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dataset_infos.json

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europarl-mono.py

@@ -0,0 +1,137 @@
+"""Europarl Monolingual Dataset."""
+
+from __future__ import absolute_import, division, print_function
+from dataclasses import dataclass
+
+import json
+import os
+import re
+
+import datasets
+
+
+_CITATION = """\
+@inproceedings{koehn2005europarl,
+  title={Europarl: A parallel corpus for statistical machine translation},
+  author={Koehn, Philipp},
+  booktitle={MT summit},
+  volume={5},
+  pages={79--86},
+  year={2005},
+  organization={Citeseer}
+}
+"""
+
+_DESCRIPTION = """\
+Europarl Monolingual Dataset.
+
+The Europarl parallel corpus is extracted from the proceedings of the
+European Parliament (from 2000 to 2011). It includes versions in 21 European
+languages: Romanic (French, Italian, Spanish, Portuguese, Romanian),
+Germanic (English, Dutch, German, Danish, Swedish), Slavik (Bulgarian,
+Czech, Polish, Slovak, Slovene), Finni-Ugric (Finnish, Hungarian, Estonian),
+Baltic (Latvian, Lithuanian), and Greek.
+
+Upstream url: https://www.statmt.org/europarl/
+"""
+
+_HOMEPAGE = "https://www.statmt.org/europarl/"
+
+_AVAILABLE_LANGUAGES = [
+    ("bg", "Bulgarian"), ("cs", "Czech"), ("da", "Danish"), ("de", "German"),
+    ("el", "Greek"), ("en", "English"), ("es", "Spanish"), ("et", "Estonian"),
+    ("fi", "Finnish"), ("fr", "French"), ("hu", "Hungarian"), ("it", "Italian"),
+    ("lt", "Lithuanian"), ("lv", "Latvian"), ("nl", "Dutch"), ("pl", "Polish"),
+    ("pt", "Portuguese"), ("ro", "Romanian"), ("sk", "Slovak"),
+    ("sl", "Slovene"), ("sv", "Swedish")
+]
+
+@dataclass
+class EuroparlMonoConfig(datasets.BuilderConfig):
+    """BuilderConfig for Europarl Monolingual."""
+    language: str = None
+
+
+class EuroparlMonoDataset(datasets.GeneratorBasedBuilder):
+    """Europarl Monolingual Dataset."""
+
+    _TRAIN_FILE = "train.jsonl"
+    _VAL_FILE = "val.jsonl"
+    _TEST_FILE = "test.jsonl"
+
+    BUILDER_CONFIGS = [
+        EuroparlMonoConfig(
+            name="europarl-%s" % langISO2,
+            language=langISO2,
+            version=datasets.Version("7.0.0"),
+            description="Europarl %s Dataset." % langEnglish,
+        ) for langISO2, langEnglish in _AVAILABLE_LANGUAGES
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "paragraph": datasets.Value("string"),
+                    "date": datasets.Value("string"),
+                    "chapter": datasets.Value("string"),
+                    "speaker": datasets.Value("int16"),
+                    "speaker_name": datasets.Value("string")
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        arch_path = dl_manager.download_and_extract(os.path.join(_HOMEPAGE, "v%d" % self.config.version.major, "europarl.tgz"))
+        path_dir = os.path.join(arch_path, os.path.join("txt", self.config.language))
+        paths = [os.path.join(path_dir, file) for file in os.listdir(path_dir)]
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN, gen_kwargs={"filepath": paths}
+            )
+        ]
+
+    def _generate_examples(self, filepath):
+        """Generate Europarl Monolingual examples."""
+
+        id_ = 0
+        for file in filepath:
+            with open(file, "r") as f:
+                current_date = "-".join(os.path.basename(file).strip(".txt").split("-")[-4:-1])
+                current_paragraph = ""
+                current_paragraph_id = 0
+                current_chapter = 0
+                current_speaker_id = 0
+                current_speaker_name = ""
+                for line in f:
+                    if not line.startswith("<"):
+                        current_paragraph += line.strip("\n")
+                    else:
+                        if len(current_paragraph) != 0:
+                            yield id_, {
+                                "paragraph": current_paragraph,
+                                "date": current_date,
+                                "chapter": current_chapter,
+                                "speaker": current_speaker_id,
+                                "speaker_name": current_speaker_name,
+                            }
+                            current_paragraph = ""
+                            id_ += 1
+                        if line.startswith("<P>"):
+                            current_paragraph_id += 1
+                        if line.startswith("<CHAPTER"):
+                            current_chapter = line.lstrip("<CHAPTER ID=").rstrip(">\n").strip("\"")
+                        if line.startswith("<SPEAKER"):
+                            current_speaker_id = "0"
+                            current_speaker_name = ""
+                            grps = re.findall("([^<\s]+)=([^\s\">]+|\"[^\">]+\")", line)
+                            for attr, value in grps:
+                                value = value.strip("\"")
+                                if attr == "ID":
+                                    current_speaker_id = int(value)
+                                elif attr == "NAME":
+                                    current_speaker_name = value