[SAC] Refactor activation checkpointing to use centralized policy-based approach

[mori360]

The previous activation checkpointing implementation had each model define its own _op_sac_save_list in its respective parallelize.py file. Manually maintaining the op list risks missing standard compute-intensive ops that PyTorch's get_default_op_list() already provides.

This PR:

1. Centralize ops in activation_checkpoint.py via default_activation_checkpoint_policy()
2. Use get_default_op_list() from torch._functorch.partitioners as the foundation
3. Split ops list into compute and communicate case, and extend them with the current ops used in torchtitan but not included in get_default_op_list
4. Specially wrap policy by ac_config.per_op_sac_force_recompute_mm_shapes_by_fqns