from __future__ import annotations

from collections.abc import Sequence
from typing import Any

import torch


def record_collate_fn(batch: Sequence[dict[str, Any]]) -> dict[str, Any]:
    if not batch:
        raise ValueError("Empty batch is not allowed.")

    collated: dict[str, Any] = {}
    keys = batch[0].keys()
    for key in keys:
        values = [sample[key] for sample in batch]
        first = values[0]

        if torch.is_tensor(first):
            shapes = [tuple(value.shape) for value in values]
            if all(shape == shapes[0] for shape in shapes):
                collated[key] = torch.stack(values, dim=0)
            else:
                collated[key] = values
            continue

        if first is None:
            collated[key] = values
            continue

        if isinstance(first, (str, int, float, dict)):
            collated[key] = values
            continue

        collated[key] = values

    return collated


__all__ = ["record_collate_fn"]