Duplicate from li2017dailydialog/daily_dialog

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README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- found
+language:
+- en
+license:
+- cc-by-nc-sa-4.0
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- text-classification
+task_ids:
+- multi-label-classification
+paperswithcode_id: dailydialog
+pretty_name: DailyDialog
+tags:
+- emotion-classification
+- dialog-act-classification
+dataset_info:
+  features:
+  - name: dialog
+    sequence: string
+  - name: act
+    sequence:
+      class_label:
+        names:
+          '0': __dummy__
+          '1': inform
+          '2': question
+          '3': directive
+          '4': commissive
+  - name: emotion
+    sequence:
+      class_label:
+        names:
+          '0': no emotion
+          '1': anger
+          '2': disgust
+          '3': fear
+          '4': happiness
+          '5': sadness
+          '6': surprise
+  splits:
+  - name: train
+    num_bytes: 7296715
+    num_examples: 11118
+  - name: test
+    num_bytes: 655844
+    num_examples: 1000
+  - name: validation
+    num_bytes: 673943
+    num_examples: 1000
+  download_size: 4475921
+  dataset_size: 8626502
+---
+
+# Dataset Card for "daily_dialog"
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** [http://yanran.li/dailydialog](http://yanran.li/dailydialog)
+- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+- **Size of downloaded dataset files:** 4.48 MB
+- **Size of the generated dataset:** 8.63 MB
+- **Total amount of disk used:** 13.11 MB
+
+### Dataset Summary
+
+We develop a high-quality multi-turn dialog dataset, DailyDialog, which is intriguing in several aspects.
+The language is human-written and less noisy. The dialogues in the dataset reflect our daily communication way
+and cover various topics about our daily life. We also manually label the developed dataset with communication
+intention and emotion information. Then, we evaluate existing approaches on DailyDialog dataset and hope it
+benefit the research field of dialog systems.
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Languages
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+## Dataset Structure
+
+### Data Instances
+
+#### default
+
+- **Size of downloaded dataset files:** 4.48 MB
+- **Size of the generated dataset:** 8.63 MB
+- **Total amount of disk used:** 13.11 MB
+
+An example of 'validation' looks as follows.
+```
+This example was too long and was cropped:
+
+{
+    "act": [2, 1, 1, 1, 1, 2, 3, 2, 3, 4],
+    "dialog": "[\"Good afternoon . This is Michelle Li speaking , calling on behalf of IBA . Is Mr Meng available at all ? \", \" This is Mr Meng ...",
+    "emotion": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+}
+```
+
+### Data Fields
+
+The data fields are the same among all splits.
+
+#### default
+- `dialog`: a `list` of `string` features.
+- `act`: a `list` of classification labels, with possible values including `__dummy__` (0), `inform` (1), `question` (2), `directive` (3) and `commissive` (4).
+- `emotion`: a `list` of classification labels, with possible values including `no emotion` (0), `anger` (1), `disgust` (2), `fear` (3), `happiness` (4), `sadness` (5) and `surprise` (6).
+
+### Data Splits
+
+| name  |train|validation|test|
+|-------|----:|---------:|---:|
+|default|11118|      1000|1000|
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+#### Who are the source language producers?
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+#### Who are the annotators?
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Personal and Sensitive Information
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Discussion of Biases
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Other Known Limitations
+
+Dataset provided for research purposes only. Please check dataset license for additional information.
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Licensing Information
+
+DailyDialog dataset is licensed under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/).
+
+### Citation Information
+
+```
+@InProceedings{li2017dailydialog,
+    author = {Li, Yanran and Su, Hui and Shen, Xiaoyu and Li, Wenjie and Cao, Ziqiang and Niu, Shuzi},
+    title = {DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset},
+    booktitle = {Proceedings of The 8th International Joint Conference on Natural Language Processing (IJCNLP 2017)},
+    year = {2017}
+}
+
+```
+
+
+### Contributions
+
+Thanks to [@thomwolf](https://github.com/thomwolf), [@julien-c](https://github.com/julien-c) for adding this dataset.

