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MixBench25.py

@@ -101,12 +101,13 @@ import json
 import datasets
 import csv
 
-_DESCRIPTION = """\
-MixBench is a benchmark for evaluating mixed-modality retrieval. It contains queries and corpora from four datasets: MSCOCO, Google_WIT, VisualNews, and OVEN. \
+_DESCRIPTION = """
+MixBench is a benchmark for evaluating mixed-modality retrieval. It contains queries and corpora from four datasets: MSCOCO, Google_WIT, VisualNews, and OVEN.
 Each subset provides: query, corpus, mixed_corpus, and qrel splits.
 """
 
 _HOMEPAGE = "https://huggingface.co/datasets/mixed-modality-search/MixBench25"
+
 _SUBSETS = ["MSCOCO", "Google_WIT", "VisualNews", "OVEN"]
 
 class MixBenchConfig(datasets.BuilderConfig):
@@ -118,35 +119,13 @@ class MixBenchConfig(datasets.BuilderConfig):
 class MixBench(datasets.GeneratorBasedBuilder):
     BUILDER_CONFIGS = [MixBenchConfig(name=subset) for subset in _SUBSETS]
 
-    def _info(self):
-        # This will be overwritten per split below
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features({
-                "placeholder": datasets.Value("string")
-            }),
-            homepage=_HOMEPAGE,
-        )
-
     def _split_generators(self, dl_manager):
         subset_dir = os.path.join(dl_manager.manual_dir or dl_manager._base_path, self.config.name)
         return [
-            datasets.SplitGenerator(
-                name="query",
-                gen_kwargs={"path": os.path.join(subset_dir, "queries.jsonl"), "split": "query"},
-            ),
-            datasets.SplitGenerator(
-                name="corpus",
-                gen_kwargs={"path": os.path.join(subset_dir, "corpus.jsonl"), "split": "corpus"},
-            ),
-            datasets.SplitGenerator(
-                name="mixed_corpus",
-                gen_kwargs={"path": os.path.join(subset_dir, "mixed_corpus.jsonl"), "split": "mixed_corpus"},
-            ),
-            datasets.SplitGenerator(
-                name="qrel",
-                gen_kwargs={"path": os.path.join(subset_dir, "qrels", "qrels.tsv"), "split": "qrel"},
-            ),
+            datasets.SplitGenerator(name="query", gen_kwargs={"path": os.path.join(subset_dir, "queries.jsonl"), "split": "query"}),
+            datasets.SplitGenerator(name="corpus", gen_kwargs={"path": os.path.join(subset_dir, "corpus.jsonl"), "split": "corpus"}),
+            datasets.SplitGenerator(name="mixed_corpus", gen_kwargs={"path": os.path.join(subset_dir, "mixed_corpus.jsonl"), "split": "mixed_corpus"}),
+            datasets.SplitGenerator(name="qrel", gen_kwargs={"path": os.path.join(subset_dir, "qrels", "qrels.tsv"), "split": "qrel"}),
         ]
 
     def _generate_examples(self, path, split):
@@ -165,52 +144,27 @@ class MixBench(datasets.GeneratorBasedBuilder):
                     row = json.loads(line)
                     if split == "query":
                         yield idx, {
-                            "query_id": row.get("query_id", ""),
-                            "text": row.get("text", ""),
-                            "image": row.get("image", ""),
+                            "query_id": row["query_id"],
+                            "text": row["text"],
+                            "image": row["image"],
                         }
                     else:  # corpus or mixed_corpus
                         yield idx, {
-                            "corpus_id": row.get("corpus_id", ""),
-                            "text": row.get("text", ""),
-                            "image": row.get("image", ""),
+                            "corpus_id": row["corpus_id"],
+                            "text": row["text"],
+                            "image": row["image"],
                         }
 
     def _info(self):
-        split = self.config.name.lower()
+        # Provide all possible features but only used in relevant splits
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
             homepage=_HOMEPAGE,
-            features={
-                "query": datasets.Features({
-                    "query_id": datasets.Value("string"),
-                    "text": datasets.Value("string"),
-                    "image": datasets.Value("string"),
-                }),
-                "corpus": datasets.Features({
-                    "corpus_id": datasets.Value("string"),
-                    "text": datasets.Value("string"),
-                    "image": datasets.Value("string"),
-                }),
-                "mixed_corpus": datasets.Features({
-                    "corpus_id": datasets.Value("string"),
-                    "text": datasets.Value("string"),
-                    "image": datasets.Value("string"),
-                }),
-                "qrel": datasets.Features({
-                    "query_id": datasets.Value("string"),
-                    "corpus_id": datasets.Value("string"),
-                    "score": datasets.Value("int32"),
-                }),
-            }.get(self.split_name, datasets.Features({"placeholder": datasets.Value("string")})),
+            features=datasets.Features({
+                "query_id": datasets.Value("string"),
+                "corpus_id": datasets.Value("string"),
+                "text": datasets.Value("string"),
+                "image": datasets.Value("string"),
+                "score": datasets.Value("int32"),
+            })
         )
-
-    @property
-    def split_name(self):
-        # Dynamically infer split being loaded
-        import inspect
-        outer = inspect.stack()[2]
-        if "split" in outer.frame.f_locals:
-            return outer.frame.f_locals["split"]
-        return None
-