Add vLLM v0.18.1 source tree with KV transfer abort fix

third_party/vllm/ now tracked in git for direct patch management.
Based on vLLM v0.18.1 release with one patch applied:

  vllm/v1/core/sched/scheduler.py:
    Replace fatal assert with graceful skip when KV transfer callback
    arrives for an already-aborted request during PD disaggregated serving.

Future vLLM modifications should be made directly in third_party/vllm/
and committed normally. The patches/ directory is kept as documentation
of what changed from upstream.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

third_party/vllm/tests/kernels/quantization/test_gptq.py

@@ -0,0 +1,35 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import torch
+
+from tests.kernels.utils import opcheck
+from vllm import _custom_ops as ops  # noqa: F401
+
+
+def test_gptq_shuffle_opcheck():
+    weight = torch.randint(
+        -2000000, 2000000, (1792, 4096), device="cuda", dtype=torch.int32
+    )
+    perm = torch.empty((0,), device="cuda", dtype=torch.int32)
+    bit = 4
+    opcheck(torch.ops._C.gptq_shuffle, (weight, perm, bit))
+
+
+def test_gptq_gemm_opcheck():
+    a = torch.rand((240, 4096), device="cuda", dtype=torch.float16)
+    weight = torch.randint(
+        -2000000, 2000000, (512, 6144), device="cuda", dtype=torch.int32
+    )
+    zeros = torch.zeros((32, 768), device="cuda", dtype=torch.int32)
+    scales = torch.rand((32, 6144), device="cuda", dtype=torch.float16)
+    idx = torch.empty((0,), device="cuda", dtype=torch.int32)
+    use_exllama = True
+    bit = 4
+    # Test both GPTQv1 and GPTQv2 format
+    opcheck(
+        torch.ops._C.gptq_gemm, (a, weight, zeros, scales, idx, use_exllama, True, bit)
+    )
+    opcheck(
+        torch.ops._C.gptq_gemm, (a, weight, zeros, scales, idx, use_exllama, False, bit)
+    )