| import io |
| import json |
| import zipfile |
|
|
| import datasets |
| from datasets.features import Sequence |
|
|
| _SPLITS = { |
| "training": "./training.zip", |
| "validation_date_in_domain_in": "./validation_date_in_domain_in.zip", |
| "validation_date_in_domain_out": "./validation_date_in_domain_out.zip", |
| "validation_date_out_domain_in": "./validation_date_out_domain_in.zip", |
| "validation_date_out_domain_out": "./validation_date_out_domain_out.zip", |
| } |
| _DESCRIPTION = """\ |
| The DSTC8 dataset as provided in the original form. |
| The only difference is that the splits are in separate zip files. |
| In the orignal output it is one big archive containing all splits. |
| """ |
| _CITATION = """\ |
| @article{lee2019multi, |
| title={Multi-domain task-completion dialog challenge}, |
| author={Lee, S and Schulz, H and Atkinson, A and Gao, J and Suleman, K and El Asri, L and Adada, M and Huang, M and Sharma, S and Tay, W and others}, |
| journal={Dialog system technology challenges}, |
| volume={8}, |
| pages={9}, |
| year={2019} |
| } |
| """ |
| _LICENSE = "Like the original DSTC8 Reddit dataset, this dataset is released under the MIT license." |
| _HOMEPAGE = "https://github.com/microsoft/dstc8-reddit-corpus" |
|
|
|
|
| class DSTC8(datasets.GeneratorBasedBuilder): |
| """ |
| The DSTC8 dataset as provided in the original form. |
| The only difference is that the splits are in separate zip files. |
| In the orignal output it is one big archive containing all splits. |
| """ |
|
|
| VERSION = datasets.Version("1.0.0") |
| BUILDER_CONFIGS = [ |
| datasets.BuilderConfig( |
| name="full", version=VERSION, description="The full dataset." |
| ) |
| ] |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features( |
| { |
| "id": datasets.Value("string"), |
| "domain": datasets.Value("string"), |
| "task_id": datasets.Value("string"), |
| "bot_id": datasets.Value("string"), |
| "user_id": datasets.Value("string"), |
| "turns": Sequence(datasets.Value("string")), |
| } |
| ), |
| citation=_CITATION, |
| license=_LICENSE, |
| homepage=_HOMEPAGE, |
| ) |
|
|
| def _split_generators(self, dl_manager: datasets.DownloadManager): |
| dl_paths = dl_manager.download(_SPLITS) |
|
|
| return [ |
| datasets.SplitGenerator( |
| name=split_name, |
| |
| gen_kwargs={"data_path": split_path}, |
| ) |
| for split_name, split_path in dl_paths.items() |
| ] |
|
|
| def _generate_examples(self, data_path: str): |
| with zipfile.ZipFile(data_path) as zip_file: |
| for file in zip_file.namelist(): |
| with io.TextIOWrapper(zip_file.open(file), encoding="utf-8") as f: |
| for line in f: |
| line = json.loads(line) |
| yield line["id"], line |
|
|