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/lora/conftest.py

@@ -0,0 +1,306 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import tempfile
+from collections import OrderedDict
+from unittest.mock import MagicMock
+
+import pytest
+import torch
+import torch.nn as nn
+from huggingface_hub import snapshot_download
+
+from vllm.distributed import (
+    cleanup_dist_env_and_memory,
+    init_distributed_environment,
+    initialize_model_parallel,
+)
+from vllm.model_executor.layers.linear import (
+    ColumnParallelLinear,
+    MergedColumnParallelLinear,
+    RowParallelLinear,
+)
+from vllm.model_executor.layers.logits_processor import LogitsProcessor
+from vllm.model_executor.layers.vocab_parallel_embedding import ParallelLMHead
+from vllm.model_executor.models.interfaces import SupportsLoRA
+from vllm.platforms import current_platform
+
+
+@pytest.fixture()
+def should_do_global_cleanup_after_test(request) -> bool:
+    """Allow subdirectories to skip global cleanup by overriding this fixture.
+    This can provide a ~10x speedup for non-GPU unit tests since they don't need
+    to initialize torch.
+    """
+
+    return not request.node.get_closest_marker("skip_global_cleanup")
+
+
+@pytest.fixture(autouse=True)
+def cleanup_fixture(should_do_global_cleanup_after_test: bool):
+    yield
+    if should_do_global_cleanup_after_test:
+        cleanup_dist_env_and_memory(shutdown_ray=True)
+
+
+@pytest.fixture
+def dist_init():
+    from tests.utils import ensure_current_vllm_config
+
+    temp_file = tempfile.mkstemp()[1]
+
+    backend = "nccl"
+    if current_platform.is_cpu() or current_platform.is_tpu():
+        backend = "gloo"
+
+    with ensure_current_vllm_config():
+        init_distributed_environment(
+            world_size=1,
+            rank=0,
+            distributed_init_method=f"file://{temp_file}",
+            local_rank=0,
+            backend=backend,
+        )
+        initialize_model_parallel(1, 1)
+        yield
+    cleanup_dist_env_and_memory(shutdown_ray=True)
+
+
+@pytest.fixture
+def dist_init_torch_only():
+    if torch.distributed.is_initialized():
+        return
+    backend = "nccl"
+    if current_platform.is_cpu():
+        backend = "gloo"
+
+    temp_file = tempfile.mkstemp()[1]
+    torch.distributed.init_process_group(
+        world_size=1, rank=0, init_method=f"file://{temp_file}", backend=backend
+    )
+
+
+class DummyLoRAModel(nn.Sequential, SupportsLoRA):
+    pass
+
+
+@pytest.fixture
+def dummy_model(default_vllm_config) -> nn.Module:
+    model = DummyLoRAModel(
+        OrderedDict(
+            [
+                ("dense1", ColumnParallelLinear(764, 100)),
+                ("dense2", RowParallelLinear(100, 50)),
+                (
+                    "layer1",
+                    nn.Sequential(
+                        OrderedDict(
+                            [
+                                ("dense1", ColumnParallelLinear(100, 10)),
+                                ("dense2", RowParallelLinear(10, 50)),
+                            ]
+                        )
+                    ),
+                ),
+                ("act2", nn.ReLU()),
+                ("output", ColumnParallelLinear(50, 10)),
+                ("outact", nn.Sigmoid()),
+                # Special handling for lm_head & sampler
+                ("lm_head", ParallelLMHead(32064, 10)),
+                ("logits_processor", LogitsProcessor(32064)),
+            ]
+        )
+    )
+    model.config = MagicMock()
+    model.embedding_modules = {"lm_head": "lm_head"}
+    model.unpadded_vocab_size = 32064
+    return model
+
+
+@pytest.fixture
+def dummy_model_gate_up(default_vllm_config) -> nn.Module:
+    model = DummyLoRAModel(
+        OrderedDict(
+            [
+                ("dense1", ColumnParallelLinear(764, 100)),
+                ("dense2", RowParallelLinear(100, 50)),
+                (
+                    "layer1",
+                    nn.Sequential(
+                        OrderedDict(
+                            [
+                                ("dense1", ColumnParallelLinear(100, 10)),
+                                ("dense2", RowParallelLinear(10, 50)),
+                            ]
+                        )
+                    ),
+                ),
+                ("act2", nn.ReLU()),
+                ("gate_up_proj", MergedColumnParallelLinear(50, [5, 5])),
+                ("outact", nn.Sigmoid()),
+                # Special handling for lm_head & sampler
+                ("lm_head", ParallelLMHead(32064, 10)),
+                ("logits_processor", LogitsProcessor(32064)),
+            ]
+        )
+    )
+    model.config = MagicMock()
+    model.packed_modules_mapping = {
+        "gate_up_proj": [
+            "gate_proj",
+            "up_proj",
+        ],
+    }
+    model.embedding_modules = {"lm_head": "lm_head"}
+    model.unpadded_vocab_size = 32064
+
+    return model
+
+
+@pytest.fixture(scope="session")
+def mixtral_lora_files():
+    # Note: this module has incorrect adapter_config.json to test
+    # https://github.com/vllm-project/vllm/pull/5909/files.
