| import torch | |
| from torch import nn | |
| class LayerScale(nn.Module): | |
| """ LayerScale on tensors with channels in last-dim. | |
| """ | |
| def __init__( | |
| self, | |
| dim: int, | |
| init_values: float = 1e-5, | |
| inplace: bool = False, | |
| ) -> None: | |
| super().__init__() | |
| self.inplace = inplace | |
| self.gamma = nn.Parameter(init_values * torch.ones(dim)) | |
| def forward(self, x: torch.Tensor) -> torch.Tensor: | |
| return x.mul_(self.gamma) if self.inplace else x * self.gamma | |
| class LayerScale2d(nn.Module): | |
| """ LayerScale for tensors with torch 2D NCHW layout. | |
| """ | |
| def __init__( | |
| self, | |
| dim: int, | |
| init_values: float = 1e-5, | |
| inplace: bool = False, | |
| ): | |
| super().__init__() | |
| self.inplace = inplace | |
| self.gamma = nn.Parameter(init_values * torch.ones(dim)) | |
| def forward(self, x): | |
| gamma = self.gamma.view(1, -1, 1, 1) | |
| return x.mul_(gamma) if self.inplace else x * gamma | |