Delete bayelemabaga.py

bayelemabaga.py

@@ -1,131 +0,0 @@
-""" RobotsMaliAI: Bayelemaba """
-
-import datasets
-
-_CITATION = """\
-@misc{bayelemabagamldataset2022
-    title={Machine Learning Dataset Development for Manding Languages},
-    author={
-        Valentin Vydrin and
-        Christopher Homan and
-        Michael Leventhal and
-        Allashera Auguste Tapo and
-        Marco Zampieri and
-        Jean-Jacques Meric and
-        Kirill Maslinsky and
-        Andrij Rovenchak and
-        Sebastien Diarra
-
-    },
-    howpublished = {url{https://github.com/robotsmali-ai/datasets}},
-    year={2022}
-}
-"""
-
-_DESCRIPTION = """\
-The Bayelemabaga dataset is a collection of 44160 aligned machine translation ready Bambara-French lines, 
-originating from Corpus Bambara de Reference. The dataset is constitued of text extracted from 231 source files, 
-varing from periodicals, books, short stories, blog posts, part of the Bible and the Quran.
-"""
-
-_URL = {
-    "parallel": "https://robotsmali-ai.github.io/datasets/bayelemabaga.tar.gz"
-}
-
-_LanguagePairs = [
-    "bam-fr", "fr-bam"]
-
-class BayelemabagaConfig(datasets.BuilderConfig):
-    """ BuilderConfig for Bayelemabaga """
-
-    def __init__(self, language_pair, **kwargs) -> None:
-        """
-        Args:
-            language_pair: language pair, you want to load
-            **kwargs: -> Super()
-        """
-        super().__init__(**kwargs)
-
-        self.language_pair = language_pair
-
-class Bayelemabaga(datasets.GeneratorBasedBuilder):
-    """ Bi-Lingual Bam, Fr text made for Machine Translation """
-
-    VERSION = datasets.Version("1.0.0")
-    BUILDER_CONFIG_CLASS = BayelemabagaConfig
-
-    BUILDER_CONFIGS = [
-        BayelemabagaConfig(name="bam-fr", description=_DESCRIPTION, language_pair="bam-fr"),
-        BayelemabagaConfig(name="fr-bam", description=_DESCRIPTION, language_pair="fr-bam")
-    ]
-
-    def _info(self):
-        src_tag, tgt_tag = self.config.language_pair.split("-")
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features({"translation": datasets.features.Translation(languages=(src_tag, tgt_tag))}),
-            supervised_keys=(src_tag, tgt_tag),
-            homepage="https://robotsmali-ai.github.io/datasets",
-            citation=_CITATION
-        )
-
-    def _split_generators(self, dl_manager):
-        lang_pair = self.config.language_pair
-        src_tag, tgt_tag = lang_pair.split("-")
-
-        archive = dl_manager.download(_URL["parallel"])
-
-        train_dir = "bayelemabaga/train"
-        valid_dir = "bayelemabaga/valid"
-        test_dir = "bayelemabaga/test"
-        
-        train = datasets.SplitGenerator(
-            name=datasets.Split.TRAIN,
-            gen_kwargs = {
-                "filepath": f"{train_dir}/train.{src_tag}",
-                "labelpath": f"{train_dir}/train.{tgt_tag}",
-                "files": dl_manager.iter_archive(archive)
-            }
-        )
-
-        valid = datasets.SplitGenerator(
-            name=datasets.Split.VALIDATION,
-            gen_kwargs = {
-                "filepath": f"{valid_dir}/dev.{src_tag}",
-                "labelpath": f"{valid_dir}/dev.{tgt_tag}",
-                "files": dl_manager.iter_archive(archive)
-            }
-        )
-
-        test = datasets.SplitGenerator(
-            name=datasets.Split.TEST,
-            gen_kwargs = {
-                "filepath": f"{test_dir}/test.{src_tag}",
-                "labelpath": f"{test_dir}/test.{tgt_tag}",
-                "files": dl_manager.iter_archive(archive)
-            }
-        )
-
-        output = []
-
-        output.append(train)
-        output.append(valid)
-        output.append(test)
-
-        return output
-    
-    def _generate_examples(self, filepath, labelpath, files):
-        """ Yield examples """
-        src_tag, tgt_tag = self.config.language_pair.split("-")
-        src, tgt = None, None
-
-        for path, f in files:
-            if(path == filepath):
-                src = f.read().decode("utf-8").split("\n")[:-1]
-            elif(path == labelpath):
-                tgt = f.read().decode("utf-8").split("\n")[:-1]
-            
-            if(src is not None and tgt is not None):
-                for idx, (s,t) in enumerate(zip(src, tgt)):
-                    yield idx, {"translation": {src_tag: s, tgt_tag: t}}
-                break