Convert dataset to Parquet (#3)

- Convert dataset to Parquet (2e86c733ba1549f9207b70b961e2b6a6a1f18fb2)
- Delete loading script (4169d92a4339f015c98cb5bc71d81df5b3459372)
- Add ratings data files (39f7d3f54e6083e13bdf36d318a275b66f30d7a6)
- Delete legacy dataset_infos.json (189d740542f7349d6c79a25a4251fcb07e6be141)

README.md

@@ -21,24 +21,12 @@ task_ids:
 - text-simplification
 paperswithcode_id: asset
 pretty_name: ASSET
+config_names:
+- ratings
+- simplification
 tags:
 - simplification-evaluation
 dataset_info:
-- config_name: simplification
-  features:
-  - name: original
-    dtype: string
-  - name: simplifications
-    sequence: string
-  splits:
-  - name: validation
-    num_bytes: 2303496
-    num_examples: 2000
-  - name: test
-    num_bytes: 411031
-    num_examples: 359
-  download_size: 3639353
-  dataset_size: 2714527
 - config_name: ratings
   features:
   - name: original
@@ -60,13 +48,37 @@ dataset_info:
     dtype: int32
   splits:
   - name: full
-    num_bytes: 1036853
+    num_bytes: 1036845
     num_examples: 4500
-  download_size: 3639353
-  dataset_size: 1036853
-config_names:
-- ratings
-- simplification
+  download_size: 44642
+  dataset_size: 1036845
+- config_name: simplification
+  features:
+  - name: original
+    dtype: string
+  - name: simplifications
+    sequence: string
+  splits:
+  - name: validation
+    num_bytes: 2303484
+    num_examples: 2000
+  - name: test
+    num_bytes: 411019
+    num_examples: 359
+  download_size: 1055163
+  dataset_size: 2714503
+configs:
+- config_name: ratings
+  data_files:
+  - split: full
+    path: ratings/full-*
+- config_name: simplification
+  data_files:
+  - split: validation
+    path: simplification/validation-*
+  - split: test
+    path: simplification/test-*
+  default: true
 ---
 
