[Intel][XPU][KVCanary] Enable KV Canary on Intel XPU (#33520)

Co-authored-by: Claude Opus 5 <noreply@anthropic.com>

test/manual/kv_canary/test_xpu_kv_canary_pp.py

@@ -0,0 +1,36 @@
+"""KV-canary end-to-end on Intel XPU with pipeline parallelism.
+
+``--pp 2`` routes the run through ``Qwen3ForCausalLM.set_embed_and_head`` (mha mode
+is Qwen/Qwen3-0.6B), the embedding/head handoff that syncs and releases the device
+cache. Needs two XPU cards, so it is manual until a 2-card lane is confirmed.
+"""
+
+from __future__ import annotations
+
+import unittest
+
+from sglang.srt.kv_canary.config import CanaryMode
+from sglang.test.kv_canary.e2e_base import CanaryE2EBase
+
+
+class TestXPUCanaryPipelineParallel(CanaryE2EBase):
+    """Clean canary run across a pipeline-parallel XPU pair."""
+
+    model_mode = "mha"
+    kv_canary_mode = CanaryMode.LOG
+    # --disable-cuda-graph is mandatory, not tuning: install_canary refuses a captured decode
+    # on a device that routes to the torch reference (host work and D2H, so replay checks nothing).
+    extra_server_args = ("--device", "xpu", "--disable-cuda-graph", "--pp", "2")
+    # The torch reference folds the chain slot-by-slot on the host, so the workload is much
+    # smaller than the CUDA-tuned defaults on the shared base.
+    default_parallel_n = 2
+    default_max_new_tokens = 32
+    default_request_timeout = 120.0
+
+    def test_no_violation(self) -> None:
+        self.send_parallel_requests()
+        self.assert_no_violation(wait_seconds=2.0)
+
+
+if __name__ == "__main__":
+    unittest.main()