mirror of
https://git.datalinker.icu/vllm-project/vllm.git
synced 2025-12-10 02:15:01 +08:00
[V0 Deprecation] Skip PP test (#25128)
Signed-off-by: Woosuk Kwon <woosuk.kwon@berkeley.edu>
This commit is contained in:
Woosuk Kwon
GitHub
parent
6c036615dc
commit
7fb2a5be28
@ -26,23 +26,10 @@ logger = init_logger("test_pipeline_parallel")
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VLLM_MULTI_NODE = os.getenv("VLLM_MULTI_NODE", "0") == "1"
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@pytest.fixture(scope="function", autouse=True)
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def use_v0_only(monkeypatch):
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"""
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For PP, we fall back to V0 by default. This means
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that the TP baseline runs with V1 while the PP engine
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runs with V0. This gives divergent results with dummy
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weights. Once we enable V1 by default for PP, we can
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remove this.
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"""
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monkeypatch.setenv('VLLM_USE_V1', '0')
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class ParallelSetup(NamedTuple):
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tp_size: int
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pp_size: int
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eager_mode: bool
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chunked_prefill: bool
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class PPTestOptions(NamedTuple):
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@ -53,23 +40,10 @@ class PPTestOptions(NamedTuple):
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@dataclass
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class PPTestSettings:
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parallel_setups: list[ParallelSetup]
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# NOTE: the length of distributed_backends and
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# vllm_major_versions should be the same, and they
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# are first zipped together to iterate over all
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# test settings.
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distributed_backends: list[str]
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# vllm major version: "0" for V0, "1" for V1
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vllm_major_versions: list[str]
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runner: RunnerOption
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test_options: PPTestOptions
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def __post_init__(self):
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if len(self.distributed_backends) != len(self.vllm_major_versions):
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raise ValueError(
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f"Length mismatch: distributed_backends "
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f"({len(self.distributed_backends)}) != "
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f"vllm_major_versions ({len(self.vllm_major_versions)})")
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@staticmethod
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def detailed(
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*,
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@ -83,27 +57,21 @@ class PPTestSettings:
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parallel_setups=[
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ParallelSetup(tp_size=tp_base,
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pp_size=pp_base,
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eager_mode=False,
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chunked_prefill=False),
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eager_mode=False),
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ParallelSetup(tp_size=tp_base,
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pp_size=2 * pp_base,
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eager_mode=False,
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chunked_prefill=True),
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eager_mode=False),
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ParallelSetup(tp_size=tp_base,
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pp_size=2 * pp_base,
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eager_mode=True,
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chunked_prefill=False),
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eager_mode=True),
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ParallelSetup(tp_size=2 * tp_base,
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pp_size=pp_base,
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eager_mode=False,
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chunked_prefill=True),
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eager_mode=False),
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ParallelSetup(tp_size=2 * tp_base,
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pp_size=pp_base,
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eager_mode=True,
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chunked_prefill=False),
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eager_mode=True),
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],
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distributed_backends=["mp", "mp", "ray", "ray"],
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vllm_major_versions=["0", "1", "0", "1"],
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distributed_backends=["mp", "ray"],
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runner=runner,
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test_options=PPTestOptions(multi_node_only=multi_node_only,
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load_format=load_format),
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@ -118,17 +86,14 @@ class PPTestSettings:
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multi_node_only: bool = False,
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load_format: Optional[str] = None,
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):
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vllm_major_versions = ["1"] if runner == "pooling" else ["0"]
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return PPTestSettings(
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parallel_setups=[
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ParallelSetup(tp_size=tp_base,
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pp_size=pp_base,
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eager_mode=True,
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chunked_prefill=False),
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eager_mode=True),
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],
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distributed_backends=["mp"],
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vllm_major_versions=vllm_major_versions,
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runner=runner,
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test_options=PPTestOptions(multi_node_only=multi_node_only,
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load_format=load_format),
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@ -138,10 +103,8 @@ class PPTestSettings:
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opts = self.test_options
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for parallel_setup in self.parallel_setups:
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for backend, vllm_major_version in zip(self.distributed_backends,
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self.vllm_major_versions):
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yield (model_id, parallel_setup, backend, vllm_major_version,
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self.runner, opts)
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for backend in self.distributed_backends:
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yield (model_id, parallel_setup, backend, self.runner, opts)
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# NOTE: You can adjust tp_base and/or pp_base locally to fit the model in GPU
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@ -269,7 +232,6 @@ def _compare_tp(
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model_id: str,
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parallel_setup: ParallelSetup,
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distributed_backend: str,
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vllm_major_version: str,
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runner: RunnerOption,
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test_options: PPTestOptions,
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num_gpus_available: int,
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@ -281,7 +243,6 @@ def _compare_tp(
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tp_size,
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pp_size,
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eager_mode,
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chunked_prefill,
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) = parallel_setup
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multi_node_only, load_format = test_options
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@ -334,8 +295,6 @@ def _compare_tp(
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"--max-num-seqs",
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"8",
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]
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if chunked_prefill:
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common_args.append("--enable-chunked-prefill")
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if eager_mode:
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common_args.append("--enforce-eager")
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if runner != "auto":
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@ -353,14 +312,10 @@ def _compare_tp(
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if max_num_seqs:
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common_args.extend(["--max-num-seqs", f"{max_num_seqs}"])
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specific_case = tp_size == 2 and pp_size == 2 and chunked_prefill
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testing_ray_compiled_graph = False
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if distributed_backend == "ray" and (vllm_major_version == "1"
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or specific_case):
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if distributed_backend == "ray":
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# For V1, test Ray Compiled Graph for all the tests
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# For V0, test Ray Compiled Graph for a subset of the tests
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pp_env = {
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"VLLM_USE_V1": vllm_major_version,
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"VLLM_USE_V1": "1",
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"VLLM_USE_RAY_COMPILED_DAG": "1",
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"VLLM_USE_RAY_SPMD_WORKER": "1",
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"VLLM_USE_RAY_COMPILED_DAG_NCCL_CHANNEL": "1",
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@ -368,17 +323,15 @@ def _compare_tp(
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# Temporary. Currently when zeromq + SPMD is used, it does not properly
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# terminate because of a Ray Compiled Graph issue.