 # Dataset Card for ASSET

asset.py

@@ -1,174 +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.
-"""ASSET: a dataset for sentence simplification evaluation"""
-
-
-import csv
-
-import datasets
-
-
-_CITATION = """\
-@inproceedings{alva-manchego-etal-2020-asset,
-    title = "{ASSET}: {A} Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations",
-    author = "Alva-Manchego, Fernando  and
-      Martin, Louis  and
-      Bordes, Antoine  and
-      Scarton, Carolina  and
-      Sagot, Benoit  and
-      Specia, Lucia",
-    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
-    month = jul,
-    year = "2020",
-    address = "Online",
-    publisher = "Association for Computational Linguistics",
-    url = "https://www.aclweb.org/anthology/2020.acl-main.424",
-    pages = "4668--4679",
-}
-"""
-
-_DESCRIPTION = """\
-ASSET is a dataset for evaluating Sentence Simplification systems with multiple rewriting transformations,
-as described in "ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations".
-The corpus is composed of 2000 validation and 359 test original sentences that were each simplified 10 times by different annotators.
-The corpus also contains human judgments of meaning preservation, fluency and simplicity for the outputs of several automatic text simplification systems.
-"""
-
-_HOMEPAGE = "https://github.com/facebookresearch/asset"
-
-_LICENSE = "Creative Common Attribution-NonCommercial 4.0 International"
-
-_URL_LIST = [
-    (
-        "human_ratings.csv",
-        "https://raw.githubusercontent.com/facebookresearch/asset/main/human_ratings/human_ratings.csv",
-    ),
-    (
-        "asset.valid.orig",
-        "https://raw.githubusercontent.com/facebookresearch/asset/main/dataset/asset.valid.orig",
-    ),
-    (
-        "asset.test.orig",
-        "https://raw.githubusercontent.com/facebookresearch/asset/main/dataset/asset.test.orig",
-    ),
-]
-_URL_LIST += [
-    (
-        f"asset.{spl}.simp.{i}",
-        f"https://raw.githubusercontent.com/facebookresearch/asset/main/dataset/asset.{spl}.simp.{i}",
-    )
-    for spl in ["valid", "test"]
-    for i in range(10)
-]
-
-_URLs = dict(_URL_LIST)
-
-
-class Asset(datasets.GeneratorBasedBuilder):
-
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="simplification",
-            version=VERSION,
-            description="A set of original sentences aligned with 10 possible simplifications for each.",
-        ),
-        datasets.BuilderConfig(
-            name="ratings",
-            version=VERSION,
-            description="Human ratings of automatically produced text implification.",
-        ),
-    ]
-
-    DEFAULT_CONFIG_NAME = "simplification"
-
-    def _info(self):
-        if self.config.name == "simplification":
-            features = datasets.Features(
-                {
-                    "original": datasets.Value("string"),
-                    "simplifications": datasets.Sequence(datasets.Value("string")),
-                }
-            )
-        else:
-            features = datasets.Features(
-                {
-                    "original": datasets.Value("string"),
-                    "simplification": datasets.Value("string"),
-                    "original_sentence_id": datasets.Value("int32"),
-                    "aspect": datasets.ClassLabel(names=["meaning", "fluency", "simplicity"]),
-                    "worker_id": datasets.Value("int32"),
-                    "rating": datasets.Value("int32"),
-                }
-            )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        data_dir = dl_manager.download_and_extract(_URLs)
-        if self.config.name == "simplification":
-            return [
-                datasets.SplitGenerator(
-                    name=datasets.Split.VALIDATION,
-                    gen_kwargs={
-                        "filepaths": data_dir,
-                        "split": "valid",
-                    },
-                ),
-                datasets.SplitGenerator(
-                    name=datasets.Split.TEST,
-                    gen_kwargs={"filepaths": data_dir, "split": "test"},
-                ),
-            ]
-        else:
-            return [
-                datasets.SplitGenerator(
-                    name="full",
-                    gen_kwargs={
-                        "filepaths": data_dir,
-                        "split": "full",
-                    },
-                ),
-            ]
-
-    def _generate_examples(self, filepaths, split):
-        """Yields examples."""
-        if self.config.name == "simplification":
-            files = [open(filepaths[f"asset.{split}.orig"], encoding="utf-8")] + [
-                open(filepaths[f"asset.{split}.simp.{i}"], encoding="utf-8") for i in range(10)
-            ]
-            for id_, lines in enumerate(zip(*files)):
-                yield id_, {
-                    "original": lines[0].strip(),
-                    "simplifications": [line.strip() for line in lines[1:]],
-                }
-        else:
-            with open(filepaths["human_ratings.csv"], encoding="utf-8") as f:
-                reader = csv.reader(f, delimiter=",")
-                for id_, row in enumerate(reader):
-                    if id_ == 0:
-                        keys = row[:]
-                    else:
-                        res = dict([(k, v) for k, v in zip(keys, row)])
-                        for k in ["original_sentence_id", "worker_id", "rating"]:
-                            res[k] = int(res[k])
-                        yield (id_ - 1), res

dataset_infos.json

@@ -1 +0,0 @@
-{"simplification": {"description": "ASSET is a dataset for evaluating Sentence Simplification systems with multiple rewriting transformations,\nas described in \"ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations\".\nThe corpus is composed of 2000 validation and 359 test original sentences that were each simplified 10 times by different annotators.\nThe corpus also contains human judgments of meaning preservation, fluency and simplicity for the outputs of several automatic text simplification systems.\n", "citation": "@inproceedings{alva-manchego-etal-2020-asset,\n    title = \"{ASSET}: {A} Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations\",\n    author = \"Alva-Manchego, Fernando  and\n      Martin, Louis  and\n      Bordes, Antoine  and\n      Scarton, Carolina  and\n      Sagot, Benoit  and\n      Specia, Lucia\",\n    booktitle = \"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics\",\n    month = jul,\n    year = \"2020\",\n    address = \"Online\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://www.aclweb.org/anthology/2020.acl-main.424\",\n    pages = \"4668--4679\",\n}\n", "homepage": "https://github.com/facebookresearch/asset", "license": "Creative Common Attribution-NonCommercial 4.0 International", "features": {"original": {"dtype": "string", "id": null, "_type": "Value"}, "simplifications": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "asset", "config_name": "simplification", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"validation": {"name": "validation", "num_bytes": 2303496, "num_examples": 2000, "dataset_name": "asset"}, "test": {"name": 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