Upload intoxicat.py

intoxicat.py

@@ -0,0 +1,112 @@
+# Loading script for the IntoxiCat dataset.
+
+import json
+
+import datasets
+
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_CITATION = """ """
+
+
+_DESCRIPTION = """ InToxiCat is a dataset for the detection of abusive language in Catalan. """
+
+
+_HOMEPAGE = """ https://huggingface.co/datasets/projecte-aina/InToxiCat"""
+
+
+
+_URL = "https://huggingface.co/datasets/projecte-aina/InToxicat/resolve/main/"
+_FILE_TRAIN = "train.json"
+_FILE_DEV = "dev.json"
+_FILE_TEST = "test.json"
+
+
+class InToxiCatConfig(datasets.BuilderConfig):
+    """ Builder config for the InToxiCat dataset """
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for InToxiCat.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(InToxiCatConfig, self).__init__(**kwargs)
+
+
+class InToxiCat(datasets.GeneratorBasedBuilder):
+    """ InToxiCat Dataset """
+
+
+    BUILDER_CONFIGS = [
+        InToxiCatConfig(
+            name="InToxiCat",
+            version=datasets.Version("1.0.0"),
+            description="InToxiCat dataset",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                 "id": datasets.Value("string"),
+                 "context": datasets.Value("string"),
+                 "sentence": datasets.Value("string"),
+                 "topic": datasets.Value("string"),
+                 "keywords": datasets.Sequence(datasets.Value("string")),
+                 "context_needed": datasets.Value("string"),
+                 "is_abusive": datasets.features.ClassLabel(names=['abusive','not_abusive']),
+                 "abusiveness_agreement": datasets.Value("string"),
+                 "target_type": datasets.Sequence(datasets.features.ClassLabel(names=['INDIVIDUAL','GROUP','OTHERS'])),
+                 "abusive_spans": datasets.Sequence(feature={'text': datasets.Value(dtype='string', id=None), 'index': datasets.Value(dtype='string', id=None)}, length=-1, id=None), #datasets.Sequence(feature=datasets.Sequence(datasets.Value(dtype='string', id=None))),
+                 "target_spans": datasets.Sequence(feature={'text': datasets.Value(dtype='string', id=None), 'index': datasets.Value(dtype='string', id=None)}, length=-1, id=None),
+                 "is_implicit": datasets.Value("string")
+                }
+            ),
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls_to_download = {
+            "train": f"{_FILE_TRAIN}",
+            "dev": f"{_FILE_DEV}",
+            "test": f"{_FILE_TEST}"
+        }
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]})
+        ]
+
+    def _generate_examples(self, filepath):
+        """This function returns the examples in the raw (text) form."""
+        logger.info("generating examples from = %s", filepath)
+        data = json.load(open(filepath, 'r'))
+        for id_, example in enumerate(data):
+            yield id_, {
+                "id": example["id"],
+                "context": example["context"],
+                "sentence": example["sentence"],
+                "topic": example["topic"],
+                "keywords": example["key_words"],
+                "context_needed": example["annotation"]["context_needed"] if example["annotation"]["context_needed"] else None,
+                "is_abusive": example["annotation"]["is_abusive"] if example["annotation"]["is_abusive"] else None,
+                "abusiveness_agreement": example["annotation"]["abusiveness_agreement"],
+                "target_type": example["annotation"]["target_type"] if example["annotation"]["target_type"] else None,
+                "abusive_spans": {
+                    "text": [text for text, _ in example["annotation"]["abusive_spans"]],
+                    "index": [index for _, index in example["annotation"]["abusive_spans"]]
+                    } if example["annotation"]["abusive_spans"] != [] else None,
+                "target_spans": {
+                    "text": [text for text, _ in example["annotation"]["target_spans"]],
+                    "index": [index for _, index in example["annotation"]["target_spans"]]
+                    } if example["annotation"]["target_spans"] != [] else None,
+                "is_implicit": example["annotation"]["is_implicit"] if example["annotation"]["is_implicit"] != "" else None
+            }