from __future__ import annotations

import json
import random
from contextlib import nullcontext
from pathlib import Path
from typing import Any

import numpy as np
import torch


def seed_everything(seed: int) -> None:
    random.seed(seed)
    np.random.seed(seed)
    torch.manual_seed(seed)
    if torch.cuda.is_available():
        torch.cuda.manual_seed_all(seed)


def get_device(prefer_mps: bool = True, requested_device: str = "auto") -> torch.device:
    if requested_device != "auto":
        if requested_device == "cuda":
            if not torch.cuda.is_available():
                raise RuntimeError("CUDA was requested but is not available.")
            return torch.device("cuda")
        if requested_device == "mps":
            if not torch.backends.mps.is_available():
                raise RuntimeError("MPS was requested but is not available.")
            return torch.device("mps")
        if requested_device == "cpu":
            return torch.device("cpu")
        raise ValueError(f"Unsupported device: {requested_device}")
    if torch.cuda.is_available():
        return torch.device("cuda")
    if prefer_mps and torch.backends.mps.is_available():
        return torch.device("mps")
    return torch.device("cpu")


def get_autocast(device: torch.device, enabled: bool):
    if not enabled:
        return nullcontext()
    if device.type == "cuda":
        return torch.autocast(device_type="cuda", dtype=torch.float16)
    return nullcontext()


def dump_json(path: str | Path, payload: dict[str, Any]) -> None:
    path = Path(path)
    path.parent.mkdir(parents=True, exist_ok=True)
    with path.open("w", encoding="utf-8") as handle:
        json.dump(payload, handle, indent=2)


def load_json(path: str | Path) -> dict[str, Any]:
    with Path(path).open("r", encoding="utf-8") as handle:
        return json.load(handle)