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[V0 Deprecation] Enable the remaining multimodal tests in V1 #25307

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Merged
merged 6 commits into from
Sep 20, 2025
Merged

[V0 Deprecation] Enable the remaining multimodal tests in V1 #25307

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5b2a301
[CI/Build] Avoid hanging AWQ test on V1
DarkLight1337 Sep 20, 2025
f800661
Migrate more tests
DarkLight1337 Sep 20, 2025
7bc206f
Refactor
DarkLight1337 Sep 20, 2025
cef9aed
Merge branch 'main' into awq-test-v1
DarkLight1337 Sep 20, 2025
2e6546d
Fix timeout
DarkLight1337 Sep 20, 2025
ef99d5d
Avoid timeout
DarkLight1337 Sep 20, 2025
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76 changes: 56 additions & 20 deletions tests/conftest.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@
import tempfile
import threading
from collections.abc import Generator
from contextlib import nullcontext
from enum import Enum
from typing import Any, Callable, Optional, TypedDict, TypeVar, Union, cast

Expand All @@ -45,14 +46,14 @@
from vllm.distributed import (cleanup_dist_env_and_memory,
init_distributed_environment,
initialize_model_parallel)
from vllm.inputs import (ExplicitEncoderDecoderPrompt, TextPrompt,
to_enc_dec_tuple_list, zip_enc_dec_prompts)
from vllm.inputs import TextPrompt
from vllm.logger import init_logger
from vllm.multimodal.utils import fetch_image
from vllm.outputs import RequestOutput
from vllm.sampling_params import BeamSearchParams
from vllm.sequence import Logprob
from vllm.transformers_utils.utils import maybe_model_redirect
from vllm.utils import set_default_torch_num_threads

logger = init_logger(__name__)

Expand Down Expand Up @@ -306,6 +307,35 @@ def __init__(
is_cross_encoder: bool = False,
skip_tokenizer_init: bool = False,
auto_cls: type[_BaseAutoModelClass] = AutoModelForCausalLM,
# Set this to avoid hanging issue
default_torch_num_threads: Optional[int] = None,
) -> None:
init_ctx = (nullcontext() if default_torch_num_threads is None else
set_default_torch_num_threads(default_torch_num_threads))

with init_ctx:
self._init(
model_name=model_name,
dtype=dtype,
model_kwargs=model_kwargs,
trust_remote_code=trust_remote_code,
is_sentence_transformer=is_sentence_transformer,
is_cross_encoder=is_cross_encoder,
skip_tokenizer_init=skip_tokenizer_init,
auto_cls=auto_cls,
)

def _init(
self,
model_name: str,
dtype: str = "auto",
*,
model_kwargs: Optional[dict[str, Any]] = None,
trust_remote_code: bool = True,
is_sentence_transformer: bool = False,
is_cross_encoder: bool = False,
skip_tokenizer_init: bool = False,
auto_cls: type[_BaseAutoModelClass] = AutoModelForCausalLM,
) -> None:
model_name = maybe_model_redirect(model_name)
self.model_name = model_name
Expand Down Expand Up @@ -714,26 +744,32 @@ def __init__(
enable_chunked_prefill: Optional[bool] = False,
swap_space: int = 4,
enforce_eager: Optional[bool] = False,
# Set this to avoid hanging issue
default_torch_num_threads: Optional[int] = None,
**kwargs,
) -> None:
self.llm = LLM(
model=model_name,
runner=runner,
convert=convert,
tokenizer=tokenizer_name,
tokenizer_mode=tokenizer_mode,
trust_remote_code=trust_remote_code,
dtype=dtype,
seed=seed,
swap_space=swap_space,
enforce_eager=enforce_eager,
disable_log_stats=disable_log_stats,
tensor_parallel_size=tensor_parallel_size,
max_model_len=max_model_len,
block_size=block_size,
enable_chunked_prefill=enable_chunked_prefill,
**kwargs,
)
init_ctx = (nullcontext() if default_torch_num_threads is None else
set_default_torch_num_threads(default_torch_num_threads))

with init_ctx:
self.llm = LLM(
model=model_name,
runner=runner,
convert=convert,
tokenizer=tokenizer_name,
tokenizer_mode=tokenizer_mode,
trust_remote_code=trust_remote_code,
dtype=dtype,
seed=seed,
swap_space=swap_space,
enforce_eager=enforce_eager,
disable_log_stats=disable_log_stats,
tensor_parallel_size=tensor_parallel_size,
max_model_len=max_model_len,
block_size=block_size,
enable_chunked_prefill=enable_chunked_prefill,
**kwargs,
)

def get_inputs(
self,
Expand Down
158 changes: 79 additions & 79 deletions tests/models/multimodal/generation/test_common.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -32,13 +32,6 @@
if current_platform.is_rocm():
os.environ["VLLM_USE_TRITON_FLASH_ATTN"] = "0"

