Update files from the datasets library (from 1.0.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.0.0

.gitattributes

@@ -0,0 +1,27 @@
+*.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

ai2_arc.py

@@ -0,0 +1,133 @@
+"""TODO(arc): Add a description here."""
+
+from __future__ import absolute_import, division, print_function
+
+import json
+import os
+
+import datasets
+
+
+# TODO(ai2_arc): BibTeX citation
+_CITATION = """\
+@article{allenai:arc,
+      author    = {Peter Clark  and Isaac Cowhey and Oren Etzioni and Tushar Khot and
+                    Ashish Sabharwal and Carissa Schoenick and Oyvind Tafjord},
+      title     = {Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge},
+      journal   = {arXiv:1803.05457v1},
+      year      = {2018},
+}
+"""
+
+# TODO(ai2_arc):
+_DESCRIPTION = """\
+A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in
+ advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains
+ only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurrence algorithm. We are also
+ including a corpus of over 14 million science sentences relevant to the task, and an implementation of three neural baseline models for this dataset. We pose ARC as a challenge to the community.
+"""
+
+_URL = "https://s3-us-west-2.amazonaws.com/ai2-website/data/ARC-V1-Feb2018.zip"
+
+
+class Ai2ArcConfig(datasets.BuilderConfig):
+    """BuilderConfig for Ai2ARC."""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for Ai2Arc.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(Ai2ArcConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
+
+
+class Ai2Arc(datasets.GeneratorBasedBuilder):
+    """TODO(arc): Short description of my dataset."""
+
+    # TODO(arc): Set up version.
+    VERSION = datasets.Version("1.0.0")
+    BUILDER_CONFIGS = [
+        Ai2ArcConfig(
+            name="ARC-Challenge",
+            description="""\
+          Challenge Set of 2590 “hard” questions (those that both a retrieval and a co-occurrence method fail to answer correctly)
+          """,
+        ),
+        Ai2ArcConfig(
+            name="ARC-Easy",
+            description="""\
+          Easy Set of 5197 questions
+          """,
+        ),
+    ]
+
+    def _info(self):
+        # TODO(ai2_arc): Specifies the datasets.DatasetInfo object
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # datasets.features.FeatureConnectors
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "question": datasets.Value("string"),
+                    "choices": datasets.features.Sequence(
+                        {"text": datasets.Value("string"), "label": datasets.Value("string")}
+                    ),
+                    "answerKey": datasets.Value("string")
+                    # These are the features of your dataset like images, labels ...
+                }
+            ),
+            # If there's a common (input, target) tuple from the features,
+            # specify them here. They'll be used if as_supervised=True in
+            # builder.as_dataset.
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage="https://allenai.org/data/arc",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # TODO(ai2_arc): Downloads the data and defines the splits
+        # dl_manager is a datasets.download.DownloadManager that can be used to
+        # download and extract URLs
+        dl_dir = dl_manager.download_and_extract(_URL)
+        data_dir = os.path.join(dl_dir, "ARC-V1-Feb2018-2")
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": os.path.join(data_dir, self.config.name, self.config.name + "-Train.jsonl")},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": os.path.join(data_dir, self.config.name, self.config.name + "-Test.jsonl")},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": os.path.join(data_dir, self.config.name, self.config.name + "-Dev.jsonl")},
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        # TODO(ai2_arc): Yields (key, example) tuples from the dataset
+        with open(filepath, encoding="utf-8") as f:
+            for row in f:
+                data = json.loads(row)
+                answerkey = data["answerKey"]
+                id_ = data["id"]
+                question = data["question"]["stem"]
+                choices = data["question"]["choices"]
+                text_choices = [choice["text"] for choice in choices]
+                label_choices = [choice["label"] for choice in choices]
+                yield id_, {
+                    "id": id_,
+                    "answerKey": answerkey,
+                    "question": question,
+                    "choices": {"text": text_choices, "label": label_choices},
+                }

dataset_infos.json

@@ -0,0 +1 @@
+{"ARC-Challenge": {"description": "A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in\n advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains\n only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurrence algorithm. We are also\n including a corpus of over 14 million science sentences relevant to the task, and an implementation of three neural baseline models for this dataset. We pose ARC as a challenge to the community.\n", "citation": "@article{allenai:arc,\n      author    = {Peter Clark  and Isaac Cowhey and Oren Etzioni and Tushar Khot and\n                    Ashish Sabharwal and Carissa Schoenick and Oyvind Tafjord},\n      title     = {Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge},\n      journal   = {arXiv:1803.05457v1},\n      year      = {2018},\n}\n", "homepage": "https://allenai.org/data/arc", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "choices": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "answerKey": {"dtype": "string", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "ai2_arc", "config_name": "ARC-Challenge", "version": {"version_str": "1.0.0", "description": "", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 377740, "num_examples": 1172, "dataset_name": "ai2_arc"}, "train": {"name": "train", "num_bytes": 351888, "num_examples": 1119, "dataset_name": "ai2_arc"}, "validation": {"name": "validation", "num_bytes": 97254, "num_examples": 299, "dataset_name": "ai2_arc"}}, "download_checksums": {"https://s3-us-west-2.amazonaws.com/ai2-website/data/ARC-V1-Feb2018.zip": {"num_bytes": 680841265, "checksum": "6d2d5ab50b2ceec6ba5f79c921be77cf2de712ea25a2b3f4fff3acc101cecfa0"}}, "download_size": 680841265, "dataset_size": 826882, "size_in_bytes": 681668147}, "ARC-Easy": {"description": "A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in\n advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains\n only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurrence algorithm. We are also\n including a corpus of over 14 million science sentences relevant to the task, and an implementation of three neural baseline models for this dataset. We pose ARC as a challenge to the community.\n", "citation": "@article{allenai:arc,\n      author    = {Peter Clark  and Isaac Cowhey and Oren Etzioni and Tushar Khot and\n                    Ashish Sabharwal and Carissa Schoenick and Oyvind Tafjord},\n      title     = {Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge},\n      journal   = {arXiv:1803.05457v1},\n      year      = {2018},\n}\n", "homepage": "https://allenai.org/data/arc", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "choices": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "answerKey": {"dtype": "string", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "ai2_arc", "config_name": "ARC-Easy", "version": {"version_str": "1.0.0", "description": "", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 661997, "num_examples": 2376, "dataset_name": "ai2_arc"}, "train": {"name": "train", "num_bytes": 623254, "num_examples": 2251, "dataset_name": "ai2_arc"}, "validation": {"name": "validation", "num_bytes": 158498, "num_examples": 570, "dataset_name": "ai2_arc"}}, "download_checksums": {"https://s3-us-west-2.amazonaws.com/ai2-website/data/ARC-V1-Feb2018.zip": {"num_bytes": 680841265, "checksum": "6d2d5ab50b2ceec6ba5f79c921be77cf2de712ea25a2b3f4fff3acc101cecfa0"}}, "download_size": 680841265, "dataset_size": 1443749, "size_in_bytes": 682285014}}

dummy/ARC-Challenge/1.0.0/dummy_data.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:14cb5c6345df3095df22c78f301589322ddcef0d022dbe7b3685000cde442e33
+size 3030

dummy/ARC-Easy/1.0.0/dummy_data.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:85600e425a311a70c8331bc6eba15b70e5e40bd03f9b76f935e42e27709f3db3
+size 2960