be wrapped with FSDP and "param_init_fn" is not specified, we
        assume your module properly implements a "reset_parameters()"
        and will throw errors if not. Note that additionally, we offer
        support for modules initialized with torchdistX's
        (https://github.com/pytorch/torchdistX) "deferred_init" API.
        In this case, deferred modules would be initialized by a
        default initialization function that calls torchdistX's
        "materialize_module", or the passed in "param_init_fn", if it
        is not "None". The same "Callable" is applied to initialize
        all meta modules. Note that this initialization function is
        applied before doing any FSDP sharding logic.
    Example:

       >>> module = MyModule(device="meta")
       >>> def my_init_fn(module):
       >>>     # responsible for initializing a module, such as with reset_parameters
       >>>     ...
