Add files using upload-large-folder tool

MixBench25.py

@@ -1,17 +1,112 @@
+# import os
+# 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. \
+# 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):
+#     def __init__(self, name, **kwargs):
+#         if name not in _SUBSETS:
+#             raise ValueError(f"Unknown subset: {name}. Choose from {_SUBSETS}")
+#         super().__init__(name=name, version=datasets.Version("1.0.0"), **kwargs)
+
+
+# class MixBench(datasets.GeneratorBasedBuilder):
+#     BUILDER_CONFIGS = [MixBenchConfig(name=subset) for subset in _SUBSETS]
+
+#     def _info(self):
+#         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"),
+#         })
+#         return datasets.DatasetInfo(
+#             description=_DESCRIPTION,
+#             features=features,
+#             homepage=_HOMEPAGE,
+#         )
+
+#     def _split_generators(self, dl_manager):
+#         # download entire repo root and go to current subset folder
+#         # data_dir = dl_manager.download_and_extract(".")
+#         # subset_dir = os.path.join(data_dir, self.config.name)
+#         # repo_root = dl_manager.manual_dir or os.path.join(os.path.dirname(__file__), self.config.name)
+#         # subset_dir = os.path.join(repo_root, self.config.name)
+#         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"},
+#             ),
+#         ]
+
+#     def _generate_examples(self, path, split):
+#         if split == "qrel":
+#             # with open(path, encoding="utf-8") as f:
+#             #     for idx, line in enumerate(f):
+#             #         qid, did, score = line.strip().split()
+#             #         yield idx, {
+#             #             "query_id": qid,
+#             #             "corpus_id": did,
+#             #             "text": "",
+#             #             "image": "",
+#             #             "score": int(score),
+#             #         }
+#             with open(path, encoding="utf-8") as f:
+#                 reader = csv.DictReader(f, delimiter="\t")  # 使用 DictReader 读取有表头的 tsv
+#                 for idx, row in enumerate(reader):
+#                     yield idx, {
+#                         "query_id": row["query_id"],
+#                         "corpus_id": row["corpus_id"],
+#                         "score": int(row["score"]),
+#                     }
+#         else:
+#             with open(path, encoding="utf-8") as f:
+#                 for idx, line in enumerate(f):
+#                     row = json.loads(line)
+#                     yield idx, {
+#                         "query_id": row.get("query_id", ""),
+#                         "corpus_id": row.get("corpus_id", ""),
+#                         "text": row.get("text", ""),
+#                         "image": row.get("image", ""),
+#                         "score": 0,
+#                     }
+
 import os
 import json
 import datasets
-import csv 
+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. \
 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):
@@ -20,30 +115,20 @@ class MixBenchConfig(datasets.BuilderConfig):
             raise ValueError(f"Unknown subset: {name}. Choose from {_SUBSETS}")
         super().__init__(name=name, version=datasets.Version("1.0.0"), **kwargs)
 
-
 class MixBench(datasets.GeneratorBasedBuilder):
     BUILDER_CONFIGS = [MixBenchConfig(name=subset) for subset in _SUBSETS]
 
     def _info(self):
-        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"),
-        })
+        # This will be overwritten per split below
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
-            features=features,
+            features=datasets.Features({
+                "placeholder": datasets.Value("string")
+            }),
             homepage=_HOMEPAGE,
         )
 
     def _split_generators(self, dl_manager):
-        # download entire repo root and go to current subset folder
-        # data_dir = dl_manager.download_and_extract(".")
-        # subset_dir = os.path.join(data_dir, self.config.name)
-        # repo_root = dl_manager.manual_dir or os.path.join(os.path.dirname(__file__), self.config.name)
-        # subset_dir = os.path.join(repo_root, self.config.name)
         subset_dir = os.path.join(dl_manager.manual_dir or dl_manager._base_path, self.config.name)
         return [
             datasets.SplitGenerator(
@@ -66,18 +151,8 @@ class MixBench(datasets.GeneratorBasedBuilder):
 
     def _generate_examples(self, path, split):
         if split == "qrel":
-            # with open(path, encoding="utf-8") as f:
-            #     for idx, line in enumerate(f):
-            #         qid, did, score = line.strip().split()
-            #         yield idx, {
-            #             "query_id": qid,
-            #             "corpus_id": did,
-            #             "text": "",
-            #             "image": "",
-            #             "score": int(score),
-            #         }
             with open(path, encoding="utf-8") as f:
-                reader = csv.DictReader(f, delimiter="\t")  # 使用 DictReader 读取有表头的 tsv
+                reader = csv.DictReader(f, delimiter="\t")
                 for idx, row in enumerate(reader):
                     yield idx, {
                         "query_id": row["query_id"],
@@ -88,10 +163,54 @@ class MixBench(datasets.GeneratorBasedBuilder):
             with open(path, encoding="utf-8") as f:
                 for idx, line in enumerate(f):
                     row = json.loads(line)
-                    yield idx, {
-                        "query_id": row.get("query_id", ""),
-                        "corpus_id": row.get("corpus_id", ""),
-                        "text": row.get("text", ""),
-                        "image": row.get("image", ""),
-                        "score": 0,
-                    }
+                    if split == "query":
+                        yield idx, {
+                            "query_id": row.get("query_id", ""),
+                            "text": row.get("text", ""),
+                            "image": row.get("image", ""),
+                        }
+                    else:  # corpus or mixed_corpus
+                        yield idx, {
+                            "corpus_id": row.get("corpus_id", ""),
+                            "text": row.get("text", ""),
+                            "image": row.get("image", ""),
+                        }
+
+    def _info(self):
+        split = self.config.name.lower()
+        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")})),
+        )
+
+    @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
+