transformers/docs/source/main_classes/pipelines.rst
Nicolas Patry db9dd09cf9
Adding AutomaticSpeechRecognitionPipeline. (#11337)
* Adding `AutomaticSpeechRecognitionPipeline`.

- Because we added everything to enable this pipeline, we probably
should add it to `transformers`.
- This PR tries to limit the scope and focuses only on the pipeline part
(what should go in, and out).
- The tests are very specific for S2T and Wav2vec2 to make sure both
architectures are supported by the pipeline. We don't use the mixin for
tests right now, because that requires more work in the `pipeline`
function (will be done in a follow up PR).
- Unsure about the "helper" function `ffmpeg_read`. It makes a lot of
  sense from a user perspective, it does not add any additional
dependencies (as in hard dependency, because users can always use their
own load mechanism). Meanwhile, it feels slightly clunky to have so much
optional preprocessing.
- The pipeline is not done to support streaming audio right now.

Future work:

- Add `automatic-speech-recognition` as a `task`. And add the
FeatureExtractor.from_pretrained within `pipeline` function.
- Add small models within tests
- Add the Mixin to tests.
- Make the logic between ForCTC vs ForConditionalGeneration better.

* Update tests/test_pipelines_automatic_speech_recognition.py

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

* Adding docs + main import + type checking + LICENSE.

* Doc style !.

* Fixing TYPE_HINT.

* Specifying waveform shape in the docs.

* Adding asserts + specify in the documentation the shape of the input
np.ndarray.

* Update src/transformers/pipelines/automatic_speech_recognition.py

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

* Adding require to tests + move the `feature_extractor` doc.

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
2021-04-30 11:54:08 +02:00

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..
Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
Pipelines
-----------------------------------------------------------------------------------------------------------------------
The pipelines are a great and easy way to use models for inference. These pipelines are objects that abstract most of
the complex code from the library, offering a simple API dedicated to several tasks, including Named Entity
Recognition, Masked Language Modeling, Sentiment Analysis, Feature Extraction and Question Answering. See the
:doc:`task summary <../task_summary>` for examples of use.
There are two categories of pipeline abstractions to be aware about:
- The :func:`~transformers.pipeline` which is the most powerful object encapsulating all other pipelines.
- The other task-specific pipelines:
- :class:`~transformers.AutomaticSpeechRecognitionPipeline`
- :class:`~transformers.ConversationalPipeline`
- :class:`~transformers.FeatureExtractionPipeline`
- :class:`~transformers.FillMaskPipeline`
- :class:`~transformers.QuestionAnsweringPipeline`
- :class:`~transformers.SummarizationPipeline`
- :class:`~transformers.TextClassificationPipeline`
- :class:`~transformers.TextGenerationPipeline`
- :class:`~transformers.TokenClassificationPipeline`
- :class:`~transformers.TranslationPipeline`
- :class:`~transformers.ZeroShotClassificationPipeline`
- :class:`~transformers.Text2TextGenerationPipeline`
- :class:`~transformers.TableQuestionAnsweringPipeline`
The pipeline abstraction
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The `pipeline` abstraction is a wrapper around all the other available pipelines. It is instantiated as any other
pipeline but requires an additional argument which is the `task`.
.. autofunction:: transformers.pipeline
The task specific pipelines
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
AutomaticSpeechRecognitionPipeline
=======================================================================================================================
.. autoclass:: transformers.AutomaticSpeechRecognitionPipeline
:special-members: __call__
:members:
ConversationalPipeline
=======================================================================================================================
.. autoclass:: transformers.Conversation
.. autoclass:: transformers.ConversationalPipeline
:special-members: __call__
:members:
FeatureExtractionPipeline
=======================================================================================================================
.. autoclass:: transformers.FeatureExtractionPipeline
:special-members: __call__
:members:
FillMaskPipeline
=======================================================================================================================
.. autoclass:: transformers.FillMaskPipeline
:special-members: __call__
:members:
NerPipeline
=======================================================================================================================
.. autoclass:: transformers.NerPipeline
See :class:`~transformers.TokenClassificationPipeline` for all details.
QuestionAnsweringPipeline
=======================================================================================================================
.. autoclass:: transformers.QuestionAnsweringPipeline
:special-members: __call__
:members:
SummarizationPipeline
=======================================================================================================================
.. autoclass:: transformers.SummarizationPipeline
:special-members: __call__
:members:
TableQuestionAnsweringPipeline
=======================================================================================================================
.. autoclass:: transformers.TableQuestionAnsweringPipeline
:special-members: __call__
TextClassificationPipeline
=======================================================================================================================
.. autoclass:: transformers.TextClassificationPipeline
:special-members: __call__
:members:
TextGenerationPipeline
=======================================================================================================================
.. autoclass:: transformers.TextGenerationPipeline
:special-members: __call__
:members:
Text2TextGenerationPipeline
=======================================================================================================================
.. autoclass:: transformers.Text2TextGenerationPipeline
:special-members: __call__
:members:
TokenClassificationPipeline
=======================================================================================================================
.. autoclass:: transformers.TokenClassificationPipeline
:special-members: __call__
:members:
TranslationPipeline
=======================================================================================================================
.. autoclass:: transformers.TranslationPipeline
:special-members: __call__
:members:
ZeroShotClassificationPipeline
=======================================================================================================================
.. autoclass:: transformers.ZeroShotClassificationPipeline
:special-members: __call__
:members:
Parent class: :obj:`Pipeline`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.Pipeline
:members: