LazyLinear
class torch.nn.LazyLinear(out_features, bias=True, device=None, dtype=None)
A "torch.nn.Linear" module where in_features is inferred.
In this module, the weight and bias are of
   "torch.nn.UninitializedParameter" class. They will be initialized
   after the first call to "forward" is done and the module will
   become a regular "torch.nn.Linear" module. The "in_features"
   argument of the "Linear" is inferred from the "input.shape[-1]".
Check the "torch.nn.modules.lazy.LazyModuleMixin" for further
   documentation on lazy modules and their limitations.
Parameters:
      * out_features (int) -- size of each output sample
  * **bias** (*UninitializedParameter*) -- If set to "False", the
    layer will not learn an additive bias. Default: "True"

Variables:
      * weight (torch.nn.parameter.UninitializedParameter) --
        the learnable weights of the module of shape
        (\text{out_features}, \text{in_features}). The values are