inception_v3 of vision 0.3.0 does not fit in DataParallel of torch 1.1.0

Environment:
Python 3.5
torch 1.1.0
torchvision 0.3.0

Reproducible example:
import torch
import torchvision
model = torchvision.models.inception_v3().cuda()
model = torch.nn.DataParallel(model, [0, 1])
x = torch.rand((8, 3, 299, 299)).cuda()
model.forward(x)

Error:

Traceback (most recent call last):
File "", line 1, in
File "env/lib/python3.5/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "env/lib/python3.5/site-packages/torch/nn/parallel/data_parallel.py", line 153, in forward
return self.gather(outputs, self.output_device)
File "/env/lib/python3.5/site-packages/torch/nn/parallel/data_parallel.py", line 165, in gather
return gather(outputs, output_device, dim=self.dim)
File "/env/lib/python3.5/site-packages/torch/nn/parallel/scatter_gather.py", line 67, in gather
return gather_map(outputs)
File "env/lib/python3.5/site-packages/torch/nn/parallel/scatter_gather.py", line 62, in gather_map
return type(out)(map(gather_map, zip(*outputs)))
TypeError: new() missing 1 required positional argument: 'aux_logits'

I guess the error occurs because the output of inception_v3 was changed from tuple to namedtuple.

Run the provided Python example with torch 1.1.0 and torchvision 0.3.0, then trace the DataParallel gather path shown in torch/nn/parallel/data_parallel.py and scatter_gather.py. Confirm the inception_v3 output shape involved in the failure and verify that DataParallel can complete the same forward pass without the aux_logits TypeError.