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Supported pipeline tasks update (#21268)

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* added tasks from SUPPORTED_TASKS to docstrings

* make style

* sorted the tasks in the docstrtings in alphabetical order
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Maria Khalusova 2023-01-23 14:23:20 -05:00 committed by GitHub
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1 changed files with 19 additions and 2 deletions
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src/transformers/pipelines/__init__.py
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@ -427,10 +427,16 @@ def check_task(task: str) -> Tuple[str, Dict, Any]:
- `"audio-classification"`
- `"automatic-speech-recognition"`
- `"conversational"`
- `"depth-estimation"`
- `"document-question-answering"`
- `"feature-extraction"`
- `"fill-mask"`
- `"image-classification"`
- `"image-segmentation"`
- `"image-to-text"`
- `"object-detection"`
- `"question-answering"`
- `"summarization"`
- `"table-question-answering"`
- `"text2text-generation"`
- `"text-classification"` (alias `"sentiment-analysis"` available)
@ -438,9 +444,11 @@ def check_task(task: str) -> Tuple[str, Dict, Any]:
- `"token-classification"` (alias `"ner"` available)
- `"translation"`
- `"translation_xx_to_yy"`
- `"summarization"`
- `"video-classification"`
- `"visual-question-answering"`
- `"zero-shot-classification"`
- `"zero-shot-image-classification"`
- `"zero-shot-object-detection"`
Returns:
(normalized_task: `str`, task_defaults: `dict`, task_options: (`tuple`, None)) The normalized task name
@ -502,10 +510,16 @@ def pipeline(
- `"audio-classification"`: will return a [`AudioClassificationPipeline`].
- `"automatic-speech-recognition"`: will return a [`AutomaticSpeechRecognitionPipeline`].
- `"conversational"`: will return a [`ConversationalPipeline`].
- `"depth-estimation"`: will return a [`DepthEstimationPipeline`].
- `"document-question-answering"`: will return a [`DocumentQuestionAnsweringPipeline`].
- `"feature-extraction"`: will return a [`FeatureExtractionPipeline`].
- `"fill-mask"`: will return a [`FillMaskPipeline`]:.
- `"image-classification"`: will return a [`ImageClassificationPipeline`].
- `"image-segmentation"`: will return a [`ImageSegmentationPipeline`].
- `"image-to-text"`: will return a [`ImageToTextPipeline`].
- `"object-detection"`: will return a [`ObjectDetectionPipeline`].
- `"question-answering"`: will return a [`QuestionAnsweringPipeline`].
- `"summarization"`: will return a [`SummarizationPipeline`].
- `"table-question-answering"`: will return a [`TableQuestionAnsweringPipeline`].
- `"text2text-generation"`: will return a [`Text2TextGenerationPipeline`].
- `"text-classification"` (alias `"sentiment-analysis"` available): will return a
@ -514,8 +528,11 @@ def pipeline(
- `"token-classification"` (alias `"ner"` available): will return a [`TokenClassificationPipeline`].
- `"translation"`: will return a [`TranslationPipeline`].
- `"translation_xx_to_yy"`: will return a [`TranslationPipeline`].
- `"summarization"`: will return a [`SummarizationPipeline`].
- `"video-classification"`: will return a [`VideoClassificationPipeline`].
- `"visual-question-answering"`: will return a [`VisualQuestionAnsweringPipeline`].
- `"zero-shot-classification"`: will return a [`ZeroShotClassificationPipeline`].
- `"zero-shot-image-classification"`: will return a [`ZeroShotImageClassificationPipeline`].
- `"zero-shot-object-detection"`: will return a [`ZeroShotObjectDetectionPipeline`].
model (`str` or [`PreTrainedModel`] or [`TFPreTrainedModel`], *optional*):
The model that will be used by the pipeline to make predictions. This can be a model identifier or an