Datasets:
Tasks:
Text Ranking
Formats:
json
Sub-tasks:
document-retrieval
Languages:
English
Size:
1K - 10K
License:
File size: 3,439 Bytes
e459613 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 |
import os
import json
import csv
import datasets
_DESCRIPTION = """
MixBench is a benchmark for mixed-modality retrieval across text, image, and image+text corpora.
"""
_HOMEPAGE = "https://huggingface.co/datasets/andy0207/mixbench"
class MixBench(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
datasets.BuilderConfig(name=name, version=datasets.Version("1.0.0"), description=f"MixBench subset: {name}")
for name in ["MSCOCO", "Google_WIT", "VisualNews", "OVEN"]
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
homepage=_HOMEPAGE,
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"),
})
)
def _split_generators(self, dl_manager):
# 确保这个方法存在且正确实现
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 == "query":
with open(path, encoding="utf-8") as f:
for idx, line in enumerate(f):
item = json.loads(line)
yield idx, {
"query_id": item.get("query_id", ""),
"corpus_id": "",
"text": item.get("text", ""),
"image": item.get("image", ""),
"score": 0,
}
elif split == "corpus" or split == "mixed_corpus":
with open(path, encoding="utf-8") as f:
for idx, line in enumerate(f):
item = json.loads(line)
yield idx, {
"query_id": "",
"corpus_id": item.get("corpus_id", ""),
"text": item.get("text", ""),
"image": item.get("image", ""),
"score": 0,
}
elif split == "qrel":
with open(path, encoding="utf-8") as f:
reader = csv.DictReader(f, delimiter="\t")
for idx, row in enumerate(reader):
yield idx, {
"query_id": row["query_id"],
"corpus_id": row["corpus_id"],
"text": "",
"image": "",
"score": int(row["score"])
} |