add FeatureConcat() module

utils/layers.py

@@ -3,6 +3,16 @@ import torch.nn.functional as F
 from utils.utils import *
 
 
+class FeatureConcat(nn.Module):
+    def __init__(self, layers):
+        super(FeatureConcat, self).__init__()
+        self.layers = layers  # layer indices
+        self.multiple = len(layers) > 1  # multiple layers flag
+
+    def forward(self, x, outputs):
+        return torch.cat([outputs[i] for i in self.layers], 1) if self.multiple else outputs[self.layers[0]]
+
+
 class WeightedFeatureFusion(nn.Module):  # weighted sum of 2 or more layers https://arxiv.org/abs/1911.09070
     def __init__(self, layers, weight=False):
         super(WeightedFeatureFusion, self).__init__()