Merge tag 'v0.9.0' into v0.9.0-ori

requirements/hpu.txt

@@ -7,6 +7,6 @@ triton==3.1.0
 pandas
 numpy==1.26.4
 tabulate
-setuptools>=61
+setuptools>=77.0.3,<80.0.0
 setuptools-scm>=8
 vllm-hpu-extension @ git+https://github.com/HabanaAI/vllm-hpu-extension.git@f1f6624

requirements/neuron.txt

@@ -2,5 +2,8 @@
 -r common.txt
 
 # Dependencies for Neuron devices
+packaging>=24.2
+setuptools>=77.0.3,<80.0.0
 torch-neuronx >= 2.5.0
-neuronx-cc
+neuronx-cc>=2.0.0a0
+torchvision # Required for Llama3.2 multimodal image preprocessing

requirements/nightly_torch_test.txt

@@ -8,12 +8,10 @@ pytest-rerunfailures
 pytest-shard
 pytest-timeout
 
-
 librosa # required by audio tests in entrypoints/openai
 sentence-transformers
 numba == 0.61.2; python_version > '3.9'
 # testing utils
-awscli
 boto3
 botocore
 datasets
@@ -24,5 +22,20 @@ runai-model-streamer-s3==0.11.0
 tensorizer>=2.9.0
 lm-eval==0.4.8
 buildkite-test-collector==0.1.9
-
 lm-eval[api]==0.4.8 # required for model evaluation test
+
+# required for quantization test
+bitsandbytes>=0.45.3
+
+# required for minicpmo_26 test
+vector_quantize_pytorch
+vocos
+
+# required for Basic Models Test
+blobfile # required for kimi-vl test
+matplotlib # required for qwen-vl test
+
+# required for  Multi-Modal Models Test (Standard)
+num2words # required for smolvlm test
+pqdm
+timm # required for internvl test

requirements/rocm-build.txt

@@ -2,14 +2,14 @@
 -r common.txt
 
 --extra-index-url https://download.pytorch.org/whl/rocm6.2.4
-torch==2.6.0
-torchvision==0.21.0
-torchaudio==2.6.0
+torch==2.7.0
+torchvision==0.22.0
+torchaudio==2.7.0
 
 triton==3.2
 cmake>=3.26,<4
-packaging
-setuptools>=61
+packaging>=24.2
+setuptools>=77.0.3,<80.0.0
 setuptools-scm>=8
 wheel
 jinja2>=3.1.6

requirements/rocm-test.txt

+# Common dependencies
+-r common.txt
 
 # entrypoints test
 # librosa==0.10.2.post1 # required by audio tests in entrypoints/openai
@@ -20,4 +22,10 @@ decord==0.6.0
 #sentence-transformers # required by entrypoints/openai/test_score.py
 sentence-transformers==3.4.1
 
+# Basic Models Test
+matplotlib==3.10.3
+
+# Multi-Modal Models Test (Extended) 3
+blobfile==3.0.0
+
 

requirements/rocm.txt

@@ -5,11 +5,10 @@ numba == 0.60.0; python_version == '3.9' # v0.61 doesn't support Python 3.9. Req
 numba == 0.61.2; python_version > '3.9'
 
 # Dependencies for AMD GPUs
-awscli
 boto3
 botocore
 datasets
-ray >= 2.10.0
+ray>=2.10.0,<2.45.0
 peft
 pytest-asyncio
 tensorizer>=2.9.0

requirements/test.in

@@ -8,7 +8,6 @@ pytest-shard
 pytest-timeout
 
 # testing utils
-awscli
 backoff # required for phi4mm test
 blobfile # required for kimi-vl test
 einops # required for MPT, qwen-vl and Mamba
@@ -23,9 +22,9 @@ sentence-transformers # required for embedding tests
 soundfile # required for audio tests
 jiwer # required for audio tests
 timm # required for internvl test
-torch==2.6.0
-torchaudio==2.6.0
-torchvision==0.21.0
+torch==2.7.0
+torchaudio==2.7.0
+torchvision==0.22.0
 transformers_stream_generator # required for qwen-vl test
 mamba_ssm # required for plamo2 test
 matplotlib # required for qwen-vl test

