loading script default

story.py

@@ -0,0 +1,131 @@
+import csv
+import os
+
+import datasets
+
+_CITATION = """\
+@Dataset{wisdomify:storyteller,
+title = {Korean proverb definitions and examples},
+author={Jongyoon Kim, Yubin Kim, Yongtaek Im
+},
+year={2021}
+}
+"""
+
+_DESCRIPTION = """\
+This dataset is designed to provide forward and reverse dictionary of Korean proverbs.
+"""
+
+# TODO: Add a link to an official homepage for the dataset here
+_HOMEPAGE = ""
+
+# TODO: Add the licence for the dataset here if you can find it
+_LICENSE = ""
+
+# TODO: Add link to the official dataset URLs here
+#  If it is dropbox link, you must set 1 for query parameter "dl".
+_URLs = {
+    'definition': "https://www.dropbox.com/s/4uh564afaimtob3/definition.zip?dl=1",
+    'example': "https://www.dropbox.com/s/adlt9n6x5gjs0a6/example.zip?dl=1",
+}
+
+
+class Story(datasets.GeneratorBasedBuilder):
+    # version must be "x.y.z' form
+    VERSION = datasets.Version("0.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="definition", version=VERSION, description="definition"),
+        datasets.BuilderConfig(name="example", version=VERSION, description="example"),
+    ]
+
+    # This config is applied when user load dataset without "name".
+    DEFAULT_CONFIG_NAME = "definition"
+
+    def _info(self):
+        # This method specifies the datasets.DatasetInfo object which contains information
+        #                                                            and typings for the dataset
+
+        if self.config.name == "definition":
+            # These are the features of your dataset like images, labels ...
+            features = datasets.Features(
+                {
+                    "wisdom": datasets.Value("string"),
+                    "def": datasets.Value("string"),
+
+                }
+            )
+        elif self.config.name == "example":
+            features = datasets.Features(
+                {
+                    "wisdom": datasets.Value("string"),
+                    "eg": datasets.Value("string"),
+                }
+            )
+        else:
+            raise NotImplementedError(f"Wrong name: {self.config.name}")
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # This method is used when user loads dataset.
+        # dl_manager can be used to download and extract the dataset
+        # and also can set split depending onf the configuration
+
+        # Downloading data with _URLs
+        downloaded_files = dl_manager.download_and_extract(_URLs[self.config.name])
+
+        dtp = 'def' if self.config.name == "definition" else 'eg'
+
+        train_path = os.path.join(downloaded_files, f'train_wisdom2{dtp}.tsv')
+        val_path = os.path.join(downloaded_files, f'val_wisdom2{dtp}.tsv')
+        test_path = os.path.join(downloaded_files, f'test_wisdom2{dtp}.tsv')
+
+        return [
+            # These gen_kwargs will be passed to _generate_examples
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": train_path, "split": "train"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": val_path, "split": "validation"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": test_path, "split": "test"},
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+        """ Yields examples as (key, example) tuples. """
+        # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
+        # The `key` is here for legacy reason (tfds) and is not important in itself.
+
+        with open(filepath, encoding="utf-8") as f:
+            tsv_reader = csv.reader(f, delimiter="\t")
+            for id_, row in enumerate(tsv_reader):
+                if id_ == 0:
+                    continue  # first row shows column info
+
+                if self.config.name == "definition":
+                    yield id_, {
+                        "wisdom": row[0],
+                        "def": row[1],
+                    }
+                elif self.config.name == "example":
+                    yield id_, {
+                        "wisdom": row[0],
+                        "eg": row[1],
+                    }
+                else:
+                    raise NotImplementedError(f"Wrong name: {self.config.name}")