Upload SimAM.py

models/SimAM.py

@@ -0,0 +1,29 @@
+import torch
+import torch.nn as nn
+
+
+class SimAM(torch.nn.Module):
+    def __init__(self, e_lambda=1e-4):
+        super(SimAM, self).__init__()
+
+        self.activaton = nn.Sigmoid()
+        self.e_lambda = e_lambda
+
+    def __repr__(self):
+        s = self.__class__.__name__ + '('
+        s += ('lambda=%f)' % self.e_lambda)
+        return s
+
+    @staticmethod
+    def get_module_name():
+        return "simam"
+
+    def forward(self, x):
+        b, c, h, w = x.size()
+
+        n = w * h - 1
+
+        x_minus_mu_square = (x - x.mean(dim=[2, 3], keepdim=True)).pow(2)
+        y = x_minus_mu_square / (4 * (x_minus_mu_square.sum(dim=[2, 3], keepdim=True) / n + self.e_lambda)) + 0.5
+
+        return x * self.activaton(y)