# Modified from: https://github.com/huggingface/pytorch-image-models/blob/main/timm/models/vision_transformer.py#L103-L110

from typing import Union

import torch

from torch import nn
from torch import Tensor


class LayerScale(nn.Module):
    def __init__(
        self,
        dim: int,
        init_values: Union[float, Tensor] = 1e-5,
        inplace: bool = False,
        device=None,
    ) -> None:
        super().__init__()
        self.inplace = inplace
        self.gamma = nn.Parameter(torch.empty(dim, device=device))
        self.init_values = init_values

    def reset_parameters(self):
        nn.init.constant_(self.gamma, self.init_values)

    def forward(self, x: Tensor) -> Tensor:
        return x.mul_(self.gamma) if self.inplace else x * self.gamma