first version of mfaq dataset

.gitignore

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+test.py

README.md

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+hello

mfaq.py

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+# coding=utf-8
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import csv
+import json
+import os
+
+import datasets
+
+
+_CITATION = """\
+@InProceedings{mfaq_a_multilingual_dataset,
+    title={MFAQ: a Multilingual FAQ Dataset},
+    author={Maxime {De Bruyn} and Ehsan Lotfi and Jeska Buhmann and Walter Daelemans},
+    year={2021},
+    booktitle={MRQA @ EMNLP 2021}
+}
+"""
+
+
+_DESCRIPTION = """\
+We present the first multilingual FAQ dataset publicly available. We collected around 6M FAQ pairs from the web, in 21 different languages.
+"""
+
+_HOMEPAGE = ""
+
+_LICENSE = ""
+
+
+_LANGUAGES = ["cs", "da", "de", "en", "es", "fi", "fr", "he", "hr", "hu", "id", "it", "nl", "no", "pl", "pt", "ro", "ru", "sv", "tr", "vi"]
+_URLs = {}
+_URLs.update({f"{l}": {"train": f"data/{l}/train.jsonl", "valid": f"data/{l}/valid.jsonl"} for l in _LANGUAGES})
+_URLs.update({f"{l}_flat": {"train": f"data/{l}/train.jsonl", "valid": f"data/{l}/valid.jsonl"} for l in _LANGUAGES})
+
+
+class MFAQ(datasets.GeneratorBasedBuilder):
+
+    VERSION = datasets.Version("1.0.0")
+    BUILDER_CONFIGS = list(map(lambda x: datasets.BuilderConfig(name=x, version=datasets.Version("1.1.0")), _URLs.keys()))
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "id": datasets.Value("int64"),
+                "language": datasets.Value("string"),
+                "num_pairs": datasets.Value("int64"),
+                "domain": datasets.Value("string"),
+                "qa_pairs": datasets.features.Sequence(
+                    {
+                        "question": datasets.Value("string"), 
+                        "answer": datasets.Value("string"),
+                        "language": datasets.Value("string")
+                    }
+                )
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,  # Here we define them above because they are different between the two configurations
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        my_urls = _URLs[self.config.name]
+        data_dir = dl_manager.download_and_extract(my_urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": data_dir["train"], "split": "train"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": data_dir["valid"], "split": "valid"},
+            ),
+        ]
+
+    def _generate_examples(
+        self, filepath, split  # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    ):
+        """ Yields examples as (key, example) tuples. """
+
+        with open(filepath, encoding="utf-8") as f:
+            for _id, row in enumerate(f):
+                data = json.loads(row)
+                if "flat" in self.config.name:
+                    for i, pair in enumerate(data["qa_pairs"]):
+                        yield f"{_id}_{i}", {
+                            "id": data["id"],
+                            "domain": data["domain"],
+                            "language": data["language"],
+                            "num_pairs": 1,
+                            "qa_pairs": [pair]
+                        }
+                else:
+                    yield _id, {
+                        "id": data["id"],
+                        "domain": data["domain"],
+                        "language": data["language"],
+                        "num_pairs": data["num_pairs"],
+                        "qa_pairs": data["qa_pairs"]
+                    }