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+ # coding=utf-8
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+ # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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+ #
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+ # Licensed under the Apache License, Version 2.0 (the "License");
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+ # you may not use this file except in compliance with the License.
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+ # You may obtain a copy of the License at
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+ #
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+ # http://www.apache.org/licenses/LICENSE-2.0
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+ #
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+ # Unless required by applicable law or agreed to in writing, software
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+ # distributed under the License is distributed on an "AS IS" BASIS,
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+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+ # See the License for the specific language governing permissions and
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+ # limitations under the License.
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+ """SuperDialseg: A Large-scale Dataset for Supervised Dialogue Segmentation"""
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+
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+
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+ import json
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+
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+ import datasets
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+
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+
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+ _CITATION = """\
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+ """
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+
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+ _DESCRIPTION = """\
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+ """
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+
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+
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+ _HOMEPAGE = "https://github.com/Coldog2333/SuperDialseg"
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+
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+ _LICENSE = """\
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+ """
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+ # TODO: Add link to the official dataset URLs here
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+ # The HuggingFace dataset library don't host the datasets but only point to the original files
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+ # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
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+ _URLs = {
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+ "train": "https://huggingface.co/datasets/Coldog2333/super_dialseg/resolve/main/train.json",
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+ "validation": "https://huggingface.co/datasets/Coldog2333/super_dialseg/resolve/main/validation.json",
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+ "test": "https://huggingface.co/datasets/Coldog2333/super_dialseg/resolve/main/test.json",
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+ }
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+
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+
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+ class SuperDialsegConfig(datasets.BuilderConfig):
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+ """BuilderConfig for SuperDialseg"""
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+
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+ def __init__(self, **kwargs):
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+ """
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+ Args:
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+ **kwargs: keyword arguments forwarded to super.
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+ """
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+ super().__init__(version=datasets.Version("1.0.0", ""), **kwargs)
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+ self.dataset_name = "super_dialseg"
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+
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+
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+ class SuperDialseg(datasets.GeneratorBasedBuilder):
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+ """SuperDialseg: A Large-scale Dataset for Supervised Dialogue Segmentation"""
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+
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+ VERSION = datasets.Version("1.0.0")
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+
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+ def _info(self):
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+ return datasets.DatasetInfo(
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+ description=_DESCRIPTION,
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+ features=datasets.Features(
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+ {
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+ "dial_id": datasets.Value("string"),
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+ "turns": datasets.features.Sequence(
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+ {
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+ "da": datasets.Value("string"),
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+ "role": datasets.Value("string"),
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+ "turn_id": datasets.Value("int32"),
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+ "utterance": datasets.Value("string"),
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+ "topic_id": datasets.Value("int32"),
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+ "segmentation_label": datasets.Value("int32"),
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+ }
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+ )
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+ }
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+ ),
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+ supervised_keys=None,
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+ homepage=_HOMEPAGE,
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+ license=_LICENSE,
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+ citation=_CITATION,
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ """Returns SplitGenerators."""
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+ downloaded_files = dl_manager.download_and_extract(_URLs)
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+ return [
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}
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+ ),
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+ datasets.SplitGenerator(
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+ name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["validation"]}
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+ ),
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}
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+ )
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+ ]
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+
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+ def _generate_examples(self, filepath):
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+ """Yields examples."""
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+ with open(filepath, encoding="utf-8") as f:
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+ data = json.load(f)["dial_data"][self.dataset_name]
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+ for id_, row in enumerate(data):
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+ yield id_, {
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+ "dial_id": row["dial_id"],
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+ "turns": row["turns"],
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+ }