+    return snapshot_download(repo_id="SangBinCho/mixtral-lora")
+
+
+@pytest.fixture(scope="session")
+def chatglm3_lora_files():
+    return snapshot_download(repo_id="jeeejeee/chatglm3-text2sql-spider")
+
+
+@pytest.fixture(scope="session")
+def baichuan_lora_files():
+    return snapshot_download(repo_id="jeeejeee/baichuan7b-text2sql-spider")
+
+
+@pytest.fixture(scope="session")
+def baichuan_zero_lora_files():
+    # all the lora_B weights are initialized to zero.
+    return snapshot_download(repo_id="jeeejeee/baichuan7b-zero-init")
+
+
+@pytest.fixture(scope="session")
+def baichuan_regex_lora_files():
+    return snapshot_download(repo_id="jeeejeee/baichuan-7b-lora-zero-regex")
+
+
+@pytest.fixture(scope="session")
+def ilama_lora_files():
+    return snapshot_download(repo_id="jeeejeee/ilama-text2sql-spider")
+
+
+@pytest.fixture(scope="session")
+def minicpmv_lora_files():
+    return snapshot_download(repo_id="jeeejeee/minicpmv25-lora-pokemon")
+
+
+@pytest.fixture(scope="session")
+def qwen2vl_lora_files():
+    return snapshot_download(repo_id="jeeejeee/qwen2-vl-lora-pokemon")
+
+
+@pytest.fixture(scope="session")
+def qwen25vl_base_huggingface_id():
+    # used as a base model for testing with qwen25vl lora adapter
+    return "Qwen/Qwen2.5-VL-3B-Instruct"
+
+
+@pytest.fixture(scope="session")
+def qwen25vl_lora_files():
+    return snapshot_download(repo_id="jeeejeee/qwen25-vl-lora-pokemon")
+
+
+@pytest.fixture(scope="session")
+def qwen2vl_language_lora_files():
+    return snapshot_download(repo_id="prashanth058/qwen2vl-flickr-lora-language")
+
+
+@pytest.fixture(scope="session")
+def qwen2vl_vision_tower_connector_lora_files():
+    return snapshot_download(repo_id="prashanth058/qwen2vl-flickr-lora-tower-connector")
+
+
+@pytest.fixture(scope="session")
+def qwen2vl_vision_tower_lora_files():
+    return snapshot_download(repo_id="prashanth058/qwen2vl-flickr-lora-tower")
+
+
+@pytest.fixture(scope="session")
+def qwen25vl_vision_lora_files():
+    return snapshot_download(repo_id="EpochEcho/qwen2.5-3b-vl-lora-vision-connector")
+
+
+@pytest.fixture(scope="session")
+def qwen3vl_vision_lora_files():
+    return snapshot_download(repo_id="EpochEcho/qwen3-4b-vl-lora-vision-connector")
+
+
+@pytest.fixture(scope="session")
+def qwen3_meowing_lora_files():
+    """Download Qwen3 Meow LoRA files once per test session."""
+    return snapshot_download(repo_id="Jackmin108/Qwen3-0.6B-Meow-LoRA")
+
+
+@pytest.fixture(scope="session")
+def qwen3_woofing_lora_files():
+    """Download Qwen3 Woof LoRA files once per test session."""
+    return snapshot_download(repo_id="Jackmin108/Qwen3-0.6B-Woof-LoRA")
+
+
+@pytest.fixture(scope="session")
+def tinyllama_lora_files():
+    return snapshot_download(repo_id="jashing/tinyllama-colorist-lora")
+
+
+@pytest.fixture(scope="session")
+def deepseekv2_lora_files():
+    return snapshot_download(repo_id="wuchen01/DeepSeek-V2-Lite-Chat-All-LoRA")
+
+
+@pytest.fixture(scope="session")
+def gptoss20b_lora_files():
+    return snapshot_download(repo_id="jeeejeee/gpt-oss-20b-lora-adapter-text2sql")
+
+
+@pytest.fixture(scope="session")
+def qwen3moe_lora_files():
+    return snapshot_download(repo_id="jeeejeee/qwen3-moe-text2sql-spider")
+
+
+@pytest.fixture(scope="session")
+def olmoe_lora_files():
+    return snapshot_download(repo_id="jeeejeee/olmoe-instruct-text2sql-spider")
+
+
+@pytest.fixture(scope="session")
+def qwen3_lora_files():
+    return snapshot_download(repo_id="charent/self_cognition_Alice")
+
+
+@pytest.fixture(scope="session")
+def llama32_lora_huggingface_id():
+    # huggingface repo id is used to test lora runtime downloading.
+    return "jeeejeee/llama32-3b-text2sql-spider"
+
+
+@pytest.fixture(scope="session")
+def llama32_lora_files(llama32_lora_huggingface_id):
+    return snapshot_download(repo_id=llama32_lora_huggingface_id)
+
+
+@pytest.fixture(scope="session")
+def whisper_lora_files():
+    return snapshot_download(repo_id="chengyili2005/whisper-small-mandarin-lora")
+
+
+@pytest.fixture
+def reset_default_device():
+    """
+    Some tests, such as `test_punica_ops.py`, explicitly set the
+    default device, which can affect subsequent tests. Adding this fixture
+    helps avoid this problem.
+    """
+    original_device = torch.get_default_device()
+    yield
+    torch.set_default_device(original_device)