Update files from the datasets library (from 1.0.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.0.0

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

dataset_infos.json

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+{"default": {"description": "LC-QuAD 2.0 is a Large Question Answering dataset with 30,000 pairs of question and its corresponding SPARQL query. The target knowledge base is Wikidata and DBpedia, specifically the 2018 version. Please see our paper for details about the dataset creation process and framework.\n", "citation": "\n@inproceedings{dubey2017lc2,\ntitle={LC-QuAD 2.0: A Large Dataset for Complex Question Answering over Wikidata and DBpedia},\nauthor={Dubey, Mohnish and Banerjee, Debayan and Abdelkawi, Abdelrahman and Lehmann, Jens},\nbooktitle={Proceedings of the 18th International Semantic Web Conference (ISWC)},\nyear={2019},\norganization={Springer}\n}\n", "homepage": "http://lc-quad.sda.tech/", "license": "", "features": {"NNQT_question": {"dtype": "string", "id": null, "_type": "Value"}, "uid": {"dtype": "int32", "id": null, "_type": "Value"}, "subgraph": {"dtype": "string", "id": null, "_type": "Value"}, "template_index": {"dtype": "int32", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "sparql_wikidata": {"dtype": "string", "id": null, "_type": "Value"}, "sparql_dbpedia18": {"dtype": "string", "id": null, "_type": "Value"}, "template": {"dtype": "string", "id": null, "_type": "Value"}, "paraphrased_question": {"dtype": "string", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "lc_quad", "config_name": "default", "version": {"version_str": "2.0.0", "description": null, "datasets_version_to_prepare": null, "major": 2, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 4072474, "num_examples": 4781, "dataset_name": "lc_quad"}, "train": {"name": "train", "num_bytes": 16660621, "num_examples": 19293, "dataset_name": "lc_quad"}}, "download_checksums": {"https://github.com/AskNowQA/LC-QuAD2.0/archive/master.zip": {"num_bytes": 3868211, "checksum": "b3475828357b6a4661362287911275240efebe484ca9849ac6b2e314f5e90843"}}, "download_size": 3868211, "dataset_size": 20733095, "size_in_bytes": 24601306}}

dummy/2.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b36702aaebe1b946ed53bcb287856636314bdc2598a10a4f47058e51d8d2219d
+size 2286

lc_quad.py

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+"""TODO(lc_quad): Add a description here."""
+
+from __future__ import absolute_import, division, print_function
+
+import json
+import os
+
+import datasets
+
+
+# TODO(lc_quad): BibTeX citation
+_CITATION = """
+@inproceedings{dubey2017lc2,
+title={LC-QuAD 2.0: A Large Dataset for Complex Question Answering over Wikidata and DBpedia},
+author={Dubey, Mohnish and Banerjee, Debayan and Abdelkawi, Abdelrahman and Lehmann, Jens},
+booktitle={Proceedings of the 18th International Semantic Web Conference (ISWC)},
+year={2019},
+organization={Springer}
+}
+"""
+
+# TODO(lc_quad):
+_DESCRIPTION = """\
+LC-QuAD 2.0 is a Large Question Answering dataset with 30,000 pairs of question and its corresponding SPARQL query. The target knowledge base is Wikidata and DBpedia, specifically the 2018 version. Please see our paper for details about the dataset creation process and framework.
+"""
+_URL = "https://github.com/AskNowQA/LC-QuAD2.0/archive/master.zip"
+
+
+class LcQuad(datasets.GeneratorBasedBuilder):
+    """TODO(lc_quad): Short description of my dataset."""
+
+    # TODO(lc_quad): Set up version.
+    VERSION = datasets.Version("2.0.0")
+
+    def _info(self):
+        # TODO(lc_quad): 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(
+                {
+                    "NNQT_question": datasets.Value("string"),
+                    "uid": datasets.Value("int32"),
+                    "subgraph": datasets.Value("string"),
+                    "template_index": datasets.Value("int32"),
+                    "question": datasets.Value("string"),
+                    "sparql_wikidata": datasets.Value("string"),
+                    "sparql_dbpedia18": datasets.Value("string"),
+                    "template": datasets.Value("string"),
+                    # "template_id": datasets.Value('string'),
+                    "paraphrased_question": datasets.Value("string")
+                    # These are the features of your dataset like images, labels ...
+                }
+            ),
+            # 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="http://lc-quad.sda.tech/",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # TODO(lc_quad): Downloads the data and defines the splits
+        # dl_manager is a datasets.download.DownloadManager that can be used to
+        # download and extract URLs
+        dl_dir = dl_manager.download_and_extract(_URL)
+        dl_dir = os.path.join(dl_dir, "LC-QuAD2.0-master", "dataset")
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": os.path.join(dl_dir, "train.json")},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"filepath": os.path.join(dl_dir, "test.json")},
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        # TODO(lc_quad): Yields (key, example) tuples from the dataset
+        with open(filepath, encoding="utf-8") as f:
+            data = json.load(f)
+            for id_, row in enumerate(data):
+                is_list = False
+                for key in row:
+                    if key != "answer" and isinstance(row[key], list):
+                        is_list = True
+                if is_list:
+                    continue
+                yield id_, {
+                    "NNQT_question": row["NNQT_question"],
+                    "uid": row["uid"],
+                    "subgraph": row["subgraph"],
+                    "template_index": row["template_index"],
+                    "question": row["question"],
+                    "sparql_wikidata": row["sparql_wikidata"],
+                    "sparql_dbpedia18": row["sparql_dbpedia18"],
+                    "template": row["template"],
+                    # "template_id": str(row['template_id']),
+                    "paraphrased_question": row["paraphrased_question"],
+                }