"list" of parameter groups or an iterable of parameters; if
           "None", then this method assumes the input was
           "model.parameters()". This argument is deprecated, and
           there is no need to pass it in anymore. (Default: "None")
     * **optim** (*Optional**[**torch.optim.Optimizer**]*) --
       Optimizer that will load the state dict returned by this
       method. This is the preferred argument to use over
       "optim_input". (Default: "None")

  Returns:
     The full optimizer state dict now remapped to flattened
     parameters instead of unflattened parameters and restricted
     to only include this rank's part of the optimizer state.

  Return type:
     Dict[str, Any]

static sharded_optim_state_dict(model, optim, group=None)
  The API is similar to "full_optim_state_dict()" but this API
  chunks all non-zero-dimension states to "ShardedTensor" to save