requirements/test.txt

 # This file was autogenerated by uv via the following command:
-#    uv pip compile requirements/test.in -o requirements/test.txt
+#    uv pip compile requirements/test.in -o requirements/test.txt --index-strategy unsafe-best-match --torch-backend cu128
 absl-py==2.1.0
     # via rouge-score
 accelerate==1.0.1
@@ -37,8 +37,6 @@ attrs==24.2.0
     #   referencing
 audioread==3.0.1
     # via librosa
-awscli==1.35.23
-    # via -r requirements/test.in
 backoff==2.2.1
     # via
     #   -r requirements/test.in
@@ -53,7 +51,6 @@ boto3==1.35.57
     # via tensorizer
 botocore==1.35.57
     # via
-    #   awscli
     #   boto3
     #   s3transfer
 bounded-pool-executor==0.0.3
@@ -81,7 +78,6 @@ click==8.1.7
     #   typer
 colorama==0.4.6
     # via
-    #   awscli
     #   sacrebleu
     #   schemathesis
     #   tqdm-multiprocess
@@ -115,8 +111,6 @@ dnspython==2.7.0
     # via email-validator
 docopt==0.6.2
     # via num2words
-docutils==0.16
-    # via awscli
 einops==0.8.0
     # via
     #   -r requirements/test.in
@@ -274,7 +268,7 @@ mamba-ssm==2.2.4
     # via -r requirements/test.in
 markdown-it-py==3.0.0
     # via rich
-markupsafe==3.0.2
+markupsafe==3.0.1
     # via
     #   jinja2
     #   werkzeug
@@ -355,45 +349,48 @@ numpy==1.26.4
     #   transformers
     #   tritonclient
     #   vocos
-nvidia-cublas-cu12==12.4.5.8
+nvidia-cublas-cu12==12.8.3.14
     # via
     #   nvidia-cudnn-cu12
     #   nvidia-cusolver-cu12
     #   torch
-nvidia-cuda-cupti-cu12==12.4.127
+nvidia-cuda-cupti-cu12==12.8.57
+    # via torch
+nvidia-cuda-nvrtc-cu12==12.8.61
     # via torch
-nvidia-cuda-nvrtc-cu12==12.4.127
+nvidia-cuda-runtime-cu12==12.8.57
     # via torch
-nvidia-cuda-runtime-cu12==12.4.127
+nvidia-cudnn-cu12==9.7.1.26
     # via torch
-nvidia-cudnn-cu12==9.1.0.70
+nvidia-cufft-cu12==11.3.3.41
     # via torch
-nvidia-cufft-cu12==11.2.1.3
+nvidia-cufile-cu12==1.13.0.11
     # via torch
-nvidia-curand-cu12==10.3.5.147
+nvidia-curand-cu12==10.3.9.55
     # via torch
-nvidia-cusolver-cu12==11.6.1.9
+nvidia-cusolver-cu12==11.7.2.55
     # via torch
-nvidia-cusparse-cu12==12.3.1.170
+nvidia-cusparse-cu12==12.5.7.53
     # via
     #   nvidia-cusolver-cu12
     #   torch
-nvidia-cusparselt-cu12==0.6.2
+nvidia-cusparselt-cu12==0.6.3
     # via torch
-nvidia-nccl-cu12==2.21.5
+nvidia-nccl-cu12==2.26.2
     # via torch
-nvidia-nvjitlink-cu12==12.4.127
+nvidia-nvjitlink-cu12==12.8.61
     # via
+    #   nvidia-cufft-cu12
     #   nvidia-cusolver-cu12
     #   nvidia-cusparse-cu12
     #   torch
-nvidia-nvtx-cu12==12.4.127
+nvidia-nvtx-cu12==12.8.55
     # via torch
 opencv-python-headless==4.11.0.86
     # via
     #   -r requirements/test.in
     #   mistral-common
-packaging==24.1
+packaging==24.2
     # via
     #   accelerate
     #   black
@@ -469,8 +466,6 @@ pyarrow==18.0.0
     # via
     #   datasets
     #   genai-perf
-pyasn1==0.6.1
-    # via rsa
 pybind11==2.13.6
     # via lm-eval
 pycparser==2.22
@@ -534,7 +529,6 @@ pytz==2024.2
 pyyaml==6.0.2
     # via
     #   accelerate
-    #   awscli
     #   datamodel-code-generator
     #   datasets
     #   genai-perf
@@ -593,16 +587,12 @@ rpds-py==0.20.1
     # via
     #   jsonschema
     #   referencing
-rsa==4.7.2
-    # via awscli
 runai-model-streamer==0.11.0
     # via -r requirements/test.in
 runai-model-streamer-s3==0.11.0
     # via -r requirements/test.in
 s3transfer==0.10.3
-    # via
-    #   awscli
-    #   boto3
+    # via boto3
 sacrebleu==2.4.3
     # via lm-eval
 safetensors==0.4.5
@@ -629,11 +619,12 @@ sentence-transformers==3.2.1
     # via -r requirements/test.in
 sentencepiece==0.2.0
     # via mistral-common
-setuptools==75.8.0
+setuptools==77.0.3
     # via
     #   mamba-ssm
     #   pytablewriter
     #   torch
+    #   triton
 shellingham==1.5.4
     # via typer
 six==1.16.0
@@ -664,7 +655,7 @@ starlette-testclient==0.4.1
     # via schemathesis
 statsmodels==0.14.4
     # via genai-perf
-sympy==1.13.1
+sympy==1.13.3
     # via
     #   einx
     #   torch
@@ -696,7 +687,7 @@ tomli==2.2.1
     # via schemathesis
 tomli-w==1.2.0
     # via schemathesis
-torch==2.6.0
+torch==2.7.0+cu128
     # via
     #   -r requirements/test.in
     #   accelerate
@@ -714,12 +705,12 @@ torch==2.6.0
     #   torchvision
     #   vector-quantize-pytorch
     #   vocos
-torchaudio==2.6.0
+torchaudio==2.7.0+cu128
     # via
     #   -r requirements/test.in
     #   encodec
     #   vocos
-torchvision==0.21.0
+torchvision==0.22.0+cu128
     # via
     #   -r requirements/test.in
     #   timm
@@ -748,7 +739,7 @@ transformers==4.51.3
     #   transformers-stream-generator
 transformers-stream-generator==0.0.5
     # via -r requirements/test.in
-triton==3.2.0
+triton==3.3.0
     # via torch
 tritonclient==2.51.0
     # via

