rm script

sts22-crosslingual-sts.py

@@ -1,119 +0,0 @@
-import json
-import datasets
-import os
-
-_CITATION = """\
-"""
-
-_LICENSE = """\
-"""
-
-_DESCRIPTION = """\
-SemEval 2022 Task 8: Multilingual News Article Similarity
-"""
-
-_LANGUAGES_TRAIN = {
-    "en": "en",
-    "de": "de",
-    "es": "es",
-    "pl": "pl",
-    "tr": "tr",
-    "fr": "fr",
-    "ar": "ar",
-    "de-en": "de-en",
-}
-_LANGUAGES_TEST = {
-    "en": "en",
-    "de": "de",
-    "es": "es",
-    "pl": "pl",
-    "tr": "tr",
-    "ar": "ar",
-    "ru": "ru",
-    "zh": "zh",
-    "fr": "fr",
-    "de-en": "de-en",
-    "es-en": "es-en",
-    "it": "it",
-    "pl-en": "pl-en",
-    "zh-en": "zh-en",
-    "es-it": "es-it",
-    "de-fr": "de-fr",
-    "de-pl": "de-pl",
-    "fr-pl": "fr-pl",
-}
-_LANGUAGES = {**_LANGUAGES_TRAIN, **_LANGUAGES_TEST}
-
-_ALL_LANGUAGES = "all_languages"
-_HOMEPAGE_URL = "https://competitions.codalab.org/competitions/33835"
-_DOWNLOAD_URL = "{lang}/{split}.jsonl"
-_VERSION = "1.0.1"
-
-
-class STS22Task8Config(datasets.BuilderConfig):
-    """BuilderConfig for STS22Task8Config."""
-
-    def __init__(self, languages=None, **kwargs):
-        super(STS22Task8Config, self).__init__(version=datasets.Version(_VERSION, ""), **kwargs),
-        self.languages = languages
-
-
-class STS22Task8(datasets.GeneratorBasedBuilder):
-
-    """Multilingual News Article Similarity"""
-
-    BUILDER_CONFIGS = [
-        STS22Task8Config(
-            name=_ALL_LANGUAGES,
-            languages=_LANGUAGES,
-            description="Multilingual News Article Similarity",
-        )
-    ] + [
-        STS22Task8Config(
-            name=lang,
-            languages=[lang],
-            description=f"{_LANGUAGES[lang]} examples from a collection of multilingual news articles",
-        )
-        for lang in _LANGUAGES
-    ]
-    BUILDER_CONFIG_CLASS = STS22Task8Config
-    DEFAULT_CONFIG_NAME = _ALL_LANGUAGES
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "sentence1": datasets.Value("string"),
-                    "sentence2": datasets.Value("string"),
-                    "score": datasets.Value("float32"),
-                },
-            ),
-            supervised_keys=None,
-            license=_LICENSE,
-            homepage=_HOMEPAGE_URL,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        # train_urls = [_DOWNLOAD_URL.format(split="train", lang=lang) for lang in self.config.languages if lang in _LANGUAGES_TRAIN]
-        test_urls = [
-            _DOWNLOAD_URL.format(split="test", lang=lang) for lang in self.config.languages if lang in _LANGUAGES_TEST
-        ]
-
-        # train_paths = dl_manager.download_and_extract(train_urls)
-        test_paths = dl_manager.download_and_extract(test_urls)
-
-        return [
-            # datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"file_paths": train_paths}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"file_paths": test_paths}),
-        ]
-
-    def _generate_examples(self, file_paths):
-        row_count = 0
-        for file_path in file_paths:
-            with open(file_path, "r", encoding="utf-8") as f:
-                for line in f:
-                    yield row_count, json.loads(line)
-                    row_count += 1