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common_args.append("--disable-frontend-multiprocessing")
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testing_ray_compiled_graph = True
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elif distributed_backend == "mp":
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# Both V0/V1 of multiprocessing executor support PP
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pp_env = {
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"VLLM_USE_V1": vllm_major_version,
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"VLLM_USE_V1": "1",
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}
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else:
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pp_env = None
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tp_env = {
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"VLLM_USE_V1": vllm_major_version,
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"VLLM_USE_V1": "1",
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}
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pp_args = [
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@ -404,25 +357,17 @@ def _compare_tp(
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"mp",
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]
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try:
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compare_two_settings(model_id,
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pp_args,
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tp_args,
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pp_env,
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tp_env,
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method=method)
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except Exception:
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if testing_ray_compiled_graph and vllm_major_version == "0":
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# Ray Compiled Graph tests are flaky for V0,
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# so we don't want to fail the test
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logger.exception("Ray Compiled Graph tests failed")
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else:
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raise
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compare_two_settings(model_id,
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pp_args,
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tp_args,
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pp_env,
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tp_env,
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method=method)
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@pytest.mark.parametrize(
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("model_id", "parallel_setup", "distributed_backend", "vllm_major_version",
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"runner", "test_options"),
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("model_id", "parallel_setup", "distributed_backend", "runner",
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"test_options"),
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[
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params for model_id, settings in TEXT_GENERATION_MODELS.items()
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for params in settings.iter_params(model_id) if model_id in TEST_MODELS
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@ -433,15 +378,14 @@ def test_tp_language_generation(
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model_id: str,
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parallel_setup: ParallelSetup,
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distributed_backend: str,
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vllm_major_version: str,
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runner: RunnerOption,
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test_options: PPTestOptions,
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num_gpus_available,
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):
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pytest.skip("Skipping the test until V1 passes it.")
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_compare_tp(model_id,
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parallel_setup,
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distributed_backend,
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vllm_major_version,
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runner,
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test_options,
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num_gpus_available,
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@ -450,8 +394,8 @@ def test_tp_language_generation(
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@pytest.mark.parametrize(
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("model_id", "parallel_setup", "distributed_backend", "vllm_major_version",
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"runner", "test_options"),
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("model_id", "parallel_setup", "distributed_backend", "runner",
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"test_options"),
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[
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params for model_id, settings in EMBEDDING_MODELS.items()
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for params in settings.iter_params(model_id) if model_id in TEST_MODELS
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@ -462,15 +406,14 @@ def test_tp_language_embedding(
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model_id: str,
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parallel_setup: ParallelSetup,
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distributed_backend: str,
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vllm_major_version: str,
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runner: RunnerOption,
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test_options: PPTestOptions,
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num_gpus_available,
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):
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pytest.skip("Skipping the test until V1 passes it.")
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_compare_tp(model_id,
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parallel_setup,
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distributed_backend,
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vllm_major_version,
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runner,
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test_options,
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num_gpus_available,
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@ -479,8 +422,8 @@ def test_tp_language_embedding(
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@pytest.mark.parametrize(
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("model_id", "parallel_setup", "distributed_backend", "vllm_major_version",
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"runner", "test_options"),
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("model_id", "parallel_setup", "distributed_backend", "runner",
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"test_options"),
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[
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params for model_id, settings in MULTIMODAL_MODELS.items()
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for params in settings.iter_params(model_id) if model_id in TEST_MODELS
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@ -491,15 +434,14 @@ def test_tp_multimodal_generation(
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model_id: str,
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parallel_setup: ParallelSetup,
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distributed_backend: str,
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vllm_major_version: str,
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runner: RunnerOption,
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test_options: PPTestOptions,
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num_gpus_available,
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):
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pytest.skip("Skipping the test until V1 passes it.")
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_compare_tp(model_id,
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parallel_setup,
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distributed_backend,
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vllm_major_version,
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runner,
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test_options,
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num_gpus_available,
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