REQUIRES_V0_MODELS = [
# V1 Test: not enough KV cache space in C1.
"fuyu",
# V1 Test: Deadlock issue when processing mm_inputs
"llava-onevision-transformers",
]

# yapf: disable
COMMON_BROADCAST_SETTINGS = {
"test_type": VLMTestType.IMAGE,
Expand Down Expand Up @@ -186,8 +179,11 @@
image_size_factors=[(0.25, 0.5, 1.0)],
vllm_runner_kwargs={
"model_impl": "transformers",
"default_torch_num_threads": 1,
},
marks=[pytest.mark.core_model],
# FIXME: Investigate why the test hangs
# when processing the 3rd prompt in vLLM
marks=[pytest.mark.core_model, pytest.mark.skip(reason="Test hangs")],
),
"idefics3-transformers": VLMTestInfo(
models=["HuggingFaceTB/SmolVLM-256M-Instruct"],
Expand Down Expand Up @@ -320,6 +316,7 @@
vllm_output_post_proc=model_utils.fuyu_vllm_to_hf_output,
num_logprobs=10,
image_size_factors=[(), (0.25,), (0.25, 0.25, 0.25), (0.25, 0.2, 0.15)],
marks=[large_gpu_mark(min_gb=32)],
),
"gemma3": VLMTestInfo(
models=["google/gemma-3-4b-it"],
Expand Down Expand Up @@ -861,13 +858,14 @@ def _mark_splits(
test_type=VLMTestType.IMAGE,
create_new_process_for_each_test=False,
))
def test_single_image_models(tmp_path: PosixPath, model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
image_assets: ImageTestAssets, monkeypatch):
if model_type in REQUIRES_V0_MODELS:
monkeypatch.setenv("VLLM_USE_V1", "0")
def test_single_image_models(
tmp_path: PosixPath,
model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
image_assets: ImageTestAssets,
):
model_test_info = VLM_TEST_SETTINGS[model_type]
runners.run_single_image_test(
tmp_path=tmp_path,
Expand All @@ -886,13 +884,14 @@ def test_single_image_models(tmp_path: PosixPath, model_type: str,
test_type=VLMTestType.MULTI_IMAGE,
create_new_process_for_each_test=False,
))
def test_multi_image_models(tmp_path: PosixPath, model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
image_assets: ImageTestAssets, monkeypatch):
if model_type in REQUIRES_V0_MODELS:
monkeypatch.setenv("VLLM_USE_V1", "0")
def test_multi_image_models(
tmp_path: PosixPath,
model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
image_assets: ImageTestAssets,
):
model_test_info = VLM_TEST_SETTINGS[model_type]
runners.run_multi_image_test(
tmp_path=tmp_path,
Expand All @@ -911,13 +910,13 @@ def test_multi_image_models(tmp_path: PosixPath, model_type: str,
test_type=VLMTestType.EMBEDDING,
create_new_process_for_each_test=False,
))
def test_image_embedding_models(model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
image_assets: ImageTestAssets, monkeypatch):
if model_type in REQUIRES_V0_MODELS:
monkeypatch.setenv("VLLM_USE_V1", "0")
def test_image_embedding_models(
model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
image_assets: ImageTestAssets,
):
model_test_info = VLM_TEST_SETTINGS[model_type]
runners.run_embedding_test(
model_test_info=model_test_info,
Expand All @@ -935,11 +934,13 @@ def test_image_embedding_models(model_type: str,
test_type=VLMTestType.VIDEO,
create_new_process_for_each_test=False,
))
def test_video_models(model_type: str, test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner], vllm_runner: type[VllmRunner],
video_assets: VideoTestAssets, monkeypatch):
if model_type in REQUIRES_V0_MODELS:
monkeypatch.setenv("VLLM_USE_V1", "0")
def test_video_models(
model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
video_assets: VideoTestAssets,
):
model_test_info = VLM_TEST_SETTINGS[model_type]
runners.run_video_test(
model_test_info=model_test_info,
Expand All @@ -957,11 +958,13 @@ def test_video_models(model_type: str, test_case: ExpandableVLMTestArgs,
test_type=VLMTestType.AUDIO,
create_new_process_for_each_test=False,
))
def test_audio_models(model_type: str, test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner], vllm_runner: type[VllmRunner],
audio_assets: AudioTestAssets, monkeypatch):
if model_type in REQUIRES_V0_MODELS:
monkeypatch.setenv("VLLM_USE_V1", "0")
def test_audio_models(
model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
audio_assets: AudioTestAssets,
):