requirements/tpu.txt

@@ -3,12 +3,13 @@
 
 # Dependencies for TPU
 cmake>=3.26
-packaging
+packaging>=24.2
 setuptools-scm>=8
 wheel
 jinja2>=3.1.6
 ray[default]
 ray[data]
+setuptools==78.1.0
 
 # Install torch_xla
 --pre
@@ -17,9 +18,9 @@ ray[data]
 --find-links https://storage.googleapis.com/libtpu-releases/index.html
 --find-links https://storage.googleapis.com/jax-releases/jax_nightly_releases.html
 --find-links https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
-torch==2.8.0.dev20250408
-torchvision==0.22.0.dev20250408
-torch_xla[tpu, pallas] @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.8.0.dev20250408-cp39-cp39-linux_x86_64.whl ; python_version == "3.9"
-torch_xla[tpu, pallas] @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.8.0.dev20250408-cp310-cp310-linux_x86_64.whl ; python_version == "3.10"
-torch_xla[tpu, pallas] @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.8.0.dev20250408-cp311-cp311-linux_x86_64.whl ; python_version == "3.11"
+torch==2.8.0.dev20250430
+torchvision==0.22.0.dev20250430
+torch_xla[tpu, pallas] @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.8.0.dev20250430-cp39-cp39-linux_x86_64.whl ; python_version == "3.9"
+torch_xla[tpu, pallas] @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.8.0.dev20250430-cp310-cp310-linux_x86_64.whl ; python_version == "3.10"
+torch_xla[tpu, pallas] @ https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.8.0.dev20250430-cp311-cp311-linux_x86_64.whl ; python_version == "3.11"
 

requirements/xpu.txt

@@ -3,14 +3,14 @@
 
 ray>=2.9
 cmake>=3.26
-packaging
+packaging>=24.2
 setuptools-scm>=8
-setuptools>=75.8.0
+setuptools>=77.0.3,<80.0.0
 wheel
 jinja2>=3.1.6
 datasets # for benchmark scripts
 
