Convert dataset to Parquet (#2)

- Convert dataset to Parquet (81f0ec71ff02b9761cccb52b804b8cfe7013695a)
- Delete loading script (239fef93adf27bcc55dd1057efd77441ab640c12)
- Delete legacy dataset_infos.json (7e8df1277151ceb787c650e4f4ab16c436d19059)

README.md

@@ -1,5 +1,4 @@
 ---
-pretty_name: ROPES
 annotations_creators:
 - crowdsourced
 language_creators:
@@ -21,7 +20,9 @@ task_categories:
 task_ids:
 - extractive-qa
 paperswithcode_id: ropes
+pretty_name: ROPES
 dataset_info:
+  config_name: plain_text
   features:
   - name: id
     dtype: string
@@ -35,19 +36,28 @@ dataset_info:
     sequence:
     - name: text
       dtype: string
-  config_name: plain_text
   splits:
   - name: train
-    num_bytes: 12231940
+    num_bytes: 12231892
     num_examples: 10924
   - name: test
-    num_bytes: 1928532
+    num_bytes: 1928508
     num_examples: 1710
   - name: validation
-    num_bytes: 1643498
+    num_bytes: 1643474
     num_examples: 1688
-  download_size: 3516917
-  dataset_size: 15803970
+  download_size: 1372548
+  dataset_size: 15803874
+configs:
+- config_name: plain_text
+  data_files:
+  - split: train
+    path: plain_text/train-*
+  - split: test
+    path: plain_text/test-*
+  - split: validation
+    path: plain_text/validation-*
+  default: true
 ---
 
 # Dataset Card for ROPES

dataset_infos.json

@@ -1 +0,0 @@
-{"plain_text": {"description": "ROPES (Reasoning Over Paragraph Effects in Situations) is a QA dataset\nwhich tests a system's ability to apply knowledge from a passage\nof text to a new situation. A system is presented a background\npassage containing a causal or qualitative relation(s) (e.g.,\n\"animal pollinators increase efficiency of fertilization in flowers\"),\na novel situation that uses this background, and questions that require\nreasoning about effects of the relationships in the background\npassage in the background of the situation.\n", "citation": "@inproceedings{Lin2019ReasoningOP,\n  title={Reasoning Over Paragraph Effects in Situations},\n  author={Kevin Lin and Oyvind Tafjord and Peter Clark and Matt Gardner},\n  booktitle={MRQA@EMNLP},\n  year={2019}\n}\n", "homepage": "https://allenai.org/data/ropes", "license": "CC BY 4.0", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "background": {"dtype": "string", "id": null, "_type": "Value"}, "situation": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "ropes", "config_name": "plain_text", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 12231940, "num_examples": 10924, "dataset_name": "ropes"}, "test": {"name": "test", "num_bytes": 1928532, "num_examples": 1710, "dataset_name": "ropes"}, "validation": {"name": "validation", "num_bytes": 1643498, "num_examples": 1688, "dataset_name": "ropes"}}, "download_checksums": {"https://ropes-dataset.s3-us-west-2.amazonaws.com/train_and_dev/ropes-train-dev-v1.0.tar.gz": {"num_bytes": 3395072, "checksum": "ba26329832f84d8c2660de1120a1d7ff086cdf8580eabeebd721c092020763e2"}, "https://ropes-dataset.s3-us-west-2.amazonaws.com/test/ropes-test-questions-v1.0.tar.gz": {"num_bytes": 121845, "checksum": "a489b9d0c0f2bcf495f6eab089ba4915e7832dc656237b40497acdccb8a45f95"}}, "download_size": 3516917, "post_processing_size": null, "dataset_size": 15803970, "size_in_bytes": 19320887}}

plain_text/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:95b2ae3c1403b56a8e6a9250ccf7b0667b4c1b82b68694050654b142f5e868a6
+size 199757

plain_text/train-00000-of-00001.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5dd4781f69556326f366989e1e5df6603b43269388d5c2e22e0a7229c08df687
+size 1063606

plain_text/validation-00000-of-00001.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5ad558e4089cbc1c0014fcd72f2bdfa3271d0a2ab04d19823ebba927323b6e26
+size 109185

ropes.py

@@ -1,138 +0,0 @@
-# coding=utf-8
-# 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.
-"""ROPES dataset.
-Code is heavily inspired from https://github.com/huggingface/datasets/blob/master/datasets/squad/squad.py"""
-
-
-import json
-
-import datasets
-
-
-_CITATION = """\
-@inproceedings{Lin2019ReasoningOP,
-  title={Reasoning Over Paragraph Effects in Situations},
-  author={Kevin Lin and Oyvind Tafjord and Peter Clark and Matt Gardner},
-  booktitle={MRQA@EMNLP},
-  year={2019}
-}
-"""
-
-_DESCRIPTION = """\
-ROPES (Reasoning Over Paragraph Effects in Situations) is a QA dataset
-which tests a system's ability to apply knowledge from a passage
-of text to a new situation. A system is presented a background
-passage containing a causal or qualitative relation(s) (e.g.,
-"animal pollinators increase efficiency of fertilization in flowers"),
-a novel situation that uses this background, and questions that require
-reasoning about effects of the relationships in the background
-passage in the background of the situation.
-"""
-
-_LICENSE = "CC BY 4.0"
-
-_URLs = {
-    "train+dev": "https://ropes-dataset.s3-us-west-2.amazonaws.com/train_and_dev/ropes-train-dev-v1.0.tar.gz",
-    "test": "https://ropes-dataset.s3-us-west-2.amazonaws.com/test/ropes-test-questions-v1.0.tar.gz",
-}
-
-
-class Ropes(datasets.GeneratorBasedBuilder):
-    """ROPES datset: testing a system's ability
-    to apply knowledge from a passage of text to a new situation.."""
-
-    VERSION = datasets.Version("1.1.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="plain_text", description="Plain text", version=VERSION),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "background": datasets.Value("string"),
-                    "situation": datasets.Value("string"),
-                    "question": datasets.Value("string"),
-                    "answers": datasets.features.Sequence(
-                        {
-                            "text": datasets.Value("string"),
-                        }
-                    ),
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://allenai.org/data/ropes",
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        archives = dl_manager.download(_URLs)
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": "/".join(["ropes-train-dev-v1.0", "train-v1.0.json"]),
-                    "split": "train",
-                    "files": dl_manager.iter_archive(archives["train+dev"]),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "filepath": "/".join(["ropes-test-questions-v1.0", "test-1.0.json"]),
-                    "split": "test",
-                    "files": dl_manager.iter_archive(archives["test"]),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "filepath": "/".join(["ropes-train-dev-v1.0", "dev-v1.0.json"]),
-                    "split": "dev",
-                    "files": dl_manager.iter_archive(archives["train+dev"]),
-                },
-            ),
-        ]
-
-    def _generate_examples(self, filepath, split, files):
-        """Yields examples."""
-        for path, f in files:
-            if path == filepath:
-                ropes = json.loads(f.read().decode("utf-8"))
-                for article in ropes["data"]:
-                    for paragraph in article["paragraphs"]:
-                        background = paragraph["background"].strip()
-                        situation = paragraph["situation"].strip()
-                        for qa in paragraph["qas"]:
-                            question = qa["question"].strip()
-                            id_ = qa["id"]
-                            answers = [] if split == "test" else [answer["text"].strip() for answer in qa["answers"]]
-
-                            yield id_, {
-                                "background": background,
-                                "situation": situation,
-                                "question": question,
-                                "id": id_,
-                                "answers": {
-                                    "text": answers,
-                                },
-                            }
-                break