Positioning of RELU in FPA

In networks.py, lines 123 - 124:

```python
x3_upsample = self.relu(self.bn_upsample_3(self.conv_upsample_3(x3_2)))
x2_merge = self.relu(x2_2 + x3_upsample)
```

I know that x2_2 has a linear activation, why does x3_upsample have a relu, if you then relu it again after the addition? 