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Tasks alignment with models #4066

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Merged
lhoestq merged 7 commits into from
Apr 8, 2022
Merged

Tasks alignment with models #4066

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3bdf2d5
update tasks list
lhoestq Mar 30, 2022
ba10285
revert bad task verification
lhoestq Mar 30, 2022
df3d8b2
speaker-language-identification -> language-identification
lhoestq Apr 1, 2022
8f3add0
speaker-intent-classification -> intent-classification
lhoestq Apr 1, 2022
0df92da
add tabular-classification subtasks from autotrain
lhoestq Apr 4, 2022
b113371
add "audio-" prefix to some audio-classification subtasks
lhoestq Apr 4, 2022
644e008
underscores to dashes
lhoestq Apr 4, 2022
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2 changes: 1 addition & 1 deletion src/datasets/utils/metadata.py
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Original file line number Diff line number Diff line change
Expand Up @@ -321,7 +321,7 @@ def validate_task_categories(task_categories: Union[List[str], Dict[str, List[st
def validate_task_ids(task_ids: Union[List[str], Dict[str, List[str]]]) -> ValidatorOutput:
# TODO: we're currently ignoring all values starting with 'other' as our task taxonomy is bound to change
# in the near future and we don't want to waste energy in tagging against a moving taxonomy.
known_set = [tid for _cat, d in known_task_ids.items() for tid in d["options"]]
known_set = [tid for _cat, d in known_task_ids.items() for tid in d.get("subtasks", [])]
validated, error = tagset_validator(
task_ids, known_set, "task_ids", known_task_ids_url, lambda e: "-other-" in e or e.startswith("other-")
)
Expand Down
265 changes: 165 additions & 100 deletions src/datasets/utils/resources/tasks.json
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Original file line number Diff line number Diff line change
@@ -1,54 +1,115 @@
{
"conditional-text-generation": {
"description": "data-to-text and text transduction tasks such as translation or summarization",
"options": [
"machine-translation",
"sentence-splitting-fusion",
"summarization",
"table-to-text",
"text-simplification",
"explanation-generation",
"other-structured-to-text",
"other"
"audio-classification": {
"type": "audio",
"subtasks": [
"keyword-spotting",
"speaker-identification",
"audio-intent-classification",
"audio-emotion-recognition",
"audio-language-identification"
]
},
"question-answering": {
"description": "question answering tasks",
"options": [
"open-domain-qa",
"closed-domain-qa",
"audio-to-audio": {
"type": "audio"
},
"automatic-speech-recognition": {
"type": "multimodal"
},
"conversational": {
"type": "text",
"subtasks": [
"dialogue-generation"
]
},
"feature-extraction": {
"type": "multimodal"
},
"fill-mask": {
"type": "text",
"subtasks": [
"slot-filling",
"masked-language-modeling"
]
},
"image-classification": {
"type": "image",
"subtasks": [
"multi-label-image-classification",
"multi-class-image-classification"
]
},
"image-segmentation": {
"type": "image",
"subtasks": [
"instance-segmentation",
"semantic-segmentation",
"panoptic-segmentation"
]
},
"image-to-text": {
"type": "multimodal",
"subtasks": [
"image-captioning"
]
},
"multiple-choice": {
"type": "text",
"subtasks": [
"multiple-choice-qa",
"multiple-choice-coreference-resolution"
]
},
"object-detection": {
"type": "image",
"subtasks": [
"face-detection",
"vehicle-detection"
]
},
"question-answering": {
"type": "text",
"aliases": [
"extractive-question-answering"
],
"subtasks": [
"extractive-qa",
"abstractive-qa",
"other"
"open-domain-qa",
"closed-domain-qa"
]
},
"sequence-modeling": {
"description": "such as language modeling or dialogue",
"options": [
"dialogue-modeling",
"language-modeling",
"other-multi-turn",
"slot-filling",
"other"
"sentence-similarity": {
"type": "text"
},
"tabular-classification": {
"type": "text",
"subtasks": [
"tabular-multi-class-classification",
"tabular-multi-label-classification",
"tabular-single-column-regression"
