| 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"), |
| } |
| ), |
| |
| |
| 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 |
