I have been following the mnist_parallel example (19540 4)for using the data_parallel call.  My module actually has nested modules, similar to how torchvision implemented GoogLeNet.  The inception layers are actually a separate module.  When I do this, the call to data_parallel crashes.  If I move the inception (can be seen here 2) layer out into the main module, then the sequential call fails with something similar to

weight of size [16, 96, 1, 1], expected input[128, 16, 15, 15] to have 96 channels, but got 16 channels instead

The question is, how do I properly implement nested modules in libtorch when I am going to be making the call to data_parallel?  I apologize for not posting the code for my net, its a bit big and ugly, but it started life very close to the torchvision GoogLeNet implementation.