-torch==2.6.0+xpu
+torch==2.7.0+xpu
 torchaudio
 torchvision
 pytorch-triton-xpu
@@ -18,6 +18,6 @@ pytorch-triton-xpu
 
 # Please refer xpu doc, we need manually install intel-extension-for-pytorch 2.6.10+xpu due to there are some conflict dependencies with torch 2.6.0+xpu
 # FIXME: This will be fix in ipex 2.7. just leave this here for awareness.
-# intel-extension-for-pytorch==2.6.10+xpu
-oneccl_bind_pt==2.6.0+xpu
+intel-extension-for-pytorch==2.7.10+xpu
+oneccl_bind_pt==2.7.0+xpu
 --extra-index-url=https://pytorch-extension.intel.com/release-whl/stable/xpu/us/

setup.py

@@ -54,7 +54,7 @@ elif (sys.platform.startswith("linux") and torch.version.cuda is None
     # fallback to cpu
     VLLM_TARGET_DEVICE = "cpu"
 
-MAIN_CUDA_VERSION = "12.4"
+MAIN_CUDA_VERSION = "12.8"
 
 
 def is_sccache_available() -> bool:

tests/async_engine/test_async_llm_engine.py

@@ -41,7 +41,7 @@ class MockEngine:
         self.abort_request_calls = 0
         self.request_id = None
         # Ugly, remove dependency when possible
-        self.parallel_config = ParallelConfig(1, 1, False)
+        self.parallel_config = ParallelConfig()
         self.model_config = MockModelConfig()
 
     async def step_async(self, virtual_engine):

tests/basic_correctness/test_basic_correctness.py

@@ -5,11 +5,13 @@ Run `pytest tests/basic_correctness/test_basic_correctness.py`.
 """
 import os
 import weakref
+from unittest.mock import Mock
 
 import pytest
 
 from vllm import LLM
 from vllm.platforms import current_platform
+from vllm.v1.engine.llm_engine import LLMEngine as LLMEngineV1
 
 from ..conftest import VllmRunner
 from ..models.utils import check_outputs_equal
@@ -152,9 +154,44 @@ def test_models_distributed(
         with hf_runner(model, dtype=dtype) as hf_model:
             hf_outputs = hf_model.generate_greedy(example_prompts, max_tokens)
 
-        check_outputs_equal(
-            outputs_0_lst=hf_outputs,
-            outputs_1_lst=vllm_outputs,
-            name_0="hf",
-            name_1="vllm",
-        )
+    check_outputs_equal(
+        outputs_0_lst=hf_outputs,
+        outputs_1_lst=vllm_outputs,
+        name_0="hf",
+        name_1="vllm",
+    )
+
+
+def test_failed_model_execution(vllm_runner, monkeypatch) -> None:
+
+    from vllm.envs import VLLM_USE_V1
+
+    if not VLLM_USE_V1:
+        pytest.skip("Skipping V0 test, dump input not supported")
+
+    # Needed to mock an error in the same process
+    monkeypatch.setenv('VLLM_ENABLE_V1_MULTIPROCESSING', '0')
+
+    with vllm_runner('facebook/opt-125m', enforce_eager=True) as vllm_model:
+        if isinstance(vllm_model.model.llm_engine, LLMEngineV1):
+            v1_test_failed_model_execution(vllm_model)
+
+
+def v1_test_failed_model_execution(vllm_model):
+
+    engine = vllm_model.model.llm_engine
+    mocked_execute_model = Mock(
+        side_effect=RuntimeError("Mocked Critical Error"))
+    engine.engine_core.engine_core.model_executor.execute_model =\
+                mocked_execute_model
+
+    with pytest.raises(RuntimeError) as exc_info:
+        prompts = [
+            "Hello, my name is",
+            "The president of the United States is",
+            "The capital of France is",
+            "The future of AI is",
+        ]
+        vllm_model.generate_greedy(prompts, 200, use_tqdm=False)
+    assert isinstance(exc_info.value, RuntimeError)
+    assert "Mocked Critical Error" in str(exc_info.value)

