import json import datasets _DESCRIPTION = "MTOP: Multilingual Task-Oriented Semantic Parsing" _LANGUAGES = ["en", "de", "es", "fr", "hi", "th"] URL = "" _URLs = { split: { "train": URL + f"{split}/train.jsonl", "test": URL + f"{split}/test.jsonl", "validation": URL + f"{split}/validation.jsonl", } for split in _LANGUAGES } class MTOP(datasets.GeneratorBasedBuilder): """MTOP Dataset.""" BUILDER_CONFIGS = [ datasets.BuilderConfig(name=name, description=f"This part of my dataset covers {name} part of MTOP Dataset.",) for name in _LANGUAGES ] DEFAULT_CONFIG_NAME = "en" def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "id": datasets.Value("int64"), "text": datasets.Value("string"), "label": datasets.Value("int32"), "label_text": datasets.Value("string"), } ), supervised_keys=None, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" my_urls = _URLs[self.config.name] data_dir = dl_manager.download_and_extract(my_urls) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, # These kwargs will be passed to _generate_examples gen_kwargs={"text_path": data_dir["train"]}, ), datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"text_path": data_dir["validation"]},), datasets.SplitGenerator( name=datasets.Split.TEST, # These kwargs will be passed to _generate_examples gen_kwargs={"text_path": data_dir["test"]}, ), ] def _generate_examples(self, text_path): """Yields examples.""" with open(text_path, encoding="utf-8") as f: texts = f.readlines() for i, text in enumerate(texts): yield i, json.loads(text)