# SPDX-License-Identifier: Apache-2.0 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project from functools import partial from unittest.mock import patch import pytest from vllm import LLM from vllm.config import ModelImpl from vllm.engine.llm_engine import LLMEngine as V0LLMEngine from vllm.utils import GiB_bytes from vllm.v1.core.kv_cache_utils import get_kv_cache_config from vllm.v1.engine.core import EngineCore as V1EngineCore from ..utils import create_new_process_for_each_test from .registry import (_TRANSFORMERS_BACKEND_MODELS, AUTO_EXAMPLE_MODELS, HF_EXAMPLE_MODELS, HfExampleModels) from .utils import dummy_hf_overrides @create_new_process_for_each_test() def can_initialize(model_arch: str, monkeypatch: pytest.MonkeyPatch, EXAMPLE_MODELS: HfExampleModels): """The reason for using create_new_process_for_each_test is to avoid the WARNING: "We must use the 'spawn' multiprocessing start method. Overriding VLLM_WORKER_MULTIPROC_METHOD to 'spawn'." The spawn process causes the _initialize_kv_caches_v1 function below to become ineffective. """ model_info = EXAMPLE_MODELS.get_hf_info(model_arch) model_info.check_available_online(on_fail="skip") model_info.check_transformers_version(on_fail="skip") hf_overrides_fn = partial(dummy_hf_overrides, model_arch=model_arch, exist_overrides=model_info.hf_overrides) if model_arch in ("Llama4ForCausalLM", "EagleLlama4ForCausalLM"): from vllm.model_executor.models.llama4 import Llama4ForCausalLM from vllm.model_executor.models.registry import ModelRegistry ModelRegistry.register_model("Llama4ForCausalLM", Llama4ForCausalLM) # Avoid calling model.forward() def _initialize_kv_caches_v0(self) -> None: self.cache_config.num_gpu_blocks = 0 self.cache_config.num_cpu_blocks = 0 def _initialize_kv_caches_v1(self, vllm_config): kv_cache_specs = self.model_executor.get_kv_cache_specs() scheduler_kv_cache_config = get_kv_cache_config( vllm_config, kv_cache_specs[0], 10 * GiB_bytes, ) # gpu_blocks (> 0), cpu_blocks, scheduler_kv_cache_config return 1, 0, scheduler_kv_cache_config with (patch.object(V0LLMEngine, "_initialize_kv_caches", _initialize_kv_caches_v0), patch.object(V1EngineCore, "_initialize_kv_caches", _initialize_kv_caches_v1), monkeypatch.context() as m): if model_info.v0_only: m.setenv("VLLM_USE_V1", "0") if model_arch == "Phi4FlashForCausalLM": # Phi4FlashForCausalLM only supports DIFFERENTIAL_FLASH_ATTN backend m.setenv("VLLM_ATTENTION_BACKEND", "DIFFERENTIAL_FLASH_ATTN") LLM( model_info.default, tokenizer=model_info.tokenizer, tokenizer_mode=model_info.tokenizer_mode, revision=model_info.revision, speculative_config={ "model": model_info.speculative_model, "num_speculative_tokens": 1, } if model_info.speculative_model else None, trust_remote_code=model_info.trust_remote_code, max_model_len=model_info.max_model_len, # these tests seem to produce leftover memory gpu_memory_utilization=0.80, load_format="dummy", model_impl=ModelImpl.TRANSFORMERS if model_arch in _TRANSFORMERS_BACKEND_MODELS else ModelImpl.VLLM, hf_overrides=hf_overrides_fn, ) @pytest.mark.parametrize("model_arch", HF_EXAMPLE_MODELS.get_supported_archs()) def test_can_initialize(model_arch: str, monkeypatch: pytest.MonkeyPatch): can_initialize(model_arch, monkeypatch, HF_EXAMPLE_MODELS) @pytest.mark.parametrize("model_arch", AUTO_EXAMPLE_MODELS.get_supported_archs()) def test_implicit_converted_models(model_arch: str, monkeypatch: pytest.MonkeyPatch): can_initialize(model_arch, monkeypatch, AUTO_EXAMPLE_MODELS)