perf(wan): pad sequence to 128-lane multiple for self-attention (wan_seq_pad="lane") - #491

Last of four pieces split out of the Wan fast-inference optimizations PR
(the cross-attention Pallas kernel, token-sharded patch embedding and
shard-major Ulysses A2A are the three PRs below this one). The switch
defaults off in the Wan YAMLs and in wan_runtime_options; it is a plain
config key plumbed to WanModel through `attention_config_entries(config)`.

- Lane sequence padding (`wan_seq_pad="lane"`): `WanModel` pads the video tokens
  at the tail to a per-shard multiple of 128 (`75,600 -> 75,776` at
  720p/CP=4; on the Ulysses-ring path each ring segment is padded at its own
  tail) so the Ulysses reshapes are copy-free, pads the rotary embedding to
  match, and unpads the output and residual. The padding descriptor
  (`TokenPadding`) is planned via `plan_token_padding` and passed explicitly as
  a `token_padding` argument from `WanModel.__call__` ->
  `WanTransformerBlock.__call__` -> `FlaxWanAttention.__call__` ->
  `NNXAttentionOp.apply_attention` (no process/thread-global `ContextVar`).
- The custom `ulysses_custom*` / `ulysses_ring_custom*` kernels mask the pad
  keys by passing the real length as the ragged KV tail; the fixed-m norm
  reductions (`_compute_fixed_m_metadata` via `q_valid_len` on both the 1-D
  Ulysses path and the R == 1 ring path, `_ring_fixed_m_norms_pre_a2a` via
  `row_ok` for R > 1) exclude the pad Q/K/V rows so pad-token values cannot
  push a block onto the online-softmax path or move the `k_mean`. The ring's
  `ring_kv_seq_len` is always the real length.
- Fails closed on invalid static/mode configs: when `wan_seq_pad="lane"` is
  requested, incompatible static configurations (`per_token_t=True` TI2V
  timesteps, `use_svg_attention`, `use_memory_efficient_attention`, unsupported
  kernels, or `ulysses_shards` that do not divide the context axis) raise
  `ValueError` in `plan_token_padding` (checked at `WanModel.__init__` time as
  well as per call); `_resolve_token_padding` raises `ValueError` on any
  `TokenPadding.total_len != seq_len` mismatch; and attention kernels that
  cannot mask active token padding raise `NotImplementedError` via
  `_reject_token_padding`. Dynamic short (`S < flash_min_seq_length`) or
  indivisible (`S % context_shards != 0`) sequences log a warn-once message and
  run unpadded.
- `wan_block_benchmark.py` applies `plan_token_padding` to the benchmarked
  sequence length and passes `token_padding` explicitly to the block.
- `run_wan_fast_inference.sh`: the v6e and v7 profiles set `WAN_SEQ_PAD=lane`
  and `DEFAULT_ULYSSES_OUT_A2A=shard_major` (overridable); the generic profile
  keeps `off` and `flat`. LIBTPU: v6e disables
  `--xla_tpu_enable_ici_ag_pipelining` / `--xla_tpu_enable_ag_backward_pipelining`,
  v7 enables them and adds `--xla_tpu_enable_offloading_copy_to_sparsecore=false`
  and `BQ=4736`.

Performance, measured at the stack tip (Wan 2.2 T2V-A14B, 720p/81f/40 steps,
warm AOT, DVFS unpinned unless noted; CP=4, DP=2, launcher defaults):
  v6e-8:   denoise 124.5s - 125.0s, generate 126.6s - 127.5s
  tpu7x-8: denoise 104.9s, generate 107.8s (106.6s / 109.6s with fused RoPE off)
  tpu7x-8, DVFS pinned (`PIN_DVFS_P_STATE=true`):
           denoise  91.7s, generate  94.6s with the fused RoPE kernel on
           denoise  93.4s, generate  96.4s with the fused RoPE kernel off

Tests
- `wan_seq_pad_test.py` (19): padding plan, `ValueError` guards for invalid
  static/mode configs (including `per_token_t=True`) and `_resolve_token_padding`
  length mismatches, warn-once logging for short/indivisible sequences, pad-key
  masking for `ulysses_custom*` and `ulysses_ring_custom*` (U=2 x R=2, U=4 x R=1,
  and shard-major U=2 x R=2), fixed-m metadata ignoring pad query rows,
  `NotImplementedError` kernel guards, and end-to-end `WanModel` lane padding
  parity. All 19 tests run unconditionally in GitHub Actions (no
  `_SKIP_IN_GITHUB_ACTIONS`).
- `wan_runtime_options_test.py` (12): the new switch's YAML default and enum
  validation; `wan_seq_pad` is excluded from the `FlaxWanAttention` attribute
  check since `WanModel` consumes it.
- `end_to_end/tpu/run_wan_stack_tests.sh`: adds `wan_seq_pad_test.py`.