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on
Zero
Running
on
Zero
import torch | |
import torch.nn as nn | |
from .layer_scale import LayerScale | |
class Addition(nn.Module): | |
def __init__( | |
self, | |
dim: int, | |
layer_scale: float | torch.Tensor = 1e-5, | |
) -> None: | |
super().__init__() | |
self.ls1 = LayerScale(dim, layer_scale) if layer_scale > 0.0 else nn.Identity() | |
def forward(self, x: torch.Tensor, y: torch.Tensor) -> torch.Tensor: | |
return x + self.ls1(y) | |
class Concat(nn.Module): | |
def __init__( | |
self, | |
dim: int, | |
layer_scale: float | torch.Tensor = 1e-5, | |
) -> None: | |
super().__init__() | |
self.project = nn.Linear(2 * dim, dim) | |
def forward(self, x: torch.Tensor, y: torch.Tensor) -> torch.Tensor: | |
return self.project(torch.cat([x, y], dim=-1)) | |