add loading script

icsi_summ.py

@@ -0,0 +1,105 @@
+# coding=utf-8
+#
+"""ICSI summary dataset."""
+
+
+import json
+
+import datasets
+
+_CITATION = """\
+
+"""
+
+_DESCRIPTION = """\
+
+"""
+
+_HOMEPAGE = "https://groups.inf.ed.ac.uk/ami/icsi/"
+
+_LICENSE = "CC BY 4.0"
+
+_BASE_DATA_URL = "https://huggingface.co/datasets/yuanpj/icsi_summ/resolve/main/data/"
+
+_SPLIT_URL = _BASE_DATA_URL + "{split}.json"
+
+logger = datasets.utils.logging.get_logger(__name__)
+
+
+class IcsisummConfig(datasets.BuilderConfig):
+    """BuilderConfig for the summary subset of ICSI Corpus."""
+
+    def __init__(self, name, *args, **kwargs):
+        """BuilderConfig for the summary subset of ICSI Corpus"""
+        super().__init__(name=name, *args, **kwargs)
+
+
+class Icsisumm(datasets.GeneratorBasedBuilder):
+    """ICSI summary dataset."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [IcsisummConfig(name="icsi_summ")]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "sample_id": datasets.Value("string"),
+                "dialogue": [
+                    {
+                        "id": datasets.Value("string"),
+                        "speaker": datasets.Value("string"),
+                        "starttime": datasets.Value("string"),
+                        "startwordid": datasets.Value("string"),
+                        "endtime": datasets.Value("string"),
+                        "endwordid": datasets.Value("string"),
+                        "text": datasets.Value("string"),
+                        "label": datasets.Value("string"),
+                        "original_label": datasets.Value("string"),
+                        "attributes": datasets.Value("string"),
+                    }
+                ],
+                "summary": [
+                    {
+                        "id": datasets.Value("string"),
+                        "text": datasets.Value("string"),
+                        "type": datasets.Value("string"),
+                    }
+                ],
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        split_urls = {}
+        for split in ["dev", "test"]:
+            split_urls[split] = _SPLIT_URL.format(split=split)
+        file_paths = dl_manager.download(split_urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "path": file_paths["dev"],
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "path": file_paths["test"],
+                },
+            ),
+        ]
+
+    def _generate_examples(self, path):
+        """Yields examples."""
+        data = json.load(open(path, "r", encoding="utf-8"))
+        for example in data:
+            yield example["sample_id"], example