decoupled_light_FGEM_safe

models/common.py

@@ -1121,3 +1121,36 @@ class Classify(nn.Module):
         if isinstance(x, list):
             x = torch.cat(x, 1)
         return self.linear(self.drop(self.pool(self.conv(x)).flatten(1)))
+
+
+# 新增
+class FGEMSafe(nn.Module):
+    """Safer lightweight fine-grained enhancement block for cls branch."""
+    def __init__(self, c1, c_mid=None, residual_scale=0.1):
+        super().__init__()
+        c_mid = c_mid or max(c1 // 2, 32)
+        self.residual_scale = residual_scale
+
+        # 1x1 reduce
+        self.reduce = Conv(c1, c_mid, 1, 1)
+
+        # depthwise 3x3 local modeling
+        self.dw = nn.Sequential(
+            nn.Conv2d(c_mid, c_mid, kernel_size=3, stride=1, padding=1, groups=c_mid, bias=False),
+            nn.BatchNorm2d(c_mid),
+            nn.SiLU()
+        )
+
+        # pointwise fusion
+        self.pw = Conv(c_mid, c_mid, 1, 1)
+
+        # 1x1 expand
+        self.expand = Conv(c_mid, c1, 1, 1)
+
+    def forward(self, x):
+        identity = x
+        y = self.reduce(x)
+        y = self.dw(y)
+        y = self.pw(y)
+        y = self.expand(y)
+        return identity + self.residual_scale * y