method. Attributes modified in preserved methods will also be
        preserved.
  * **optimize_numerics** (*bool*) -- If "True", a set of
    optimization passes will be run that does not strictly
    preserve numerics. Full details of optimization can be found
    at *torch.jit.run_frozen_optimizations*.

Returns:
      Frozen "ScriptModule".
Example (Freezing a simple module with a Parameter):
      def forward(self, input):
          output = self.weight.mm(input)
          output = self.linear(output)
          return output

  scripted_module = torch.jit.script(MyModule(2, 3).eval())
  frozen_module = torch.jit.freeze(scripted_module)
  # parameters have been removed and inlined into the Graph as constants
  assert len(list(frozen_module.named_parameters())) == 0
  # See the compiled graph as Python code
  print(frozen_module.code)

Example (Freezing a module with preserved attributes)
      def forward(self, input):
