import os.path as osp
from typing import Optional, Tuple

import torch

torch.ops.load_library(
    osp.join(osp.dirname(osp.abspath(__file__)), '_scatter.so'))


@torch.jit.script
def scatter_sum(src: torch.Tensor, index: torch.Tensor, dim: int = -1,
                out: Optional[torch.Tensor] = None,
                dim_size: Optional[int] = None) -> torch.Tensor:
    return torch.ops.torch_scatter.scatter_sum(src, index, dim, out, dim_size)


@torch.jit.script
def scatter_add(src: torch.Tensor, index: torch.Tensor, dim: int = -1,
                out: Optional[torch.Tensor] = None,
                dim_size: Optional[int] = None) -> torch.Tensor:
    return torch.ops.torch_scatter.scatter_sum(src, index, dim, out, dim_size)


@torch.jit.script
def scatter_mean(src: torch.Tensor, index: torch.Tensor, dim: int = -1,
                 out: Optional[torch.Tensor] = None,
                 dim_size: Optional[int] = None) -> torch.Tensor:
    return torch.ops.torch_scatter.scatter_mean(src, index, dim, out, dim_size)


@torch.jit.script
def scatter_min(src: torch.Tensor, index: torch.Tensor, dim: int = -1,
                out: Optional[torch.Tensor] = None,
                dim_size: Optional[int] = None
                ) -> Tuple[torch.Tensor, torch.Tensor]:
    return torch.ops.torch_scatter.scatter_min(src, index, dim, out, dim_size)


@torch.jit.script
def scatter_max(src: torch.Tensor, index: torch.Tensor, dim: int = -1,
                out: Optional[torch.Tensor] = None,
                dim_size: Optional[int] = None
                ) -> Tuple[torch.Tensor, torch.Tensor]:
    return torch.ops.torch_scatter.scatter_max(src, index, dim, out, dim_size)


@torch.jit.script
def scatter(src: torch.Tensor, index: torch.Tensor, dim: int = -1,
            out: Optional[torch.Tensor] = None, dim_size: Optional[int] = None,
            reduce: str = "sum") -> torch.Tensor:
    if reduce == 'sum' or reduce == 'add':
        return scatter_sum(src, index, dim, out, dim_size)
    elif reduce == 'mean':
        return scatter_mean(src, index, dim, out, dim_size)
    elif reduce == 'min':
        return scatter_min(src, index, dim, out, dim_size)[0]
    elif reduce == 'max':
        return scatter_max(src, index, dim, out, dim_size)[0]
    else:
        raise ValueError