…rward

The FSDP2 path in Accelerate currently passes the plugin's
`reshard_after_forward` (default `True`) uniformly to every
`fully_shard()` call, including the final call on the whole model that
creates the root unit. PyTorch's default (`None`) is smarter: it
resolves to `True` for non-root units and `False` for the root, which
avoids an unhideable pre-backward all-gather of the root's leftover
params (embeddings, final norm, lm_head) that would otherwise be
resharded and immediately re-gathered.

Stripping the kwarg from the root call lets PyTorch apply its heuristic.
Peak memory is unchanged on typical workloads (dominated by backward,
where the root is gathered in either case); we save one all-gather per
step on the root unit. This also matches torchtitan's default wrapping,
which similarly lets the root call fall back to `None`.