Loader script is added

uzabsa.py

@@ -0,0 +1,83 @@
+import os
+import xml.etree.ElementTree as ET
+from datasets import DatasetBuilder, DatasetInfo, BuilderConfig, Split, SplitGenerator
+
+class UZABSAConfig(BuilderConfig):
+    def __init__(self, **kwargs):
+        super(UZABSAConfig, self).__init__(version="1.0.0", **kwargs)
+
+class UzABSA(DatasetBuilder):
+    BUILDER_CONFIG_CLASS = UZABSAConfig
+    BUILDER_CONFIGS = [
+        UZABSAConfig(name="uzabsa", description="Uzbek ABSA dataset"),
+    ]
+
+    def _info(self):
+        # Define the dataset features
+        return DatasetInfo(
+            features={
+                "sentence_id": datasets.Value("string"),
+                "text": datasets.Value("string"),
+                "aspect_terms": datasets.Sequence(
+                    {
+                        "term": datasets.Value("string"),
+                        "polarity": datasets.Value("string"),
+                        "from": datasets.Value("int32"),
+                        "to": datasets.Value("int32"),
+                    }
+                ),
+                "aspect_categories": datasets.Sequence(
+                    {
+                        "category": datasets.Value("string"),
+                        "polarity": datasets.Value("string"),
+                    }
+                ),
+            }
+        )
+
+    def _split_generators(self, dl_manager):
+        # Use os.path.join to find the XML file path
+        filepath = os.path.join(os.path.dirname(os.path.abspath(__file__)), "/dataset/uzabsa_all.xml")
+        return [
+            SplitGenerator(
+                name=Split.TRAIN,
+                gen_kwargs={
+                    "filepath": filepath,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        tree = ET.parse(filepath)
+        root = tree.getroot()
+
+        for sentence in root.findall("sentence"):
+            sentence_id = sentence.attrib["ID"]
+            text = sentence.find("text").text
+
+            aspect_terms = []
+            for aspect_term in sentence.findall(".//aspectTerms/aspectTerm"):
+                aspect_terms.append(
+                    {
+                        "term": aspect_term.attrib["term"],
+                        "polarity": aspect_term.attrib["polarity"],
+                        "from": int(aspect_term.attrib["from"]),
+                        "to": int(aspect_term.attrib["to"]),
+                    }
+                )
+
+            aspect_categories = []
+            for aspect_category in sentence.findall(".//aspectCategories/aspectCategory"):
+                aspect_categories.append(
+                    {
+                        "category": aspect_category.attrib["category"],
+                        "polarity": aspect_category.attrib["polarity"],
+                    }
+                )
+
+            yield sentence_id, {
+                "sentence_id": sentence_id,
+                "text": text,
+                "aspect_terms": aspect_terms,
+                "aspect_categories": aspect_categories,
+            }