Fix style

vilaquad.py

@@ -6,191 +6,118 @@ import datasets
 
 logger = datasets.logging.get_logger(__name__)
 
-_CITATION = """
+_CITATION = """\
+Rodriguez-Penagos, Carlos Gerardo, & Armentano-Oller, Carme. (2021).
+VilaQuAD: an extractive QA dataset for catalan, from Vilaweb newswire text
+[Data set]. Zenodo. https://doi.org/10.5281/zenodo.4562337
+"""
 
-               Rodriguez-Penagos, Carlos Gerardo, & Armentano-Oller, Carme. (2021). 
+_DESCRIPTION = """\
+This dataset contains 2095 of Catalan language news articles along with 1 to 5 questions referring to each fragment (or context).
 
-               VilaQuAD: an extractive QA dataset for catalan, from Vilaweb newswire text
+VilaQuad articles are extracted from the daily Vilaweb (www.vilaweb.cat) and used under CC-by-nc-sa-nd (https://creativecommons.org/licenses/by-nc-nd/3.0/deed.ca) licence. 
 
-               [Data set]. Zenodo. https://doi.org/10.5281/zenodo.4562337
-               
-            """
+This dataset can be used to build extractive-QA and Language Models.
 
-_DESCRIPTION = """
+Funded by the Generalitat de Catalunya, Departament de Polítiques Digitals i Administració Pública (AINA),
 
-                This dataset contains 2095 of Catalan language news articles along with 1 to 5 questions referring to each fragment (or context).
-                
-                VilaQuad articles are extracted from the daily Vilaweb (www.vilaweb.cat) and used under CC-by-nc-sa-nd (https://creativecommons.org/licenses/by-nc-nd/3.0/deed.ca) licence. 
-                
-                This dataset can be used to build extractive-QA and Language Models.
+MT4ALL and Plan de Impulso de las Tecnologías del Lenguaje (Plan TL).
+"""
 
-                Funded by the Generalitat de Catalunya, Departament de Polítiques Digitals i Administració Pública (AINA),
-
-                MT4ALL and Plan de Impulso de las Tecnologías del Lenguaje (Plan TL).
-
-               """
-
-_HOMEPAGE = """https://doi.org/10.5281/zenodo.4562337"""
+_HOMEPAGE = "https://doi.org/10.5281/zenodo.4562337"
 
 _URL = "https://huggingface.co/datasets/projecte-aina/vilaquad/resolve/main/"
-
 _TRAINING_FILE = "train.json"
-
 _DEV_FILE = "dev.json"
-
 _TEST_FILE = "test.json"
 
-class VilaQuADConfig(datasets.BuilderConfig):
 
-    """ Builder config for the VilaQuAD dataset """
+class VilaQuADConfig(datasets.BuilderConfig):
+    """Builder config for the VilaQuAD dataset"""
 
     def __init__(self, **kwargs):
-
         """BuilderConfig for VilaQuAD.
 
         Args:
-
           **kwargs: keyword arguments forwarded to super.
-
         """
-
         super(VilaQuADConfig, self).__init__(**kwargs)
 
-class VilaQuAD(datasets.GeneratorBasedBuilder):
 
+class VilaQuAD(datasets.GeneratorBasedBuilder):
     """VilaQuAD Dataset."""
 
     BUILDER_CONFIGS = [
-
         VilaQuADConfig(
-
             name="VilaQuAD",
-
             version=datasets.Version("1.0.1"),
-
             description="VilaQuAD dataset",
-
         ),
-
     ]
 
     def _info(self):
 
         return datasets.DatasetInfo(
-
             description=_DESCRIPTION,
-
             features=datasets.Features(
-
                 {
-
                     "id": datasets.Value("string"),
-
                     "title": datasets.Value("string"),
-
                     "context": datasets.Value("string"),
-
                     "question": datasets.Value("string"),
-
                     "answers": [
-
                         {
-
                             "text": datasets.Value("string"),
-
                             "answer_start": datasets.Value("int32"),
-
                         }
-
                     ],
-
                 }
-
             ),
-
             # No default supervised_keys (as we have to pass both question
-
             # and context as input).
-
             supervised_keys=None,
-
             homepage=_HOMEPAGE,
-
             citation=_CITATION,
-
         )
 
     def _split_generators(self, dl_manager):
-
         """Returns SplitGenerators."""
-
         urls_to_download = {
-
             "train": f"{_URL}{_TRAINING_FILE}",
-
             "dev": f"{_URL}{_DEV_FILE}",
-
             "test": f"{_URL}{_TEST_FILE}",
-
         }
-
         downloaded_files = dl_manager.download_and_extract(urls_to_download)
 
         return [
-
             datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-
             datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
-
             datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
-
         ]
 
     def _generate_examples(self, filepath):
-
         """This function returns the examples in the raw (text) form."""
-
         logger.info("generating examples from = %s", filepath)
-
         with open(filepath, encoding="utf-8") as f:
-
             vilaquad = json.load(f)
-
             for article in vilaquad["data"]:
-
                 title = article.get("title", "").strip()
-
                 for paragraph in article["paragraphs"]:
-
                     context = paragraph["context"].strip()
-
                     for qa in paragraph["qas"]:
-
                         question = qa["question"].strip()
-
                         id_ = qa["id"]
-
-                        #answer_starts = [answer["answer_start"] for answer in qa["answers"]]
-
-                        #answers = [answer["text"].strip() for answer in qa["answers"]]
-                        
-
+                        # answer_starts = [answer["answer_start"] for answer in qa["answers"]]
+                        # answers = [answer["text"].strip() for answer in qa["answers"]]
                         # Features currently used are "context", "question", and "answers".
-
                         # Others are extracted here for the ease of future expansions.
                         text = qa["answers"][0]["text"]
                         answer_start = qa["answers"][0]["answer_start"]
 
                         yield id_, {
-
                             "title": title,
-
                             "context": context,
-
                             "question": question,
-
                             "id": id_,
-
-                            "answers": [{"text": text, "answer_start": answer_start}]
-
+                            "answers": [{"text": text, "answer_start": answer_start}],
                         }