tests/compile/piecewise/test_full_cudagraph.py

+# SPDX-License-Identifier: Apache-2.0
+import contextlib
+import os
+
+import pytest
+
+from vllm import LLM, SamplingParams
+from vllm.config import CompilationConfig
+
+MODEL = "Qwen/Qwen2-1.5B-Instruct"
+
+
+@contextlib.contextmanager
+def temporary_environ(env_vars):
+    """
+    Temporarily set environment variables and restore them afterward.
+    We have to do this vs monkeypatch because monkeypatch doesn't work
+    with "module" scoped fixtures.
+    """
+    original_env = {k: os.environ.get(k) for k in env_vars}
+    try:
+        os.environ.update(env_vars)
+        yield
+    finally:
+        for k, v in original_env.items():
+            if v is None:
+                os.environ.pop(k, None)
+            else:
+                os.environ[k] = v
+
+
+@pytest.fixture(scope="module")
+def full_cudagraph_llm():
+    with temporary_environ({
+            "VLLM_USE_V1": "1",
+            "VLLM_FLASH_ATTN_VERSION": "3"
+    }):
+        return LLM(model=MODEL,
+                   gpu_memory_utilization=0.2,
+                   compilation_config=CompilationConfig(full_cuda_graph=True))
+
+
+@pytest.fixture(scope="module")
+def piecewise_llm():
+    with temporary_environ({
+            "VLLM_USE_V1": "1",
+            "VLLM_FLASH_ATTN_VERSION": "3"
+    }):
+        return LLM(model=MODEL,
+                   gpu_memory_utilization=0.5,
+                   compilation_config=CompilationConfig())
+
+
+def generate_text(llm: LLM, batch_size: int, max_tokens: int):
+    prompts = ["Hi my name is"] * batch_size
+    sampling_params = SamplingParams(temperature=0.0,
+                                     max_tokens=max_tokens,
+                                     top_p=0.95)
+
+    return llm.generate(prompts, sampling_params)
+
+
+@pytest.mark.parametrize(("batch_size", "max_tokens"), [(1, 10), (7, 10),
+                                                        (16, 10), (25, 10),
+                                                        (32, 10), (45, 10),
+                                                        (64, 10), (8, 5),
+                                                        (8, 20), (8, 200)])
+def test_full_cudagraph(batch_size, max_tokens, full_cudagraph_llm,
+                        piecewise_llm):
+    """
+    Load full cudagraph model and piecewise model once, and at the same time to
+    reuse them across various test cases.
+
+    Test various batch sizes and max_tokens to ensure that the full cudagraph
+    compilation works for padded cases too.
+    """
+    piecewise_responses = generate_text(piecewise_llm,
+                                        batch_size=batch_size,
+                                        max_tokens=max_tokens)
+    full_cudagraph_responses = generate_text(full_cudagraph_llm,
+                                             batch_size=batch_size,
+                                             max_tokens=max_tokens)
+
+    # Check that all responses are the same
+    for i in range(len(piecewise_responses)):
+        assert piecewise_responses[i].outputs[
+            0].text == full_cudagraph_responses[i].outputs[0].text
+
+
+def test_full_cudagraph_with_invalid_backend():
+    with temporary_environ({
+            "VLLM_USE_V1": "1",
+            "VLLM_FLASH_ATTN_VERSION":
+            "2"  #FA2 not supported with full_cuda_graph
+    }), pytest.raises(RuntimeError):
+        LLM(model=MODEL,
+            compilation_config=CompilationConfig(full_cuda_graph=True))