model_test_info = VLM_TEST_SETTINGS[model_type]
runners.run_audio_test(
model_test_info=model_test_info,
Expand All @@ -984,10 +987,7 @@ def test_custom_inputs_models(
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
monkeypatch,
):
if model_type in REQUIRES_V0_MODELS:
monkeypatch.setenv("VLLM_USE_V1", "0")
model_test_info = VLM_TEST_SETTINGS[model_type]
runners.run_custom_inputs_test(
model_test_info=model_test_info,
Expand All @@ -1006,13 +1006,14 @@ def test_custom_inputs_models(
create_new_process_for_each_test=True,
))
@create_new_process_for_each_test()
def test_single_image_models_heavy(tmp_path: PosixPath, model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
image_assets: ImageTestAssets, monkeypatch):
if model_type in REQUIRES_V0_MODELS:
monkeypatch.setenv("VLLM_USE_V1", "0")
def test_single_image_models_heavy(
tmp_path: PosixPath,
model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
image_assets: ImageTestAssets,
):
model_test_info = VLM_TEST_SETTINGS[model_type]
runners.run_single_image_test(
tmp_path=tmp_path,
Expand All @@ -1032,13 +1033,14 @@ def test_single_image_models_heavy(tmp_path: PosixPath, model_type: str,
create_new_process_for_each_test=True,
))
@create_new_process_for_each_test()
def test_multi_image_models_heavy(tmp_path: PosixPath, model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
image_assets: ImageTestAssets, monkeypatch):
if model_type in REQUIRES_V0_MODELS:
monkeypatch.setenv("VLLM_USE_V1", "0")
def test_multi_image_models_heavy(
tmp_path: PosixPath,
model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
image_assets: ImageTestAssets,
):
model_test_info = VLM_TEST_SETTINGS[model_type]
runners.run_multi_image_test(
tmp_path=tmp_path,
Expand All @@ -1058,14 +1060,13 @@ def test_multi_image_models_heavy(tmp_path: PosixPath, model_type: str,
create_new_process_for_each_test=True,
))
@create_new_process_for_each_test()
def test_image_embedding_models_heavy(model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
image_assets: ImageTestAssets,
monkeypatch):
if model_type in REQUIRES_V0_MODELS:
monkeypatch.setenv("VLLM_USE_V1", "0")
def test_image_embedding_models_heavy(
model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
image_assets: ImageTestAssets,
):
model_test_info = VLM_TEST_SETTINGS[model_type]
runners.run_embedding_test(
model_test_info=model_test_info,
Expand All @@ -1083,12 +1084,13 @@ def test_image_embedding_models_heavy(model_type: str,
test_type=VLMTestType.VIDEO,
create_new_process_for_each_test=True,
))
def test_video_models_heavy(model_type: str, test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
video_assets: VideoTestAssets, monkeypatch):
if model_type in REQUIRES_V0_MODELS:
monkeypatch.setenv("VLLM_USE_V1", "0")
def test_video_models_heavy(
model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
video_assets: VideoTestAssets,
):
model_test_info = VLM_TEST_SETTINGS[model_type]
runners.run_video_test(
model_test_info=model_test_info,
Expand All @@ -1106,12 +1108,13 @@ def test_video_models_heavy(model_type: str, test_case: ExpandableVLMTestArgs,
test_type=VLMTestType.AUDIO,
create_new_process_for_each_test=True,
))
def test_audio_models_heavy(model_type: str, test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
audio_assets: AudioTestAssets, monkeypatch):
if model_type in REQUIRES_V0_MODELS:
monkeypatch.setenv("VLLM_USE_V1", "0")
def test_audio_models_heavy(
model_type: str,
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
audio_assets: AudioTestAssets,
):
model_test_info = VLM_TEST_SETTINGS[model_type]
runners.run_audio_test(
model_test_info=model_test_info,
Expand All @@ -1135,10 +1138,7 @@ def test_custom_inputs_models_heavy(
test_case: ExpandableVLMTestArgs,
hf_runner: type[HfRunner],
vllm_runner: type[VllmRunner],
monkeypatch,
):
if model_type in REQUIRES_V0_MODELS:
monkeypatch.setenv("VLLM_USE_V1", "0")
model_test_info = VLM_TEST_SETTINGS[model_type]
runners.run_custom_inputs_test(
model_test_info=model_test_info,
Expand Down
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