New AGLU activation module (#14644)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

docs/en/reference/nn/modules/activation.md

@@ -0,0 +1,16 @@
+---
+description: Explore activation functions in Ultralytics, including the Unified activation function and other custom implementations for neural networks.
+keywords: ultralytics, activation functions, neural networks, Unified activation, AGLU, SiLU, ReLU, PyTorch, deep learning, custom activations
+---
+
+# Reference for `ultralytics/nn/modules/activation.py`
+
+!!! Note
+
+    This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/nn/modules/activation.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/nn/modules/activation.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/nn/modules/activation.py) 🛠️. Thank you 🙏!
+
+<br>
+
+## ::: ultralytics.nn.modules.activation.AGLU
+
+<br><br>

docs/mkdocs_github_authors.yaml

@@ -12,6 +12,7 @@
 48149018+zhixuwei@users.noreply.github.com: zhixuwei
 49699333+dependabot[bot]@users.noreply.github.com: dependabot
 52826299+Chayanonjackal@users.noreply.github.com: Chayanonjackal
+53246858+hasanghaffari93@users.noreply.github.com: hasanghaffari93
 61612323+Laughing-q@users.noreply.github.com: Laughing-q
 62214284+Burhan-Q@users.noreply.github.com: Burhan-Q
 68285002+Kayzwer@users.noreply.github.com: Kayzwer

mkdocs.yml

@@ -536,6 +536,7 @@ nav:
       - nn:
           - autobackend: reference/nn/autobackend.md
           - modules:
+              - activation: reference/nn/modules/activation.md
               - block: reference/nn/modules/block.md
               - conv: reference/nn/modules/conv.md
               - head: reference/nn/modules/head.md

ultralytics/nn/modules/activation.py

@@ -0,0 +1,22 @@
+# Ultralytics YOLO 🚀, AGPL-3.0 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)
+        y = torch.exp((1 / lam) * self.act((self.kappa * x) - torch.log(lam)))
+        return y  # for AGLU simply return y * input