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- # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
- """Activation modules."""
- import torch
- import torch.nn as nn
- class AGLU(nn.Module):
- """Unified activation function module from https://github.com/kostas1515/AGLU."""
- def __init__(self, device=None, dtype=None) -> None:
- """Initialize the Unified activation function."""
- super().__init__()
- self.act = nn.Softplus(beta=-1.0)
- self.lambd = nn.Parameter(nn.init.uniform_(torch.empty(1, device=device, dtype=dtype))) # lambda parameter
- self.kappa = nn.Parameter(nn.init.uniform_(torch.empty(1, device=device, dtype=dtype))) # kappa parameter
- def forward(self, x: torch.Tensor) -> torch.Tensor:
- """Compute the forward pass of the Unified activation function."""
- lam = torch.clamp(self.lambd, min=0.0001)
- return torch.exp((1 / lam) * self.act((self.kappa * x) - torch.log(lam)))
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