]
},
"structure-prediction": {
"description": "predicting structural properties of the text, such as syntax",
"options": [
"coreference-resolution",
"named-entity-recognition",
"part-of-speech-tagging",
"parsing",
"semantic-role-labeling",
"lemmatization",
"word-sense-disambiguation",
"other"
"tabular-to-text": {
"type": "text",
"subtasks": [
"rdf-to-text"
]
},
"summarization": {
"type": "text",
"subtasks": [
"news-articles-summarization",
"news-articles-headline-generation"
]
},
"table-to-text": {
"type": "text"
},
"table-question-answering": {
"type": "text"
},
"text-classification": {
"description": "predicting a class index or boolean value",
"options": [
"type": "text",
"subtasks": [
"acceptability-classification",
"entity-linking-classification",
"fact-checking",
Expand All @@ -59,90 +120,94 @@
"semantic-similarity-classification",
"sentiment-classification",
"topic-classification",
"other"
"semantic-similarity-scoring",
"sentiment-scoring",
"sentiment-analysis",
"hate-speech-detection",
"text-scoring"
]
},
"text-generation": {
"type": "text",
"subtasks": [
"dialogue-modeling",
"language-modeling"
]
},
"text-retrieval": {
"description": "information or text retrieval tasks",
"options": [
"type": "text",
"subtasks": [
"document-retrieval",
"utterance-retrieval",
"entity-linking-retrieval",
"fact-checking-retrieval",
"other"
"fact-checking-retrieval"
]
},
"text-scoring": {
"description": "text scoring tasks, predicting a real valued score for some text",
"options": [
"semantic-similarity-scoring",
"sentiment-scoring",
"other"
"text-to-image": {
"type": "multimodal"
},
"text-to-tabular": {
"type": "text",
"subtasks": [
"relation-extraction",
"semantic-role-labeling"
]
},
"speech-processing": {
"description": "tasks related to the analysis and representations of speech signals",
"options": [
"automatic-speech-recognition",
"phoneme-recognition",
"keyword-spotting",
"query-by-example-spoken-term-detection",
"speaker-identification",
"automatic-speaker-verification",
"speaker-diarization",
"intent-classification",
"slot-filling",
"emotion-recognition"
"text-to-speech": {
"type": "multimodal"
},
"text2text-generation": {
"type": "text",
"subtasks": [
"text-simplification",
"explanation-generation",
"abstractive-qa",
"open-domain-abstractive-qa",
"closed-domain-qa",
"open-book-qa",
"closed-book-qa"
]
},
"time-series-forecasting": {
"description": "tasks related to predicting future values of a time series",
"options": [
"type": "time series",
"subtasks": [
"univariate-time-series-forecasting",
"multivariate-time-series-forecasting"
]
},
"object-detection": {
"description": "tasks related to detecting instances of objects from a particular class in an image",
"options": [
"face-detection",
"other"
"token-classification": {
"type": "text",
"aliases": [
"structure-prediction"
],
"subtasks": [
"named-entity-recognition",
"part-of-speech-tagging",
"parsing",
"lemmatization",
"word-sense-disambiguation",
"coreference-resolution"
]
},
"image-to-text": {
"description": "tasks related to generating text from images",
"options": [
"image-captioning",
"other"
]
"translation": {
"type": "text"
},
"text-to-image": {
"description": "tasks related to generating images from text",
"options": []
"visual-question-answering": {
"type": "multimodal"
},
"image-segmentation": {
"description": "tasks related to detecting and delineating distinct objects in images",
"options": [
"instance-segmentation",
"semantic-segmentation",
"panoptic-segmentation",
"other"
]
"voice-activity-detection": {
"type": "audio"
},
"image-classification": {
"description": "tasks related to identifying what images represent",
"options": [
"multi-label-image-classification",
"single-label-image-classification",
"other"
]

"zero-shot-classification": {
"type": "text"
},
"zero-shot-image-classification": {
"type": "multimodal"
},
"reinforcement-learning": {
"type": "other"
},

"other": {
"description": "other task family not mentioned here",
"options": [
"other"
]
"type": "other"
}
}