The activation values are a bit tricky in this use case.
As you can see in this line of code, the Bottleneck module uses self.relu directly after the batch norm layers.
Since self.relu is defined as an inplace operation, the output of the batchnorm layers will be manipulated inplace, which is why you actually see the “output” of the self.relu layer.