2Vec2Processor, Wav2Vec2Tokenizer (#10324)

* push to show

* small improvement

* small improvement

* Update src/transformers/feature_extraction_utils.py

* Update src/transformers/feature_extraction_utils.py

* implement base

* add common tests

* make all tests pass for wav2vec2

* make padding work & add more tests

* finalize feature extractor utils

* add call method to feature extraction

* finalize feature processor

* finish tokenizer

* finish general processor design

* finish tests

* typo

* remove bogus file

* finish docstring

* add docs

* finish docs

* small fix

* correct docs

* save intermediate

* load changes

* apply changes

* apply changes to doc

* change tests

* apply surajs recommend

* final changes

* Apply suggestions from code review

* fix typo

* fix import

* correct docstring
      cb38ffcc
  37. 07 Dec, 2020 1 commit
  39. 15 Nov, 2020 1 commit
    • Thomas Wolf's avatar
      [breaking|pipelines|tokenizers] Adding slow-fast tokenizers equivalence tests... · f4e04cd2
      Thomas Wolf authored 
      
[breaking|pipelines|tokenizers] Adding slow-fast tokenizers equivalence tests pipelines - Removing sentencepiece as a required dependency (#8073)

* Fixing roberta for slow-fast tests

* WIP getting equivalence on pipelines

* slow-to-fast equivalence - working on question-answering pipeline

* optional FAISS tests

* Pipeline Q&A

* Move pipeline tests to their own test job again

* update tokenizer to add sequence id methods

* update to tokenizers 0.9.4

* set sentencepiecce as optional

* clean up squad

* clean up pipelines to use sequence_ids

* style/quality

* wording

* Switch to use_fast = True by default

* update tests for use_fast at True by default

* fix rag tokenizer test

* removing protobuf from required dependencies

* fix NER test for use_fast = True by default

* fixing example tests (Q&A examples use slow tokenizers for now)

* protobuf in main deps extras["sentencepiece"] and example deps

* fix protobug install test

* try to fix seq2seq by switching to slow tokenizers for now

* Update src/transformers/tokenization_utils_base.py
Co-authored-by: default avatarLysandre Debut <lysandre@huggingface.co>

* Update src/transformers/tokenization_utils_base.py
Co-authored-by: default avatarLysandre Debut <lysandre@huggingface.co>
Co-authored-by: default avatarLysandre Debut <lysandre@huggingface.co>
      f4e04cd2
  41. 02 Nov, 2020 1 commit
  43. 23 Oct, 2020 1 commit