Update dataset.py

dataset.py

@@ -0,0 +1,61 @@
+import json
+import os
+import datasets
+
+# Define the dataset
+class M3Retrieve(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description="M3Retrieve: Benchmarking Multimodal Retrieval for Medicine",
+            features={
+                "queries": {
+                    "_id": datasets.Value("string"),
+                    "caption": datasets.Value("string"),
+                    "image_path": datasets.Value("string"),
+                },
+                "corpus": {
+                    "_id": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                },
+                "qrels": {
+                    "query-id": datasets.Value("string"),
+                    "corpus-id": datasets.Value("string"),
+                    "score": datasets.Value("float32"),
+                },
+            },
+            supervised_keys=None,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        data_dir = dl_manager.download_and_extract(self.config.data_dir)
+
+        return [
+            datasets.SplitGenerator(
+                name="queries",
+                gen_kwargs={"filepath": os.path.join(data_dir, "queries.jsonl"), "key": "queries"},
+            ),
+            datasets.SplitGenerator(
+                name="corpus",
+                gen_kwargs={"filepath": os.path.join(data_dir, "corpus.jsonl"), "key": "corpus"},
+            ),
+            datasets.SplitGenerator(
+                name="qrels",
+                gen_kwargs={"filepath": os.path.join(data_dir, "qrels/test.tsv"), "key": "qrels"},
+            ),
+        ]
+
+    def _generate_examples(self, filepath, key):
+        """Yields examples as (key, example) tuples."""
+        if key in ["queries", "corpus"]:
+            with open(filepath, "r", encoding="utf-8") as f:
+                for i, line in enumerate(f):
+                    data = json.loads(line)
+                    yield i, data
+        elif key == "qrels":
+            with open(filepath, "r", encoding="utf-8") as f:
+                for i, line in enumerate(f):
+                    query_id, corpus_id, score = line.strip().split("\t")
+                    yield i, {"query-id": query_id, "corpus-id": corpus_id, "score": float(score)}