Thanks for the code!
After removing the hard coded checkpoint paths, I get the same outputs for the model in eval mdoe:
net = RetinaNet(backbone='resnet34', num_classes=10, pretrained=False)
net.eval()
x = torch.randn(2, 3, 224, 224)
output1a, output1b = net(x)
output2a, output2b = net(x)

print((output1a==output2a).all())
> tensor(1, dtype=torch.uint8)
print((output1b==output2b).all())
> tensor(1, dtype=torch.uint8)