import importlib.resources as pkg_resources import json from collections import defaultdict from enum import Enum from types import SimpleNamespace from bigbio.utils import resources from bigbio.utils.license import License from bigbio.utils.schemas import ( entailment_features, kb_features, pairs_features, qa_features, text2text_features, text_features, ) BigBioValues = SimpleNamespace(NULL="") # shamelessly compied from: # https://github.com/huggingface/datasets/blob/master/src/datasets/utils/metadata.py langs_json = pkg_resources.read_text(resources, "languages.json") langs_dict = {k.replace("-", "_").upper(): v for k, v in json.loads(langs_json).items()} Lang = Enum("Lang", langs_dict) METADATA: dict = { "_LOCAL": bool, "_LANGUAGES": Lang, "_PUBMED": bool, "_LICENSE": License, "_DISPLAYNAME": str, } class Tasks(Enum): NAMED_ENTITY_RECOGNITION = "NER" NAMED_ENTITY_DISAMBIGUATION = "NED" EVENT_EXTRACTION = "EE" RELATION_EXTRACTION = "RE" COREFERENCE_RESOLUTION = "COREF" QUESTION_ANSWERING = "QA" TEXTUAL_ENTAILMENT = "TE" SEMANTIC_SIMILARITY = "STS" PARAPHRASING = "PARA" TRANSLATION = "TRANSL" SUMMARIZATION = "SUM" TEXT_CLASSIFICATION = "TXTCLASS" TASK_TO_SCHEMA = { Tasks.NAMED_ENTITY_RECOGNITION: "KB", Tasks.NAMED_ENTITY_DISAMBIGUATION: "KB", Tasks.EVENT_EXTRACTION: "KB", Tasks.RELATION_EXTRACTION: "KB", Tasks.COREFERENCE_RESOLUTION: "KB", Tasks.QUESTION_ANSWERING: "QA", Tasks.TEXTUAL_ENTAILMENT: "TE", Tasks.SEMANTIC_SIMILARITY: "PAIRS", Tasks.PARAPHRASING: "T2T", Tasks.TRANSLATION: "T2T", Tasks.SUMMARIZATION: "T2T", Tasks.TEXT_CLASSIFICATION: "TEXT", } SCHEMA_TO_TASKS = defaultdict(set) for task, schema in TASK_TO_SCHEMA.items(): SCHEMA_TO_TASKS[schema].add(task) SCHEMA_TO_TASKS = dict(SCHEMA_TO_TASKS) VALID_TASKS = set(TASK_TO_SCHEMA.keys()) VALID_SCHEMAS = set(TASK_TO_SCHEMA.values()) SCHEMA_TO_FEATURES = { "KB": kb_features, "QA": qa_features, "TE": entailment_features, "T2T": text2text_features, "TEXT": text_features, "PAIRS": pairs_features, }