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()