Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+annotations_creators:
+- crowdsourced
+language_creators:
+- crowdsourced
+languages:
+  en:
+  - en
+  de:
+  - de
+  it:
+  - it
+  de_en:
+  - en
+  - de
+  it_en:
+  - en
+  - it
+licenses:
+- unknown
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- sequence-modeling
+- structure-prediction
+- text-classification
+task_ids:
+- dialogue-modeling
+- multi-class-classification
+- parsing
+---
+
+# Dataset Card Creation Guide
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [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)
+
+## Dataset Description
+
+- **Homepage:** [More info needed]
+- **Repository:** [GitHub](https://github.com/nmrksic/neural-belief-tracker/tree/master/data/woz)
+- **Paper:** [A Network-based End-to-End Trainable Task-oriented Dialogue System](https://arxiv.org/abs/1604.04562)
+- **Leaderboard:** [More info needed]
+- **Point of Contact:** [More info needed]
+
+### Dataset Summary
+
+[More Information Needed]
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+[More Information Needed]
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+[More Information Needed]
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+[More Information Needed]
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+[More Information Needed]
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]

dataset_infos.json

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woz_dialogue.py

@@ -0,0 +1,135 @@
+# 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.
+"""WozDialogue: a dataset for training task-oriented dialogue systems"""
+
+from __future__ import absolute_import, division, print_function
+
+import json
+
+import datasets
+
+
+_CITATION = """\
+@misc{wen2017networkbased,
+      title={A Network-based End-to-End Trainable Task-oriented Dialogue System},
+      author={Tsung-Hsien Wen and David Vandyke and Nikola Mrksic and Milica Gasic and Lina M. Rojas-Barahona and Pei-Hao Su and Stefan Ultes and Steve Young},
+      year={2017},
+      eprint={1604.04562},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+Wizard-of-Oz (WOZ) is a dataset for training task-oriented dialogue systems. The dataset is designed around the \
+task of finding a restaurant in the Cambridge, UK area. There are three informable slots (food, pricerange,area) \
+that users can use to constrain the search and six requestable slots (address, phone, postcode plus the three informable slots) \
+that the user can ask a value for once a restaurant has been offered.
+"""
+
+_HOMEPAGE = "https://github.com/nmrksic/neural-belief-tracker/tree/master/data/woz"
+
+_BASE_URL = "https://raw.githubusercontent.com/nmrksic/neural-belief-tracker/master/data/woz"
+
+
+class WozDialogue(datasets.GeneratorBasedBuilder):
+    """WozDialogue: a dataset for training task-oriented dialogue systems"""
+
+    VERSION = datasets.Version("1.0.0")
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="en",
+            version=datasets.Version("1.0.0"),
+            description="WOZ English dataset",
+        ),
+        datasets.BuilderConfig(name="de", version=datasets.Version("1.0.0"), description="WOZ German dataset"),
+        datasets.BuilderConfig(
+            name="de_en",
+            version=datasets.Version("1.0.0"),
+            description="WOZ German-English dataset. For this config, the dialogues are in German and the labels in English ",
+        ),
+        datasets.BuilderConfig(name="it", version=datasets.Version("1.0.0"), description="WOZ Italian dataset"),
+        datasets.BuilderConfig(
+            name="it_en",
+            version=datasets.Version("1.0.0"),
+            description="WOZ Italian-English dataset. For this config, the dialogues are in Italian and the labels in English ",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "dialogue_idx": datasets.Value("int32"),
+                    "dialogue": [
+                        {
+                            "turn_label": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
+                            "asr": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
+                            "system_transcript": datasets.Value("string"),
+                            "turn_idx": datasets.Value("int32"),
+                            "belief_state": [
+                                {
+                                    "slots": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
+                                    "act": datasets.Value("string"),
+                                }
+                            ],
+                            "transcript": datasets.Value("string"),
+                            "system_acts": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
+                        }
+                    ],
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls = {
+            "train": f"{_BASE_URL}/woz_train_{self.config.name}.json",
+            "dev": f"{_BASE_URL}/woz_validate_{self.config.name}.json",
+            "test": f"{_BASE_URL}/woz_test_{self.config.name}.json",
+        }
+        downloaded_paths = dl_manager.download(urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": downloaded_paths["train"]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": downloaded_paths["dev"]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": downloaded_paths["test"]},
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            examples = json.load(f)
+            for i, example in enumerate(examples):
+                for dialogue in example["dialogue"]:
+                    # exclude the second element which is same for every instance and is of type int
+                    dialogue["asr"] = [asr[:1] for asr in dialogue["asr"]]
+                    # some system_acts is either to string or list of strings,
+                    # converting all to list of strings
+                    dialogue["system_acts"] = [
+                        [act] if isinstance(act, str) else act for act in dialogue["system_acts"]
+                    ]
+
+                yield example["dialogue_idx"], example