Datasets:

GEM
/

wiki_auto_asset_turk

@@ -1,246 +0,0 @@
-import csv
-import json
-import os
-import datasets
-_CITATION = """\
-@inproceedings{jiang-etal-2020-neural,
-    title = "Neural {CRF} Model for Sentence Alignment in Text Simplification",
-    author = "Jiang, Chao  and
-      Maddela, Mounica  and
-      Lan, Wuwei  and
-      Zhong, Yang  and
-      Xu, Wei",
-    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.709",
-    doi = "10.18653/v1/2020.acl-main.709",
-    pages = "7943--7960",
-}
-"""
-_DESCRIPTION = """\
-WikiAuto provides a set of aligned sentences from English Wikipedia and Simple
-English Wikipedia as a resource to train sentence simplification systems.
-The authors first crowd-sourced a set of manual alignments between sentences in
-a subset of the Simple English Wikipedia and their corresponding versions in
-English Wikipedia (this corresponds to the manual config in this version of the
-dataset), then trained a neural CRF system to predict these alignments.
-The trained alignment prediction model was then applied to the other articles in
-Simple English Wikipedia with an English counterpart to create a larger corpus
-of aligned sentences (corresponding to the auto and auto_acl configs here).
-"""
-_URLs = {
-    "train": "train.tsv",
-    "validation": "valid.tsv",
-    "test_turk": "https://storage.googleapis.com/huggingface-nlp/datasets/gem/gem_turk_detokenized.json",
-    "challenge_set": "https://storage.googleapis.com/huggingface-nlp/datasets/gem/gem_challenge_sets/wiki_auto_asset_turk_train_valid.zip",
-    "test_contract": "benchmarks/contract-benchmark.tsv",
-    "test_wiki": "benchmarks/wiki-benchmark.tsv",
-}
-# Add Asset files.
-_URLs[
-    "test_asset_orig"
-] = "https://raw.githubusercontent.com/facebookresearch/asset/main/dataset/asset.test.orig"
-for i in range(10):
-    _URLs[
-        f"test_asset_{i}"
-    ] = f"https://raw.githubusercontent.com/facebookresearch/asset/main/dataset/asset.test.simp.{i}"
-class WikiAuto(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.0.0")
-    DEFAULT_CONFIG_NAME = "wiki_auto_asset_turk"
-    def _info(self):
-        features = datasets.Features(
-            {
-                "gem_id": datasets.Value("string"),
-                "gem_parent_id": datasets.Value("string"),
-                "source": datasets.Value("string"),
-                "target": datasets.Value("string"),
-                "references": [datasets.Value("string")],
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=datasets.info.SupervisedKeysData(
-                input="source", output="target"
-            ),
-            homepage="",
-            citation=_CITATION,
-        )
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        dl_dir = dl_manager.download_and_extract(_URLs)
-        challenge_sets = [
-            (
-                "challenge_train_sample",
-                "train_wiki_auto_asset_turk_RandomSample500.json",
-            ),
-            (
-                "challenge_validation_sample",
-                "validation_wiki_auto_asset_turk_RandomSample500.json",
-            ),
-            (
-                "challenge_test_asset_backtranslation",
-                "test_asset_wiki_auto_asset_turk_BackTranslation.json",
-            ),
-            (
-                "challenge_test_asset_bfp02",
-                "test_asset_wiki_auto_asset_turk_ButterFingersPerturbation_p=0.02.json",
-            ),
-            (
-                "challenge_test_asset_bfp05",
-                "test_asset_wiki_auto_asset_turk_ButterFingersPerturbation_p=0.05.json",
-            ),
-            (
-                "challenge_test_asset_nopunc",
-                "test_asset_wiki_auto_asset_turk_WithoutPunctuation.json",
-            ),
-            (
-                "challenge_test_turk_backtranslation",
-                "detok_test_turk_wiki_auto_asset_turk_BackTranslation.json",
-            ),
-            (
-                "challenge_test_turk_bfp02",
-                "detok_test_turk_wiki_auto_asset_turk_ButterFingersPerturbation_p=0.02.json",
-            ),
-            (
-                "challenge_test_turk_bfp05",
-                "detok_test_turk_wiki_auto_asset_turk_ButterFingersPerturbation_p=0.05.json",
-            ),
-            (
-                "challenge_test_turk_nopunc",
-                "detok_test_turk_wiki_auto_asset_turk_WithoutPunctuation.json",
-            ),
-        ]
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "filepath": dl_dir["train"],
-                    "split": "train",
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "filepath": dl_dir["validation"],
