When this submodule is used, it will be compiled
             self.linear = torch.nn.Linear(N, M)

         def forward(self, input):
             output = self.weight.mv(input)

             # This calls the `forward` method of the `nn.Linear` module, which will
             # cause the `self.linear` submodule to be compiled to a `ScriptModule` here
             output = self.linear(output)
             return output

     scripted_module = torch.jit.script(MyModule(2, 3))

  Example (scripting a module with traced submodules):

     import torch
     import torch.nn as nn
     import torch.nn.functional as F

     class MyModule(nn.Module):
         def __init__(self):
             super(MyModule, self).__init__()
             # torch.jit.trace produces a ScriptModule's conv1 and conv2
             self.conv1 = torch.jit.trace(nn.Conv2d(1, 20, 5), torch.rand(1, 1, 16, 16))
