Fix style

viquiquad.py

@@ -1,26 +1,28 @@
+"""ViquiQuAD Dataset."""
 # Loading script for the ViquiQuAD dataset.
 import json
+
 import datasets
 
 logger = datasets.logging.get_logger(__name__)
 
-_CITATION = """
-               Rodriguez-Penagos, Carlos Gerardo, & Armentano-Oller, Carme. (2021). 
-               ViquiQuAD: an extractive QA dataset from Catalan Wikipedia (Version ViquiQuad_v.1.0.1) 
-               [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4761412
-            """
+_CITATION = """\
+Rodriguez-Penagos, Carlos Gerardo, & Armentano-Oller, Carme. (2021). 
+ViquiQuAD: an extractive QA dataset from Catalan Wikipedia (Version ViquiQuad_v.1.0.1) 
+[Data set]. Zenodo. http://doi.org/10.5281/zenodo.4761412
+"""
 
-_DESCRIPTION = """
-                  ViquiQuAD: an extractive QA dataset from Catalan Wikipedia.
-                  This dataset contains 3111 contexts extracted from a set of 597 high quality original (no translations) 
-                  articles in the Catalan Wikipedia "Viquipèdia" (ca.wikipedia.org), and 1 to 5 questions with their
-                  answer for each fragment. Viquipedia articles are used under CC-by-sa licence. 
-                  This dataset can be used to build extractive-QA and Language Models.
-                  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).
-               """
+_DESCRIPTION = """\
+ViquiQuAD: an extractive QA dataset from Catalan Wikipedia.
+This dataset contains 3111 contexts extracted from a set of 597 high quality original (no translations) 
+articles in the Catalan Wikipedia "Viquipèdia" (ca.wikipedia.org), and 1 to 5 questions with their
+answer for each fragment. Viquipedia articles are used under CC-by-sa licence. 
+This dataset can be used to build extractive-QA and Language Models.
+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://zenodo.org/record/4562345#.YK41aqGxWUk"""
+_HOMEPAGE = "https://zenodo.org/record/4562345#.YK41aqGxWUk"
 
 _URL = "https://huggingface.co/datasets/projecte-aina/viquiquad/resolve/main/"
 _TRAINING_FILE = "train.json"
@@ -42,17 +44,12 @@ class ViquiQuAD(datasets.GeneratorBasedBuilder):
                     "title": datasets.Value("string"),
                     "context": datasets.Value("string"),
                     "question": datasets.Value("string"),
-                    "answers":[
-
+                    "answers": [
                         {
-
                             "text": datasets.Value("string"),
-
                             "answer_start": datasets.Value("int32"),
-
                         }
-
-                    ]
+                    ],
                 }
             ),
             # No default supervised_keys (as we have to pass both question
@@ -89,10 +86,8 @@ class ViquiQuAD(datasets.GeneratorBasedBuilder):
                     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"]]
                         text = qa["answers"][0]["text"]
                         answer_start = qa["answers"][0]["answer_start"]
 
@@ -103,5 +98,5 @@ class ViquiQuAD(datasets.GeneratorBasedBuilder):
                             "context": context,
                             "question": question,
                             "id": id_,
-                            "answers": [{"text": text, "answer_start": answer_start}]
+                            "answers": [{"text": text, "answer_start": answer_start}],
                         }