-                    "split": "validation",
-                },
-            ),
-            datasets.SplitGenerator(
-                name="test_asset",
-                gen_kwargs={
-                    "filepath": "",
-                    "split": "test_asset",
-                    "filepaths": [dl_dir["test_asset_orig"]]
-                    + [dl_dir[f"test_asset_{i}"] for i in range(10)],
-                },
-            ),
-            datasets.SplitGenerator(
-                name="test_turk",
-                gen_kwargs={
-                    "filepath": dl_dir["test_turk"],
-                    "split": "test_turk",
-                },
-            ),
-            datasets.SplitGenerator(
-                name="test_contract",
-                gen_kwargs={
-                    "filepath": dl_dir["test_contract"],
-                    "split": "test_contract",
-                },
-            ),
-            datasets.SplitGenerator(
-                name="test_wiki",
-                gen_kwargs={
-                    "filepath": dl_dir["test_wiki"],
-                    "split": "test_wiki",
-                },
-            ),
-        ] + [
-            datasets.SplitGenerator(
-                name=challenge_split,
-                gen_kwargs={
-                    "filepath": os.path.join(
-                        dl_dir["challenge_set"], "wiki_auto_asset_turk", filename
-                    ),
-                    "split": challenge_split,
-                },
-            )
-            for challenge_split, filename in challenge_sets
-        ]
-    def _generate_examples(self, filepath, split, filepaths=None, lang=None):
-        """Yields examples."""
-        if split in ["train", "validation"]:
-            keys = [
-                "source",
-                "target",
-            ]
-            with open(filepath, encoding="utf-8") as f:
-                for id_, line in enumerate(f):
-                    values = line.strip().split("\t")
-                    assert (
-                        len(values) == 2
-                    ), f"Not enough fields in ---- {line} --- {values}"
-                    example = dict([(k, val) for k, val in zip(keys, values)])
-                    example["gem_id"] = f"wiki_auto_asset_turk-{split}-{id_}"
-                    example["gem_parent_id"] = example["gem_id"]
-                    example["references"] = (
-                        [] if split == "train" else [example["target"]]
-                    )
-                    yield id_, example
-        elif split == "test_turk":
-            examples = json.load(open(filepath, encoding="utf-8"))
-            for id_, example in enumerate(examples):
-                example["gem_parent_id"] = example["gem_id"]
-                for k in ["source_id", "target_id"]:
-                    if k in example:
-                        del example[k]
-                yield id_, example
-        elif split == "test_asset":
-            files = [open(f_name, encoding="utf-8") for f_name in filepaths]
-            for id_, lines in enumerate(zip(*files)):
-                yield id_, {
-                    "gem_id": f"wiki_auto_asset_turk-{split}-{id_}",
-                    "gem_parent_id": f"wiki_auto_asset_turk-{split}-{id_}",
-                    "target": lines[1].strip(),
-                    "source": lines[0].strip(),
-                    "references": [line.strip() for line in lines[1:]],
-                }
-        elif split == "test_wiki" or split == "test_contract":
-            with open(filepath, 'r') as f:
-                reader = csv.DictReader(f, delimiter="\t")
-                for id_, entry in enumerate(reader):
-                    yield id_, {
-                        "gem_id": f"wiki_auto_asset_turk-{split}-{id_}",
-                        "gem_parent_id": f"wiki_auto_asset_turk-{split}-{id_}",
-                        "target": entry["simple"],
-                        "source": entry["complex"],
-                        "references": [entry["simple"]],
-                    }
-        else:
-            exples = json.load(open(filepath, encoding="utf-8"))
-            if isinstance(exples, dict):
-                assert len(exples) == 1, "multiple entries found"
-                exples = list(exples.values())[0]
-            for id_, exple in enumerate(exples):
-                exple["gem_parent_id"] = exple["gem_id"]
-                exple["gem_id"] = f"wiki_auto_asset_turk-{split}-{id_}"
-                for k in ["source_id", "target_id"]:
-                    if k in exple:
-                        del exple[k]
-                yield id_, exple