LazyModuleMixin
class torch.nn.modules.lazy.LazyModuleMixin(args, *kwargs)
A mixin for modules that lazily initialize parameters, also known
   as "lazy modules."
Modules that lazily initialize parameters, or "lazy modules",
   derive the shapes of their parameters from the first input(s) to
   their forward method. Until that first forward they contain
   "torch.nn.UninitializedParameter" s that should not be accessed or
   used, and afterward they contain regular "torch.nn.Parameter" s.
   Lazy modules are convenient since they don't require computing some
   module arguments, like the "in_features" argument of a typical
   "torch.nn.Linear".
After construction, networks with lazy modules should first be
   converted to the desired dtype and placed on the expected device.
   This is because lazy modules only perform shape inference so the
   usual dtype and device placement behavior applies. The lazy modules
   should then perform "dry runs" to initialize all the components in