tests/compile/test_basic_correctness.py

@@ -103,7 +103,8 @@ def test_compile_correctness(
     method = test_setting.method
     fullgraph = test_setting.fullgraph
     if cuda_device_count_stateless() != pp_size * tp_size:
-        pytest.skip("Not correct CUDA devices for the test.")
+        pytest.skip(f"Need exactly {pp_size}*{tp_size} CUDA gpus but got "
+                    f"{cuda_device_count_stateless()}")
 
     with monkeypatch.context() as m:
         m.setenv("VLLM_ATTENTION_BACKEND", attn_backend)

tests/compile/test_full_graph.py

@@ -9,7 +9,7 @@ import torch
 
 from tests.quantization.utils import is_quant_method_supported
 from vllm import LLM, SamplingParams
-from vllm.config import CompilationConfig, CompilationLevel
+from vllm.config import CompilationConfig, CompilationLevel, PassConfig
 from vllm.platforms import current_platform
 
 from ..utils import create_new_process_for_each_test
@@ -95,9 +95,6 @@ def test_full_graph(
         run_model(optimization_level, model, model_kwargs)
 
 
-PassConfig = CompilationConfig.PassConfig
-
-
 # TODO(luka) add other supported compilation config scenarios here
 @pytest.mark.parametrize(
     "compilation_config, model_info",

tests/compile/test_functionalization.py

@@ -5,19 +5,19 @@ import torch
 
 import vllm.envs as envs
 from vllm import LLM, SamplingParams
+from vllm.compilation.activation_quant_fusion import ActivationQuantFusionPass
 from vllm.compilation.fix_functionalization import FixFunctionalizationPass
 from vllm.compilation.fusion import (FUSED_OPS, FusionPass, QuantKey,
                                      kFp8DynamicTokenSym, kFp8StaticTensorSym)
 from vllm.compilation.fx_utils import find_auto_fn, find_auto_fn_maybe, is_func
 from vllm.compilation.noop_elimination import NoOpEliminationPass
-from vllm.config import CompilationConfig, VllmConfig
+from vllm.config import CompilationConfig, PassConfig, VllmConfig
 
 from .backend import TestBackend
 
 OPS_IN_MODEL = [
     torch.ops._C.rotary_embedding.default,
     torch.ops._C.fused_add_rms_norm.default,
-    torch.ops._C.silu_and_mul.default,
 ]
 
 RMS_OP = torch.ops._C.rms_norm.default
@@ -29,6 +29,9 @@ RMS_QUANT_OPS = {
     ],
 }
 
+SILU_MUL_OP = torch.ops._C.silu_and_mul.default
+
+SILU_MUL_QUANT_OP = torch.ops._C.silu_and_mul_quant.default
 prompts = [
     "Hello, my name is",
     "The president of the United States is",
@@ -50,13 +53,14 @@ def test_fix_functionalization(model: str, quant_key: QuantKey,
     torch.set_default_device("cuda")
 
     vllm_config = VllmConfig()
-    vllm_config.compilation_config = CompilationConfig(pass_config= \
-        CompilationConfig.PassConfig(enable_fusion=do_fusion,
-                                          enable_noop=True))
+    vllm_config.compilation_config = CompilationConfig(
+        pass_config=PassConfig(enable_fusion=do_fusion, enable_noop=True))
     noop_pass = NoOpEliminationPass(vllm_config)
     fusion_pass = FusionPass.instance(vllm_config)
+    act_quant_fusion_pass = ActivationQuantFusionPass(vllm_config)
 
