Create mutual_harness.py

mutual_harness.py

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+# 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.
+"""MuTual dataset."""
+
+
+import json
+import os
+from pathlib import Path
+
+import datasets
+
+
+_CITATION = """\
+@inproceedings{mutual,
+    title = "MuTual: A Dataset for Multi-Turn Dialogue Reasoning",
+    author = "Cui, Leyang  and Wu, Yu and Liu, Shujie and Zhang, Yue and Zhou, Ming" ,
+    booktitle = "Proceedings of the 58th Conference of the Association for Computational Linguistics",
+    year = "2020",
+    publisher = "Association for Computational Linguistics",
+}
+"""
+
+_DESCRIPTION = """\
+MuTual is a retrieval-based dataset for multi-turn dialogue reasoning, which is
+modified from Chinese high school English listening comprehension test data.
+"""
+
+_HOMEPAGE = "https://github.com/Nealcly/MuTual"
+
+# TODO: Add the licence for the dataset here if you can find it
+_LICENSE = ""
+
+_URLS = "https://github.com/Nealcly/MuTual/archive/master.zip"
+
+
+class Mutual(datasets.GeneratorBasedBuilder):
+    """MuTual: A Dataset for Multi-Turn Dialogue Reasoning"""
+
+    VERSION = datasets.Version("0.0.1")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="mutual", version=VERSION, description="The MuTual dataset."
+        ),
+        datasets.BuilderConfig(
+            name="mutual_plus",
+            version=VERSION,
+            description="MuTualPlus is a more difficult MuTual that replaces positive responses with a safe responses.",
+        ),
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "answers": datasets.Value("string"),
+                "options": datasets.features.Sequence(datasets.Value("string")),
+                "article": datasets.Value("string"),
+                "id": datasets.Value("string"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=f"{_DESCRIPTION}\n{self.config.description}",
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls = _URLS
+        data_dir = dl_manager.download_and_extract(urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "basepath": os.path.join(
+                        data_dir, "MuTual-master", "data", self.config.name, "train"
+                    ),
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "basepath": os.path.join(
+                        data_dir, "MuTual-master", "data", self.config.name, "test"
+                    ),
+                    "split": "test",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "basepath": os.path.join(
+                        data_dir, "MuTual-master", "data", self.config.name, "dev"
+                    ),
+                    "split": "dev",
+                },
+            ),
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, basepath, split):
+        # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
+        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
+        key = 0
+        for file in sorted(Path(basepath).iterdir()):
+            if file.suffix != ".txt":
+                continue
+            with open(file, "r", encoding="utf-8") as f:
+                data_str = f.read()
+                # Ignore the occasional empty file.
+                if not data_str:
+                    continue
+                data = json.loads(data_str)
+                yield key, {
+                    "answers": data["answers"],
+                    "options": data["options"],
+                    "article": data["article"],
+                    "id": data["id"],
+                }
+                key += 1