<Neck_2>change Concat to WeightedAdd

models/common.py

@@ -1121,3 +1121,23 @@ 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)))
+
+# 以下是我自己添加的
+class WeightedAdd(nn.Module):
+    """
+    Weighted feature fusion (BiFPN-style)
+    inputs: list of feature maps with same shape
+    """
+    def __init__(self, n_inputs, eps=1e-4):
+        super().__init__()
+        self.eps = eps
+        self.w = nn.Parameter(torch.ones(n_inputs), requires_grad=True)
+
+    def forward(self, x):
+        # x: list of tensors
+        w = torch.relu(self.w)
+        w = w / (w.sum() + self.eps)
+        out = 0
+        for i in range(len(x)):
+            out += w[i] * x[i]
+        return out