-    passes = [noop_pass, fusion_pass] if do_fusion else [noop_pass]
+    passes = [noop_pass, fusion_pass, act_quant_fusion_pass
+              ] if do_fusion else [noop_pass]
     func_pass = FixFunctionalizationPass(vllm_config)
     backend_func = TestBackend(*passes, func_pass)
     backend_no_func = TestBackend(*passes)
@@ -79,6 +83,7 @@ def test_fix_functionalization(model: str, quant_key: QuantKey,
     model_runner.model = torch.compile(orig_model,
                                        fullgraph=True,
                                        backend=backend_no_func)
+
     gen_no_func = llm.generate(prompts, sampling_params)
 
     for output_func, output_no_func in zip(gen_func, gen_no_func):
@@ -88,7 +93,12 @@ def test_fix_functionalization(model: str, quant_key: QuantKey,
     # and replaced by fused quantized ops in RMS_QUANT_OPS.
     rms_ops = [FUSED_OPS[(quant_key, True)], FUSED_OPS[(quant_key, False)]
                ] if do_fusion else [RMS_OP]
-    ops = OPS_IN_MODEL + rms_ops
+    silu_mul_ops = [SILU_MUL_QUANT_OP] if do_fusion and \
+        quant_key == kFp8StaticTensorSym else [
+        SILU_MUL_OP
+    ]
+
+    ops = OPS_IN_MODEL + rms_ops + silu_mul_ops
 
     for op in ops:
         find_auto_fn(backend_no_func.graph_post_pass.nodes, op)

tests/compile/test_fusion.py

@@ -9,7 +9,8 @@ from vllm.compilation.fusion import (FUSED_OPS, QUANT_OPS, FusedRMSQuantKey,
                                      FusionPass, QuantKey)
 from vllm.compilation.fx_utils import find_auto_fn, find_auto_fn_maybe
 from vllm.compilation.noop_elimination import NoOpEliminationPass
-from vllm.config import CompilationConfig, CompilationLevel, VllmConfig
+from vllm.config import (CompilationConfig, CompilationLevel, PassConfig,
+                         VllmConfig)
 from vllm.model_executor.layers.layernorm import RMSNorm
 from vllm.model_executor.layers.quantization.utils.w8a8_utils import (
     CUTLASS_FP8_SUPPORTED, Fp8LinearOp, maybe_create_device_identity)
@@ -78,8 +79,7 @@ def test_fusion_rmsnorm_quant(dtype, hidden_size, num_tokens, eps, static,
     vllm_config = VllmConfig(compilation_config=CompilationConfig(
         level=CompilationLevel.PIECEWISE, custom_ops=["+rms_norm"]))
     vllm_config.compilation_config.pass_config = \
-            CompilationConfig.PassConfig(enable_fusion=True,
-                                              enable_noop=True)
+        PassConfig(enable_fusion=True, enable_noop=True)
     with vllm.config.set_current_vllm_config(vllm_config):
         # Reshape pass is needed for the fusion pass to work
         noop_pass = NoOpEliminationPass(vllm_config)

tests/compile/test_pass_manager.py

@@ -22,7 +22,7 @@ def test_bad_callable():
     pass_manager.configure(config)
 
     with pytest.raises(AssertionError):
-        pass_manager.add(simple_callable)  # noqa, type wrong on purpose
+        pass_manager.add(simple_callable)
 
 
 # Pass that inherits from InductorPass

tests/compile/test_sequence_parallelism.py

@@ -10,7 +10,7 @@ from vllm.compilation.fx_utils import (find_auto_fn, find_auto_fn_maybe,
                                        find_specified_fn_maybe, is_func)
 from vllm.compilation.sequence_parallelism import SequenceParallelismPass
 from vllm.config import (CompilationConfig, DeviceConfig, ModelConfig,
-                         VllmConfig)
+                         PassConfig, VllmConfig)
 from vllm.distributed import tensor_model_parallel_all_reduce
 from vllm.distributed.parallel_state import (init_distributed_environment,
                                              initialize_model_parallel)
@@ -126,9 +126,8 @@ def sequence_parallelism_pass_on_test_model(local_rank: int, world_size: int,
 
     # configure vllm config for SequenceParallelismPass
     vllm_config = VllmConfig()
-    vllm_config.compilation_config = CompilationConfig(
-        pass_config=CompilationConfig.PassConfig(
-            enable_sequence_parallelism=True, ), )
+    vllm_config.compilation_config = CompilationConfig(pass_config=PassConfig(
+        enable_sequence_parallelism=True))
     vllm_config.device_config = DeviceConfig(device=torch.device("cuda"))
 
     # this is a fake model name to construct the model config