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from __future__ import annotations
import argparse
from collections import Counter
import numpy as np
from datasets import load_dataset
from .common import DATASET_NAME, DATASET_SPLIT, write_json
def parse_args() -> argparse.Namespace:
p = argparse.ArgumentParser()
p.add_argument("--output", default="artifacts/manifest.json")
p.add_argument("--dataset", default=DATASET_NAME)
p.add_argument("--seed", type=int, default=20260728)
p.add_argument("--unpaired-per-modality", type=int, default=12_000)
p.add_argument("--paired-train", type=int, default=12_000)
p.add_argument("--max-eval", type=int, default=1_000)
return p.parse_args()
def main() -> None:
args = parse_args()
dataset = load_dataset(args.dataset, split=DATASET_SPLIT)
by_split: dict[str, list[int]] = {}
for i, split in enumerate(dataset["split"]):
by_split.setdefault(split, []).append(i)
counts = Counter(dataset["split"])
print(f"Internal Flickr splits: {dict(counts)}")
train = np.asarray(by_split["train"], dtype=np.int64)
rng = np.random.default_rng(args.seed)
rng.shuffle(train)
n_unpaired = min(args.unpaired_per_modality, len(train) // 2)
vision_only = train[:n_unpaired]
text_only = train[n_unpaired : 2 * n_unpaired]
assert not set(vision_only.tolist()) & set(text_only.tolist())
paired_n = min(args.paired_train, len(train))
paired_train = train[:paired_n]
val_key = "val" if "val" in by_split else "validation"
val = np.asarray(by_split[val_key], dtype=np.int64)[: args.max_eval]
test = np.asarray(by_split["test"], dtype=np.int64)[: args.max_eval]
all_rows = sorted(
set(vision_only.tolist())
| set(text_only.tolist())
| set(paired_train.tolist())
| set(val.tolist())
| set(test.tolist())
)
manifest = {
"dataset": args.dataset,
"dataset_split": DATASET_SPLIT,
"seed": args.seed,
"vision_only_train": vision_only.tolist(),
"text_only_train": text_only.tolist(),
"paired_train": paired_train.tolist(),
"val": val.tolist(),
"test": test.tolist(),
"all_rows": all_rows,
"protocol": (
"vision_only_train and text_only_train contain disjoint image IDs; "
"val/test pairs are held out from all bridge training"
),
}
write_json(args.output, manifest)
print(
f"Wrote {args.output}: unpaired={n_unpaired}+{n_unpaired}, "
f"paired_upper_bound={paired_n}, val={len(val)}, test={len(test)}, "
f"features={len(all_rows)} rows"
)
if __name__ == "__main__":
main()
|
