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nordic_dsl_10000test.csv

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nordic_dsl_10000train.csv

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nordic_dsl_50000test.csv

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nordic_dsl_50000train.csv

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nordic_langid.py

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+# coding=utf-8
+# Copyright 2020 HuggingFace Datasets Authors.
+#
+# 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.
+
+# Lint as: python3
+"""NordicDSL: A language identification datasets for Nordic languages"""
+
+import csv
+import os
+
+import datasets
+
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_CITATION = """\
+@inproceedings{haas-derczynski-2021-discriminating,
+    title = "Discriminating Between Similar Nordic Languages",
+    author = "Haas, Ren{\'e}  and
+      Derczynski, Leon",
+    booktitle = "Proceedings of the Eighth Workshop on NLP for Similar Languages, Varieties and Dialects",
+    month = apr,
+    year = "2021",
+    address = "Kiyv, Ukraine",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2021.vardial-1.8",
+    pages = "67--75",
+}
+
+"""
+
+_DESCRIPTION = """\
+Automatic language identification is a challenging problem. Discriminating
+between closely related languages is especially difficult. This paper presents
+a machine learning approach for automatic language identification for the
+Nordic languages, which often suffer miscategorisation by existing 
+state-of-the-art tools. Concretely we will focus on discrimination between six 
+Nordic languages: Danish, Swedish, Norwegian (Nynorsk), Norwegian (Bokmål), 
+Faroese and Icelandic.
+
+This is the data for the tasks. Two variants are provided: 10K and 50K, with
+holding 10,000 and 50,000 examples for each language respectively.
+
+"""
+
+_URLS = {
+    "10K": "nordic_dsl_10000",
+    "50K": "nordic_dsl_50000",
+}
+
+
+class NordicLangIdConfig(datasets.BuilderConfig):
+    """BuilderConfig for NordicLangId"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig NordicLangId.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(NordicLangIdConfig, self).__init__(**kwargs)
+
+
+class NordicLangId(datasets.GeneratorBasedBuilder):
+    """NordicLangId dataset."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        NordicLangIdConfig(
+            name="10k", 
+            description="Data for distinguishing between similar Nordic languages: 10k examples per class",
+            version=VERSION, 
+        ),
+        NordicLangIdConfig(
+            name="50k", 
+            description="Data for distinguishing between similar Nordic languages: 50k examples per class",
+            version=VERSION, 
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "sentence": datasets.Value("string"),
+                    "language": datasets.features.ClassLabel(
+                        names=[
+                            "dk",
+                            "sv",
+                            "nb",
+                            "nn",
+                            "fo",
+                            "is",
+                        ]
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage="https://aclanthology.org/2021.vardial-1.8/",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        if self.config.name == "10k":
+            downloaded_train = dl_manager.download(_URLS["10K"] + 'train.csv')
+            downloaded_test = dl_manager.download(_URLS["10K"] + 'test.csv')
+        elif self.config.name == "50k":
+            downloaded_train = dl_manager.download(_URLS["50K"] + 'train.csv')
+            downloaded_test = dl_manager.download(_URLS["50K"] + 'test.csv')
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_train}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_test}),
+        ]
+
+    def _generate_examples(self, filepath):
+        logger.info("⏳ Generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            guid = 0
+            for line in f:
+                line = line.strip()
+                if not line:
+                    continue
+                if self.config.name == "10k":
+                    line = line.replace('dataset10000, ', '')
+                if self.config.name == "50k":
+                    line = line.replace('dataset50000, ', '')
+                
+                instance = {
+                    "id": str(guid),
+                    "language": line[-2:],
+                    "sentence": line[:-3],
+                }
+
+                yield guid, instance
+                guid += 1