dataset script

wsdmt.py

@@ -0,0 +1,86 @@
+import json
+
+import datasets
+from datasets import DownloadManager, DatasetInfo
+
+
+class WSDMTConfig(datasets.BuilderConfig):
+    def __init__(self, *args, corpus, lang1, lang2, path='data', **kwargs):
+        super().__init__(
+            *args,
+            name=f"{corpus}@{lang1}-{lang2}",
+            **kwargs,
+        )
+        self.lang1 = lang1
+        self.lang2 = lang2
+        self.corpus = corpus
+        self.path = path
+
+    def path_for(self, split, lang):
+        return f"{self.path}/{self.corpus}/{split}/{lang}.jsonl"
+
+
+class WSDMTDataset(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIG_CLASS = WSDMTConfig
+    config: WSDMTConfig
+
+    def _generate_examples(self, path_lang1, path_lang2):
+        with open(path_lang1) as f1, open(path_lang2) as f2:
+            for n, (line1, line2) in enumerate(zip(f1, f2)):
+                sentence1_data = json.loads(line1)
+                sentence2_data = json.loads(line2)
+
+                texts1, senses1, is_senses1 = zip(*sentence1_data['data'])
+                texts2, senses2, is_senses2 = zip(*sentence2_data['data'])
+                sid1, sid2 = sentence1_data['sid'], sentence2_data['sid']
+
+                assert sid1 == sid2, (
+                    f"Different sentence id found for {self.config.lang1} and {self.config.lang2}: "
+                    f"{sid1} != {sid2} at line {n}"
+                )
+
+                data_dict = {
+                    'sid': sid1,
+                    self.config.lang1: dict(tokens=texts1, sense=senses1, identified_as_sense=is_senses1),
+                    self.config.lang2: dict(tokens=texts2, sense=senses2, identified_as_sense=is_senses2),
+                }
+
+                yield n, data_dict
+
+    def _info(self) -> DatasetInfo:
+        return datasets.DatasetInfo(
+            description="empty description",
+            features=datasets.Features(
+                {
+                    "sid": datasets.Value("string"),
+                    self.config.lang1: {
+                        "tokens": datasets.Sequence(datasets.Value("string")),
+                        "sense": datasets.Sequence(datasets.Value("string")),
+                        "identified_as_sense": datasets.Sequence(datasets.Value("bool")),
+                    },
+                    self.config.lang2: {
+                        "tokens": datasets.Sequence(datasets.Value("string")),
+                        "sense": datasets.Sequence(datasets.Value("string")),
+                        "identified_as_sense": datasets.Sequence(datasets.Value("bool")),
+                    }
+                },
+            ),
+            supervised_keys=None,
+            homepage="no-homepage",
+            citation="no-citation",
+        )
+
+    def _split_generators(self, dl_manager: DownloadManager):
+        splits = [
+            (datasets.Split.TRAIN, 'train'),
+            (datasets.Split.VALIDATION, 'dev'),
+            (datasets.Split('test_2014'), 'test_2014'),
+            (datasets.Split('test_2019'), 'test_2019'),
+        ]
+        return [
+            datasets.SplitGenerator(name=split, gen_kwargs=dict(
+                path_lang1=self.config.path_for(path, self.config.lang1),
+                path_lang2=self.config.path_for(path, self.config.lang2),
+            ))
+            for split, path in splits
+        ]