Upload super_dialseg.py

super_dialseg.py

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