Convert dataset to Parquet

README.md

@@ -20,6 +20,7 @@ task_ids:
 paperswithcode_id: squad-es
 pretty_name: SQuAD-es
 dataset_info:
+- config_name: v1.1.0
   features:
   - name: id
     dtype: string
@@ -35,16 +36,53 @@ dataset_info:
       dtype: string
     - name: answer_start
       dtype: int32
-  config_name: v1.1.0
   splits:
   - name: train
-    num_bytes: 83680438
+    num_bytes: 83570686
     num_examples: 87595
   - name: validation
-    num_bytes: 10955800
+    num_bytes: 10936484
     num_examples: 10570
-  download_size: 39291362
-  dataset_size: 94636238
+  download_size: 16687140
+  dataset_size: 94507170
+- config_name: v2.0.0
+  features:
+  - name: id
+    dtype: string
+  - name: title
+    dtype: string
+  - name: context
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answers
+    sequence:
+    - name: text
+      dtype: string
+    - name: answer_start
+      dtype: int32
+  splits:
+  - name: train
+    num_bytes: 122845988
+    num_examples: 130313
+  - name: validation
+    num_bytes: 12248541
+    num_examples: 11858
+  download_size: 18152297
+  dataset_size: 135094529
+configs:
+- config_name: v1.1.0
+  data_files:
+  - split: train
+    path: v1.1.0/train-*
+  - split: validation
+    path: v1.1.0/validation-*
+- config_name: v2.0.0
+  data_files:
+  - split: train
+    path: v2.0.0/train-*
+  - split: validation
+    path: v2.0.0/validation-*
 ---
 
 # Dataset Card for "squad_es"

squad_es.py

@@ -1,151 +0,0 @@
-"""TODO(squad_es): Add a description here."""
-
-
-import json
-
-import datasets
-
-
-# TODO(squad_es): BibTeX citation
-_CITATION = """\
-@article{2016arXiv160605250R,
-       author = {Casimiro Pio , Carrino and  Marta R. , Costa-jussa and  Jose A. R. , Fonollosa},
-        title = "{Automatic Spanish Translation of the SQuAD Dataset for Multilingual
-Question Answering}",
-      journal = {arXiv e-prints},
-         year = 2019,
-          eid = {arXiv:1912.05200v1},
-        pages = {arXiv:1912.05200v1},
-archivePrefix = {arXiv},
-       eprint = {1912.05200v2},
-}
-"""
-
-# TODO(squad_es_v1):
-_DESCRIPTION = """\
-automatic translation of the Stanford Question Answering Dataset (SQuAD) v2 into Spanish
-"""
-
-_URL = "https://raw.githubusercontent.com/ccasimiro88/TranslateAlignRetrieve/master/"
-_URLS_V1 = {
-    "train": _URL + "SQuAD-es-v1.1/train-v1.1-es.json",
-    "dev": _URL + "SQuAD-es-v1.1/dev-v1.1-es.json",
-}
-_URLS_V2 = {
-    "train": _URL + "SQuAD-es-v2.0/train-v2.0-es.json",
-    "dev": _URL + "SQuAD-es-v2.0/dev-v2.0-es.json",
-}
-
-
-class SquadEsConfig(datasets.BuilderConfig):
-    """BuilderConfig for SQUADEsV2."""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for SQUADEsV2.
-
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(SquadEsConfig, self).__init__(**kwargs)
-
-
-class SquadEs(datasets.GeneratorBasedBuilder):
-    """TODO(squad_es): Short description of my dataset."""
-
-    # TODO(squad_es): Set up version.
-    VERSION = datasets.Version("0.1.0")
-
-    BUILDER_CONFIGS = [
-        SquadEsConfig(
-            name="v1.1.0",
-            version=datasets.Version("1.1.0", ""),
-            description="Plain text Spanish squad version 1",
-        ),
-        SquadEsConfig(
-            name="v2.0.0",
-            version=datasets.Version("2.0.0", ""),
-            description="Plain text Spanish squad version 2",
-        ),
-    ]
-
-    def _info(self):
-        # TODO(squad_es): Specifies the datasets.DatasetInfo object
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # datasets.features.FeatureConnectors
-            features=datasets.Features(
-                {
-                    # These are the features of your dataset like images, labels ...
-                    "id": datasets.Value("string"),
-                    "title": datasets.Value("string"),
-                    "context": datasets.Value("string"),
-                    "question": datasets.Value("string"),
-                    "answers": datasets.features.Sequence(
-                        {
-                            "text": datasets.Value("string"),
-                            "answer_start": datasets.Value("int32"),
-                        }
-                    ),
-                }
-            ),
-            # If there's a common (input, target) tuple from the features,
-            # specify them here. They'll be used if as_supervised=True in
-            # builder.as_dataset.
-            supervised_keys=None,
-            # Homepage of the dataset for documentation
-            homepage="https://github.com/ccasimiro88/TranslateAlignRetrieve",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        # TODO(squad_es): Downloads the data and defines the splits
-        # dl_manager is a datasets.download.DownloadManager that can be used to
-
-        # download and extract URLs
-        if self.config.name == "v1.1.0":
-            dl_dir = dl_manager.download_and_extract(_URLS_V1)
-        elif self.config.name == "v2.0.0":
-            dl_dir = dl_manager.download_and_extract(_URLS_V2)
-        else:
-            raise Exception("version does not match any existing one")
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": dl_dir["train"]},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={"filepath": dl_dir["dev"]},
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        # TODO(squad_es): Yields (key, example) tuples from the dataset
-        with open(filepath, encoding="utf-8") as f:
-            data = json.load(f)
-            for example in data["data"]:
-                title = example.get("title", "").strip()
-                for paragraph in example["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"]]
-
-                        yield id_, {
-                            "title": title,
-                            "context": context,
-                            "question": question,
-                            "id": id_,
-                            "answers": {
-                                "answer_start": answer_starts,
-                                "text": answers,
-                            },
-                        }

v1.1.0/train-00000-of-00001.parquet

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+size 14830851

v1.1.0/validation-00000-of-00001.parquet

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+size 1856289

v2.0.0/train-00000-of-00001.parquet

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+size 16773981

v2.0.0/validation-00000-of-00001.parquet

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+size 1378316