update mix data and script

OpenSLU.py

@@ -0,0 +1,183 @@
+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.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]

atis.tar.gz

@@ -1,3 +1,3 @@
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-size 129044
+oid sha256:80063f7b2046a7e80ed06e5870a08e7e9d22c224aaaa69ee14114b254bab00bc
+size 134507

atis.tar → mix_atis.tar.gz

@@ -1,3 +1,3 @@
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-size 1216512
+oid sha256:398dbda06def10deca858aabbb557c5b7ab11f710d89ac74105e467a852c8a43
+size 602622

snips.tar → mix_snips.tar.gz

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-size 2461696
+oid sha256:48933496e422a498f03969fbdf8899efdbf047d3c29bb97af430478d2a8903f8
+size 2476548

snips.tar.gz

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-size 378851
+oid sha256:7fd1f889cb516df34d1200f2db7e644c5e218b9239eb74fd5a2073a94ac4cf0b
+size 395478