Launches a real sgl server and exercises snapshot/compare/reset_tensors
plus an unknown-action negative case. Cases that mutate weights are
named to sort last so they cannot affect earlier cases sharing the
server.

Two new cases on top of the existing snapshot/compare/reset coverage:
  - update_weights_from_tensor with a divergent tensor must make compare
    fail and surface the param name in the error message
  - update_weights_from_tensor with byte-identical bytes (prime, snapshot,
    push the same bytes again) must keep compare passing

Qwen3-0.6B is smaller than the previous Llama-3.2-1B-Instruct default,
shortening server launch and pre-fill steps. The fused name
gate_up_proj.weight is sglang's actual on-disk parameter name (no HF
remapping in the path), so the test exercises the parameter unambiguously.

Matches sglang's inference-time nn.Parameter convention so that
_reset_tensors can do in-place copy_ without autograd rejecting it.
Fixes: RuntimeError 'a leaf Variable that requires grad is being used
in an in-place operation' from the reset / compare-after-reset cases.

_snapshot's '.detach().cpu()' is a no-op on a CPU tensor, so a CPU-only
fixture leaves the snapshot aliasing live storage and masks reset-then-
compare divergence. Putting the fixture on CUDA mirrors production
(model is always on the device) and forces _snapshot to produce a real
independent CPU copy.

Sending the fused gate_up_proj.weight name directly trips a name.replace
collision in sglang's stacked_params_mapping (gate_up_proj contains the
substring up_proj), producing the bogus key gate_gate_up_proj.weight and
crashing the model loader. Use the HF unfused alias up_proj.weight with
shape (intermediate_size, hidden_size); sglang rewrites it onto the
fused tensor with shard_id=1, writing only the up half — sufficient to
make compare detect a divergence.

Hoists the per-callsite skip-pattern lists in _reset_tensors and
_postprocess_tensors to a single module-level _NON_PERSISTENT_BUFFER_PATTERNS
tuple, accessed through _is_non_persistent_buffer_name. The unified set is
the union of the two prior lists: cos_sin_cache, inv_freq, freqs_cis,
_weight_fp32 — both callsites skip the same buffers now (previously
_reset_tensors was missing inv_freq and _postprocess_tensors was missing
freqs_cis).

Adds an action='checksum' route to WeightChecker.handle that returns a
dict produced by pydantic ChecksumInfo, containing per-tensor hashes
(hex of tensor_hash from mm_utils, GPU-accelerated via the existing
gpu_tensor_hash triton kernel) plus this rank's ParallelismInfo
(tp/dp/pp coordinates + global rank/size from torch.distributed).

The computation reuses _postprocess_tensors so fp8 weights are
dequantized to bf16 before hashing — two (qweight, scale) pairs that
dequant to the same bf16 produce the same checksum, matching the
semantics of the existing snapshot/compare path. Surrounded by
torch.cuda.synchronize() and timed via logger.info so callers can
observe per-rank duration.

handle() now returns Optional[Dict] — None for snapshot/reset/compare
and the dict payload for checksum.

Plumbs the optional dict returned by WeightChecker.handle from
model_runner up to the /weights_checker HTTP body:

- model_runner.check_weights now returns the underlying handle() value.
- CheckWeightsReqOutput gains an optional payload: Dict carrying one
  rank's ChecksumInfo dict.
- Scheduler's check_weights captures payload into the output.
- TokenizerManager.check_weights now returns
  (success, message, ranks) where ranks is the per-rank list collected
  naively in fan-out order (None when no rank produced a payload).
  FanOutCommunicator.merge_results is left untouched so the 11+ existing
  2-tuple callers keep working.
- /weights_checker HTTP body adds a top-level 'ranks' key when present,
  preserving the prior 'success'/'message' shape for the snapshot, reset,
  and compare actions.

Adds unit coverage for ChecksumInfo / ParallelismInfo /
_is_non_persistent_buffer_name / _hash_tensor / _compute_checksum:
hash stability and hex format, parallelism info reflection,
post-mutation hash drift, and round-trip through the strict pydantic
schema. Extends TestHandle to cover the new 'checksum' route.

The e2e test gains four cases on the shared engine: response shape,
two-call stability, hash drift after update_weights_from_tensor, and
absence of non-persistent buffer names in the checksum keys.