daily_dialog.py

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+# coding=utf-8
+# Copyright 2020 The HuggingFace Datasets Authors
+#
+# 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.
+"""DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset"""
+
+
+import os
+from zipfile import ZipFile
+
+import datasets
+
+
+_CITATION = """\
+@InProceedings{li2017dailydialog,
+    author = {Li, Yanran and Su, Hui and Shen, Xiaoyu and Li, Wenjie and Cao, Ziqiang and Niu, Shuzi},
+    title = {DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset},
+    booktitle = {Proceedings of The 8th International Joint Conference on Natural Language Processing (IJCNLP 2017)},
+    year = {2017}
+}
+"""
+
+_DESCRIPTION = """\
+We develop a high-quality multi-turn dialog dataset, DailyDialog, which is intriguing in several aspects.
+The language is human-written and less noisy. The dialogues in the dataset reflect our daily communication way
+and cover various topics about our daily life. We also manually label the developed dataset with communication
+intention and emotion information. Then, we evaluate existing approaches on DailyDialog dataset and hope it
+benefit the research field of dialog systems.
+"""
+
+_URL = "http://yanran.li/files/ijcnlp_dailydialog.zip"
+
+act_label = {
+    "0": "__dummy__",  # Added to be compatible out-of-the-box with datasets.ClassLabel
+    "1": "inform",
+    "2": "question",
+    "3": "directive",
+    "4": "commissive",
+}
+
+emotion_label = {
+    "0": "no emotion",
+    "1": "anger",
+    "2": "disgust",
+    "3": "fear",
+    "4": "happiness",
+    "5": "sadness",
+    "6": "surprise",
+}
+
+
+class DailyDialog(datasets.GeneratorBasedBuilder):
+    """DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset"""
+
+    VERSION = datasets.Version("1.0.0")
+
+    __EOU__ = "__eou__"
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "dialog": datasets.features.Sequence(datasets.Value("string")),
+                    "act": datasets.features.Sequence(datasets.ClassLabel(names=list(act_label.values()))),
+                    "emotion": datasets.features.Sequence(datasets.ClassLabel(names=list(emotion_label.values()))),
+                }
+            ),
+            supervised_keys=None,
+            homepage="http://yanran.li/dailydialog",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager):
+        dl_dir = dl_manager.download_and_extract(_URL)
+        data_dir = os.path.join(dl_dir, "ijcnlp_dailydialog")
+        splits = [datasets.Split.TRAIN, datasets.Split.VALIDATION, datasets.Split.TEST]
+        return [
+            datasets.SplitGenerator(
+                name=split,
+                gen_kwargs={
+                    "data_zip": os.path.join(data_dir, f"{split}.zip"),
+                    "dialog_path": f"{split}/dialogues_{split}.txt",
+                    "act_path": f"{split}/dialogues_act_{split}.txt",
+                    "emotion_path": f"{split}/dialogues_emotion_{split}.txt",
+                },
+            )
+            for split in splits
+        ]
+
+    def _generate_examples(self, data_zip, dialog_path, act_path, emotion_path):
+        with open(data_zip, "rb") as data_file:
+            with ZipFile(data_file) as zip_file:
+                with zip_file.open(dialog_path) as dialog_file, zip_file.open(act_path) as act_file, zip_file.open(
+                    emotion_path
+                ) as emotion_file:
+                    for idx, (dialog_line, act_line, emotion_line) in enumerate(
+                        zip(dialog_file, act_file, emotion_file)
+                    ):
+                        if not dialog_line.strip():
+                            break
+                        dialog = dialog_line.decode().split(self.__EOU__)[:-1]
+                        act = act_line.decode().split(" ")[:-1]
+                        emotion = emotion_line.decode().split(" ")[:-1]
+                        assert (
+                            len(dialog) == len(act) == len(emotion)
+                        ), "Different turns btw dialogue & emotion & action"
+                        yield idx, {
+                            "dialog": dialog,
+                            "act": [act_label[x] for x in act],
+                            "emotion": [emotion_label[x] for x in emotion],
+                        }