Create dwy100k-d-y.py

dwy100k-d-y.py

@@ -0,0 +1,176 @@
+import datasets
+import os
+import pickle
+import json
+
+class Dwy100kDYConfig(datasets.BuilderConfig):
+
+    def __init__(self, features, data_url, citation, url, label_classes=("False", "True"), **kwargs):
+        super(Dwy100kDYConfig, self).__init__(version=datasets.Version("0.0.1"), **kwargs)
+        self.features = features
+        self.label_classes = label_classes
+        self.data_url = data_url
+        self.citation = citation
+        self.url = url
+
+
+class Dwy100kDY(datasets.GeneratorBasedBuilder):
+
+    BUILDER_CONFIGS = [
+        Dwy100kDYConfig(
+            name="source",
+            features=["column1", "column2", "column3"],
+            citation="TODO",
+            url="TODO",
+            data_url="https://huggingface.co/datasets/matchbench/dwy100k-d-y/resolve/main/dwy-dbp-yg-100k.zip"
+        ),
+        Dwy100kDYConfig(
+            name="target",
+            features=["column1", "column2", "column3"],
+            citation="TODO",
+            url="TODO",
+            data_url="https://huggingface.co/datasets/matchbench/dwy100k-d-y/resolve/main/dwy-dbp-yg-100k.zip"
+        ),
+        Dwy100kDYConfig(
+            name="pairs",
+            features=["left_id", "right_id"],
+            citation="TODO",
+            url="TODO",
+            data_url="https://huggingface.co/datasets/matchbench/dwy100k-d-y/resolve/main/dwy-dbp-yg-100k.zip"
+        ),
+    ]
+
+    def _info(self):
+        if self.config.name=="source":
+            features = {feature: datasets.Value("string") for feature in self.config.features}
+        elif self.config.name=="target":
+            features = {feature: datasets.Value("string") for feature in self.config.features}
+        elif self.config.name=="pairs":
+            features = {feature: datasets.Value("string") for feature in self.config.features}
+        
+        return datasets.DatasetInfo(
+            features=datasets.Features(features)
+        )
+
+    def _split_generators(self, dl_manager):
+        dl_dir = dl_manager.download_and_extract(self.config.data_url) or ""
+        #task_name = _get_task_name_from_data_url(self.config.data_url)
+        #dl_dir = os.path.join(dl_dir, task_name)
+        if self.config.name == "source":
+            return [
+            datasets.SplitGenerator(
+                name="ent_ids",
+                gen_kwargs={
+                    "data_file": os.path.join(dl_dir, "ent_ids_1"),
+                    "split": "ent_ids",
+                },
+            ),
+            datasets.SplitGenerator(
+                name="rel_triples_id",
+                gen_kwargs={
+                    "data_file": os.path.join(dl_dir, "triples_1"),
+                    "split": "rel_triples_id",
+                },
+            ),
+            ]
+        elif self.config.name == "target":
+            return [
+            datasets.SplitGenerator(
+                name="ent_ids",
+                gen_kwargs={
+                    "data_file": os.path.join(dl_dir, "ent_ids_2"),
+                    "split": "ent_ids",
+                },
+            ),
+            datasets.SplitGenerator(
+                name="rel_triples_id",
+                gen_kwargs={
+                    "data_file": os.path.join(dl_dir, "triples_2"),
+                    "split": "rel_triples_id",
+                },
+            )
+            ]
+        elif self.config.name == "pairs":
+            return [
+            datasets.SplitGenerator(
+                name="train",
+                gen_kwargs={
+                    "data_file": os.path.join(dl_dir, "train_ent_ids"),
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name="valid",
+                gen_kwargs={
+                    "data_file": os.path.join(dl_dir, "valid_ent_ids"),
+                    "split": "valid",
+                },
+            ),
+            datasets.SplitGenerator(
+                name="test",
+                gen_kwargs={
+                    "data_file": os.path.join(dl_dir, "ref_ent_ids"),
+                    "split": "test",
+                },
+            ),
+            datasets.SplitGenerator(
+                name="sup",
+                gen_kwargs={
+                    "data_file": os.path.join(dl_dir, "sup_ent_ids"),
+                    "split": "sup",
+                },
+            ),
+            datasets.SplitGenerator(
+                name="ref",
+                gen_kwargs={
+                    "data_file": os.path.join(dl_dir, "ref_ent_ids"),
+                    "split": "ref",
+                },
+            ),
+            ]
+
+
+    def _generate_examples(self, data_file, split):
+        if split in ["translated_name"]:
+            trans = json.load(open(data_file,"r"))
+            #i = -1
+            for i in range(len(trans)):
+                yield i, {
+                    "column1": str(trans[i][0]),
+                    "column2": str(trans[i][1]),
+                    "column3": None
+                }
+        else:
+            f = open(data_file,"r",encoding='utf-8')
+            data = f.readlines()
+            for i in range(len(data)):
+                #print(row)
+                if self.config.name in ["source", "target"]:
+                    if split in ["ent_ids","rel_ids"]:
+                        row = data[i].strip('\n').split('\t')
+                        yield i, {
+                                    "column1": row[0],
+                                    "column2": row[1],
+                                    "column3": None
+                                }
+                    elif split in ["rel_triples_id","rel_triples_whole","rel_triples_name"]:
+                        row = data[i].strip('\n').split('\t')
+                        yield i, {
+                                    "column1": row[0],
+                                    "column2": row[1],
+                                    "column3": row[2]
+                                }
+                    elif split in ["attr_triples"]:
+                        row = data[i].rstrip('\n').split('\t')
+                        yield i, {
+                                    "column1": row[0],
+                                    "column2": row[1],
+                                    "column3": row[2]
+                                }
+                        
+                if self.config.name == "pairs":
+                    row = data[i].strip('\n').split('\t')
+                    yield i, {
+                                "left_id": row[0],
+                                "right_id": row[1]
+                    }