fix recursive call of DLA (#6771)

ppdet/modeling/necks/centernet_fpn.py

@@ -164,11 +164,11 @@ class IDAUp(nn.Layer):
         for i in range(start_level + 1, end_level):
             upsample = getattr(self, 'up_' + str(i - start_level))
             project = getattr(self, 'proj_' + str(i - start_level))
-
             inputs[i] = project(inputs[i])
             inputs[i] = upsample(inputs[i])
             node = getattr(self, 'node_' + str(i - start_level))
             inputs[i] = node(paddle.add(inputs[i], inputs[i - 1]))
+        return inputs
 
 
 class DLAUp(nn.Layer):
@@ -197,8 +197,8 @@ class DLAUp(nn.Layer):
         out = [inputs[-1]]  # start with 32
         for i in range(len(inputs) - self.start_level - 1):
             ida = getattr(self, 'ida_{}'.format(i))
-            ida(inputs, len(inputs) - i - 2, len(inputs))
-            out.insert(0, inputs[-1])
+            outputs = ida(inputs, len(inputs) - i - 2, len(inputs))
+            out.insert(0, outputs[-1])
         return out
 
 
@@ -259,7 +259,9 @@ class CenterNetDLAFPN(nn.Layer):
 
     def forward(self, body_feats):
 
-        dla_up_feats = self.dla_up(body_feats)
+        inputs = [body_feats[i] for i in range(len(body_feats))]
+
+        dla_up_feats = self.dla_up(inputs)
 
         ida_up_feats = []
         for i in range(self.last_level - self.first_level):
@@ -271,7 +273,11 @@ class CenterNetDLAFPN(nn.Layer):
         if self.with_sge:
             feat = self.sge_attention(feat)
         if self.down_ratio != 4:
-            feat = F.interpolate(feat, scale_factor=self.down_ratio // 4, mode="bilinear", align_corners=True)
+            feat = F.interpolate(
+                feat,
+                scale_factor=self.down_ratio // 4,
+                mode="bilinear",
+                align_corners=True)
         return feat
 
     @property