Update parquet files

OpenSLU.py

@@ -1,183 +0,0 @@
-import json
-import os
-
-import datasets
-
-_OPEN_SLU_CITATION = """\
-xxx"""
-
-_OPEN_SLU_DESCRIPTION = """\
-xxx"""
-
-_ATIS_DESCRIPTION = """\
-@article{wang2019superglue,
-  title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
-  author={Wang, Alex and Pruksachatkun, Yada and Nangia, Nikita and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R},
-  journal={arXiv preprint arXiv:1905.00537},
-  year={2019}
-}
-Note that each SuperGLUE dataset has its own citation. Please see the source to
-get the correct citation for each contained dataset.
-"""
-
-_BOOLQ_CITATION = """\
-@inproceedings{clark2019boolq,
-  title={BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions},
-  author={Clark, Christopher and Lee, Kenton and Chang, Ming-Wei, and Kwiatkowski, Tom and Collins, Michael, and Toutanova, Kristina},
-  booktitle={NAACL},
-  year={2019}
-}"""
-
-
-class OpenSLUConfig(datasets.BuilderConfig):
-    """BuilderConfig for OpenSLU."""
-
-    def __init__(self, features, data_url, citation, url, intent_label_classes=None, slot_label_classes=None, **kwargs):
-        """BuilderConfig for OpenSLU.
-        Args:
-          features: `list[string]`, list of the features that will appear in the
-            feature dict. Should not include "label".
-          data_url: `string`, url to download the zip file from.
-          citation: `string`, citation for the data set.
-          url: `string`, url for information about the data set.
-          intent_label_classes: `list[string]`, the list of classes for the intent label
-          slot_label_classes: `list[string]`, the list of classes for the slot label
-          **kwargs: keyword arguments forwarded to super.
-        """
-        # Version history:
-        # 0.0.1: Initial version.
-        super(OpenSLUConfig, self).__init__(version=datasets.Version("0.0.1"), **kwargs)
-        self.features = features
-        self.intent_label_classes = intent_label_classes
-        self.slot_label_classes = slot_label_classes
-        self.data_url = data_url
-        self.citation = citation
-        self.url = url
-
-
-class OpenSLU(datasets.GeneratorBasedBuilder):
-    """The SuperGLUE benchmark."""
-
-    BUILDER_CONFIGS = [
-        OpenSLUConfig(
-            name="atis",
-            description=_ATIS_DESCRIPTION,
-            features=["text"],
-            data_url="https://huggingface.co/datasets/LightChen2333/OpenSLU/resolve/main/atis.tar.gz",
-            citation="",
-            url="",
-        ),
-        OpenSLUConfig(
-            name="snips",
-            description=_ATIS_DESCRIPTION,
-            features=["text"],
-            data_url="https://huggingface.co/datasets/LightChen2333/OpenSLU/resolve/main/snips.tar.gz",
-            citation="",
-            url="",
-        ),
-        OpenSLUConfig(
-            name="mix-atis",
-            description=_ATIS_DESCRIPTION,
-            features=["text"],
-            data_url="https://huggingface.co/datasets/LightChen2333/OpenSLU/resolve/main/mix-atis.tar.gz",
-            citation="",
-            url="",
-        ),
-        OpenSLUConfig(
-            name="mix-snips",
-            description=_ATIS_DESCRIPTION,
-            features=["text"],
-            data_url="https://huggingface.co/datasets/LightChen2333/OpenSLU/resolve/main/mix-snips.tar.gz",
-            citation="",
-            url="",
-        ),
-    ]
-
-    def _info(self):
-        features = {feature: datasets.Sequence(datasets.Value("string")) for feature in self.config.features}
-        features["slot"] = datasets.Sequence(datasets.Value("string"))
-        features["intent"] = datasets.Value("string")
-
-        return datasets.DatasetInfo(
-            description=_OPEN_SLU_DESCRIPTION + self.config.description,
-            features=datasets.Features(features),
-            homepage=self.config.url,
-            citation=self.config.citation + "\n" + _OPEN_SLU_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        print(self.config.data_url)
-        dl_dir = dl_manager.download_and_extract(self.config.data_url) or ""
-
-        task_name = _get_task_name_from_data_url(self.config.data_url)
-        print(dl_dir)
-        print(task_name)
-        dl_dir = os.path.join(dl_dir, task_name)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "data_file": os.path.join(dl_dir, "train.jsonl"),
-                    "split": datasets.Split.TRAIN,
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "data_file": os.path.join(dl_dir, "dev.jsonl"),
-                    "split": datasets.Split.VALIDATION,
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "data_file": os.path.join(dl_dir, "test.jsonl"),
-                    "split": datasets.Split.TEST,
-                },
-            ),
-        ]
-
-    def _generate_examples(self, data_file, split):
-        with open(data_file, encoding="utf-8") as f:
-            for index, line in enumerate(f):
-                row = json.loads(line)
-                yield index, row
-
-
-def _cast_label(label):
-    """Converts the label into the appropriate string version."""
-    if isinstance(label, str):
-        return label
-    elif isinstance(label, bool):
-        return "True" if label else "False"
-    elif isinstance(label, int):
-        assert label in (0, 1)
-        return str(label)
-    else:
-        raise ValueError("Invalid label format.")
-
-
-def _get_record_entities(passage):
-    """Returns the unique set of entities."""
-    text = passage["text"]
-    entity_spans = list()
-    for entity in passage["entities"]:
-        entity_text = text[entity["start"]: entity["end"] + 1]
-        entity_spans.append({"text": entity_text, "start": entity["start"], "end": entity["end"] + 1})
-    entity_spans = sorted(entity_spans, key=lambda e: e["start"])  # sort by start index
-    entity_texts = set(e["text"] for e in entity_spans)  # for backward compatability
-    return entity_texts, entity_spans
-
-
-def _get_record_answers(qa):
-    """Returns the unique set of answers."""
-    if "answers" not in qa:
-        return []
-    answers = set()
-    for answer in qa["answers"]:
-        answers.add(answer["text"])
-    return sorted(answers)
-
-
-def _get_task_name_from_data_url(data_url):
-    return data_url.split("/")[-1].split(".")[0]

README.md

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----
-license: mit
----

snips.tar.gz → atis/open_slu-test.parquet

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