Delete AV.py

AV.py

@@ -1,65 +0,0 @@
-""" generated with GPT-4o """
-from datasets import GeneratorBasedBuilder, DatasetInfo, SplitGenerator, Split, BuilderConfig
-import datasets
-import csv
-import pyarrow as pa
-import os
-
-class CustomConfig(BuilderConfig):
-    def __init__(self, **kwargs):
-        super().__init__(**kwargs)
-
-class MyDataset(GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        CustomConfig(
-            name="Contrastive Learning",
-            version=datasets.Version("1.0.0"),
-            description="Load from Arrow files"
-        ),
-        CustomConfig(
-            name="Thresholding",
-            version=datasets.Version("1.0.0"),
-            description="Load from CSV files"
-        ),
-    ]
-
-    def _info(self):
-        return DatasetInfo()
-
-    def _split_generators(self, dl_manager):
-        if self.config.name == "Contrastive Learning":
-            return [
-                SplitGenerator(name=Split.TRAIN, gen_kwargs={"filepath": "train/data-00000-of-00001.arrow"}),
-                SplitGenerator(name=Split.VALIDATION, gen_kwargs={"filepath": "validation/data-00000-of-00001.arrow"}),
-                SplitGenerator(name=Split.TEST, gen_kwargs={"filepath": "test/data-00000-of-00001.arrow"}),
-            ]
-
-        elif self.config.name == "Thresholding":
-            return [
-                SplitGenerator(name=Split.TRAIN, gen_kwargs={"filepath": "train/train.csv"}),
-                SplitGenerator(name=Split.VALIDATION, gen_kwargs={"filepath": "validation/validation.csv"}),
-                SplitGenerator(name=Split.TEST, gen_kwargs={"filepath": "test/test.csv"}),
-            ]
-
-        else:
-            raise ValueError(f"Unsupported config: {self.config.name}")
-
-    def _generate_examples(self, filepath):
-        if filepath.endswith(".arrow"):
-            with open(filepath, "rb") as f:
-                try:
-                    table = pa.ipc.RecordBatchFileReader(f).read_all()
-                except Exception as e:
-                    raise ValueError(f"Could not read Arrow file: {filepath}") from e
-            data = table.to_pydict()
-            for i in range(len(next(iter(data.values())))):
-                yield i, {k: data[k][i] for k in data}
-
-        elif filepath.endswith(".csv"):
-            with open(filepath, encoding="utf-8") as f:
-                reader = csv.DictReader(f)
-                for i, row in enumerate(reader):
-                    yield i, row
-
-        else:
-            raise ValueError(f"Unsupported file format: {filepath}")