edited build_database

build_database.py

@@ -1 +1,99 @@
-test
+import json
+import os
+
+import datasets
+
+
+
+_CITATION = """\
+@InProceedings{huggingface:dataset,
+title = {Ember2018-malware-v2},
+author=Christian Williams
+},
+year={2024}
+}
+"""
+
+_DESCRIPTION = """\
+This dataset is based on the EMBER 2018 Malware Analysis dataset that was uploaded to kaggle
+"""
+_HOMEPAGE = "https://www.kaggle.com/datasets/dhoogla/ember-2018-v2-features"
+
+_LICENSE = ""
+
+class EMBERConfig(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.1.0")
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="text_classification", 
+            version=VERSION,
+            description="This part of my dataset can be used to train LLMs for text classification",
+            license=""
+        )
+    ]
+
+    DEFAULT_CONFIG_NAME = "text_classification" 
+
+    def _info(self):
+        if self.config.name == "text_classification": 
+            features = datasets.Features(
+                {
+                    "input": datasets.Value("string"),
+                    "label": datasets.Value("string"),
+                }
+            )
+        else: 
+            features = datasets.Features(
+                {
+                    "input": datasets.Value("string"),
+                    "label": datasets.Value("string"),
+                }
+            )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features, 
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+        
+    def _split_generators(self, dl_manager):
+        _URLS = "https://huggingface.co/datasets/cw1521/ember2018-malware-v2/tree/main/data"
+        urls = _URLS[self.config.name]
+        data_dir = dl_manager.download_and_extract(urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepaths": os.path.join(data_dir, "ember2018-train_*.jsonl"),
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepaths": os.path.join(data_dir, "ember2018-test_*.jsonl"),
+                    "split": "test"
+                },
+            )
+        ]
+
+
+    def _generate_examples(self, filepaths, split):
+        key = 0
+        for id, filepath in enumerate(filepaths[split]): 
+            key += 1
+            with open(filepath[id], encoding="utf-8") as f:
+                data_list = json.load(f)
+                for data in data_list:
+                    if self.config.name == "text_classification":
+                        data.remove
+                        yield key, {
+                            "input": data["input"],
+                            "label": data["label"]
+                        }
+                    else:
+                        yield key, {
+                            "input": data["input"],
+                            "label": data["label"]
+                        }