Datasets:
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| import datasets | |
| """ | |
| domain in {'alarm', | |
| 'calling', | |
| 'event', | |
| 'messaging', | |
| 'music', | |
| 'news', | |
| 'people', | |
| 'recipes', | |
| 'reminder', | |
| 'timer', | |
| 'weather'} | |
| """ | |
| _URL = "https://fb.me/mtop_dataset" | |
| _CITATION = """@article{li2020mtop, | |
| title={MTOP: A comprehensive multilingual task-oriented semantic parsing benchmark}, | |
| author={Li, Haoran and Arora, Abhinav and Chen, Shuohui and Gupta, Anchit and Gupta, Sonal and Mehdad, Yashar}, | |
| journal={arXiv preprint arXiv:2008.09335}, | |
| year={2020} | |
| }""" | |
| _DESCRIPTION = """ """ | |
| class MtopConfig(datasets.BuilderConfig): | |
| """BuilderConfig for Mtop.""" | |
| def __init__(self, **kwargs): | |
| """BuilderConfig for Mtop. | |
| Args: | |
| **kwargs: keyword arguments forwarded to super. | |
| """ | |
| super(MtopConfig, self).__init__(**kwargs) | |
| class Mtop(datasets.GeneratorBasedBuilder): | |
| BUILDER_CONFIGS = [ | |
| MtopConfig( | |
| name="mtop", | |
| version=datasets.Version("1.0.0", ""), | |
| description="Plain text", | |
| ), | |
| ] | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features( | |
| { | |
| "idx": datasets.Value("string"), | |
| "intent": datasets.Value("string"), | |
| "spans": datasets.Value("string"), | |
| "question": datasets.Value("string"), | |
| "domain": datasets.Value("string"), | |
| "lang": datasets.Value("string"), | |
| "logical_form": datasets.Value("string"), | |
| "tokenized_question": datasets.Value("string"), | |
| } | |
| ), | |
| # No default supervised_keys (as we have to pass both question | |
| # and context as input). | |
| supervised_keys=None, | |
| homepage="", | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| filepath = dl_manager.download_and_extract(_URL) | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": filepath,"split":"train"}), | |
| datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": filepath,"split":"eval"}), | |
| datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": filepath,"split":"test"}), | |
| ] | |
| def _generate_examples(self, filepath, split): | |
| """This function returns the examples in the raw (text) form.""" | |
| key = 0 | |
| for lang in "de en es fr hi th".split(): | |
| with open(f"{filepath}/mtop/{lang}/{split}.txt", encoding="utf-8") as f: | |
| for example in f: | |
| example = example.split("\t") | |
| dict_example = dict(idx=example[0], | |
| intent=example[1], | |
| spans=example[2], | |
| question=example[3], | |
| domain=example[4], | |
| lang=example[5], | |
| logical_form=example[6], | |
| tokenized_question=example[7]) | |
| yield key, dict_example | |
| key += 1 |