serialize_torch_rng_state/deserialize_torch_rng_state only handled CPU
and CUDA generators. On MPS, resumed training was not bit-exact for any
stochastic op (dropout, ACT's CVAE noise) since the MPS generator's state
was never saved or restored. Mirrors the existing CUDA branch using
torch.mps.get_rng_state/set_rng_state (available since torch 2.11).
Note: get_rng_state()/set_rng_state() (used by seeded_context()) have the
same gap but are out of scope here — happy to follow up separately if
useful.
Co-authored-by: Sunny Dave <sunnydave@Sunnys-Mac-Studio.local>
Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>
sunnydave234