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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+*.arrow filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- crowdsourced
+language_creators:
+- expert-generated
+languages:
+- en
+licenses:
+- cc-by-sa-3-0
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- question-answering
+task_ids:
+- extractive-qa
+- question-answering-other-multi-hop
+---
+
+# 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:** [QAngaroo](http://qangaroo.cs.ucl.ac.uk/)
+- **Repository:** [If the dataset is hosted on github or has a github homepage, add URL here]()
+- **Paper:** [Constructing Datasets for Multi-hop Reading Comprehension Across Documents](https://arxiv.org/abs/1710.06481)
+- **Leaderboard:** [leaderboard](http://qangaroo.cs.ucl.ac.uk/leaderboard.html)
+- **Point of Contact:** [Johannes Welbl](j.welbl@cs.ucl.ac.uk)
+
+### 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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+{"original": {"description": "MedHop is based on research paper abstracts from PubMed, and the queries are about interactions between pairs of drugs. The correct answer has to be inferred by combining information from a chain of reactions of drugs and proteins.\n", "citation": "@misc{welbl2018constructing,\n      title={Constructing Datasets for Multi-hop Reading Comprehension Across Documents},\n      author={Johannes Welbl and Pontus Stenetorp and Sebastian Riedel},\n      year={2018},\n      eprint={1710.06481},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL}\n}\n", "homepage": "http://qangaroo.cs.ucl.ac.uk/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "query": {"dtype": "string", "id": null, "_type": "Value"}, "answer": {"dtype": "string", "id": null, "_type": "Value"}, "candidates": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "supports": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "med_hop", "config_name": "original", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 93937322, "num_examples": 1620, "dataset_name": "med_hop"}, "validation": {"name": "validation", "num_bytes": 16461640, "num_examples": 342, "dataset_name": "med_hop"}}, "download_checksums": {"https://drive.google.com/uc?export=download&id=1ytVZ4AhubFDOEL7o7XrIRIyhU8g9wvKA": {"num_bytes": 339843061, "checksum": "2f512869760cdad76a022a1465f025b486ae79dc5b8f0bf3ad901a4caf2d3050"}}, "download_size": 339843061, "post_processing_size": null, "dataset_size": 110398962, "size_in_bytes": 450242023}, "masked": {"description": "MedHop iss based on research paper abstracts from PubMed, and the queries are about interactions between pairs of drugs. The correct answer has to be inferred by combining information from a chain of reactions of drugs and proteins.\n", "citation": "@misc{welbl2018constructing,\n      title={Constructing Datasets for Multi-hop Reading Comprehension Across Documents},\n      author={Johannes Welbl and Pontus Stenetorp and Sebastian Riedel},\n      year={2018},\n      eprint={1710.06481},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL}\n}\n", "homepage": "http://qangaroo.cs.ucl.ac.uk/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "answer": {"dtype": "string", "id": null, "_type": "Value"}, "candidates": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "supports": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "med_hop", "config_name": "masked", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 95813584, "num_examples": 1620, "dataset_name": "med_hop"}, "validation": {"name": "validation", "num_bytes": 16800570, "num_examples": 342, "dataset_name": "med_hop"}}, "download_checksums": {"https://drive.google.com/uc?export=download&id=1ytVZ4AhubFDOEL7o7XrIRIyhU8g9wvKA": {"num_bytes": 339843061, "checksum": "2f512869760cdad76a022a1465f025b486ae79dc5b8f0bf3ad901a4caf2d3050"}}, "download_size": 339843061, "post_processing_size": null, "dataset_size": 112614154, "size_in_bytes": 452457215}}

dummy/masked/1.0.0/dummy_data.zip

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dummy/original/1.0.0/dummy_data.zip

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med_hop.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.
+"""MedHop: Reading Comprehension with Multiple Hops"""
+
+from __future__ import absolute_import, division, print_function
+
+import json
+import os
+
+import datasets
+
+
+_CITATION = """\
+@misc{welbl2018constructing,
+      title={Constructing Datasets for Multi-hop Reading Comprehension Across Documents},
+      author={Johannes Welbl and Pontus Stenetorp and Sebastian Riedel},
+      year={2018},
+      eprint={1710.06481},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+MedHop is based on research paper abstracts from PubMed, and the queries are about interactions between pairs of drugs. \
+The correct answer has to be inferred by combining information from a chain of reactions of drugs and proteins.
+"""
+
+_URL = "https://drive.google.com/uc?export=download&id=1ytVZ4AhubFDOEL7o7XrIRIyhU8g9wvKA"
+
+
+class MedHopConfig(datasets.BuilderConfig):
+    """BuilderConfig for MedHop."""
+
+    def __init__(self, masked=False, **kwargs):
+        """BuilderConfig for MedHop.
+
+        Args:
+          masked: `bool`, original or maksed data.
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(MedHopConfig, self).__init__(**kwargs)
+        self.masked = masked
+
+
+class MedHop(datasets.GeneratorBasedBuilder):
+    """MedHop: Reading Comprehension with Multiple Hops"""
+
+    VERSION = datasets.Version("1.0.0")
+    BUILDER_CONFIGS = [
+        MedHopConfig(
+            name="original",
+            version=datasets.Version("1.0.0"),
+            description="The un-maksed MedHop dataset",
+            masked=False,
+        ),
+        MedHopConfig(
+            name="masked", version=datasets.Version("1.0.0"), description="Masked MedHop dataset", masked=True
+        ),
+    ]
+    BUILDER_CONFIG_CLASS = MedHopConfig
+    DEFAULT_CONFIG_NAME = "original"
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "question": datasets.Value("string"),
+                    "answer": datasets.Value("string"),
+                    "candidates": datasets.Sequence(datasets.Value("string")),
+                    "supports": datasets.Sequence(datasets.Value("string")),
+                }
+            ),
+            supervised_keys=None,
+            homepage="http://qangaroo.cs.ucl.ac.uk/",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        extracted_path = dl_manager.download_and_extract(_URL)
+
+        medhop_path = os.path.join(extracted_path, "qangaroo_v1.1", "medhop")
+        train_file = "train.json" if self.config.name == "original" else "train.masked.json"
+        dev_file = "dev.json" if self.config.name == "original" else "dev.masked.json"
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": os.path.join(medhop_path, train_file)},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": os.path.join(medhop_path, dev_file)},
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            examples = json.load(f)
+            for i, example in enumerate(examples):
+                example["question"] = example.pop("query")
+                yield example["id"], example