Your Bottleneck layer defines:
# pw-linear
nn.Conv2d(inp * expansion, oup, 1, 1, 0, bias=False),
nn.BatchNorm2d(oup),

where at the oup is set to 64, which creates the last conv and batchnorm layer in the first Bottleneck as:
(6): Conv2d(128, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
(7): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)