[CI] Add pytest markers to current tests and update the doc. (#577)

Signed-off-by: Alicia <115451386+congw729@users.noreply.github.com>
Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>
This commit is contained in:
AliciaandHongsheng Liu authored and GitHub committed 2026-02-09 16:49:45 +08:00
1 parent cdde401813
commit d3ea94309d
37 files changed
+165 -94

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@@ -20,16 +20,17 @@ import torch
import torch.distributed as dist
from PIL import Image
from tests.utils import hardware_test
from vllm_omni import Omni
from vllm_omni.diffusion.data import DiffusionParallelConfig
from vllm_omni.inputs.data import OmniDiffusionSamplingParams
from vllm_omni.platforms import current_omni_platform
# ruff: noqa: E402
REPO_ROOT = Path(__file__).resolve().parents[3]
if str(REPO_ROOT) not in sys.path:
sys.path.insert(0, str(REPO_ROOT))
from vllm_omni import Omni
from vllm_omni.diffusion.data import DiffusionParallelConfig
from vllm_omni.platforms import current_omni_platform
# Test configuration
MODELS = ["riverclouds/qwen_image_random"]
@@ -145,9 +146,11 @@ def _run_inference(
# - warmup: whether to run warmup for this SP config
# - is_perf_test: whether this is a performance test (show speedup metrics)
SP_CONFIGS = [
(2, 1, DEFAULT_HEIGHT, DEFAULT_WIDTH, True, True), # Ulysses-2 - performance test
# Ulysses-2 - performance test
(2, 1, DEFAULT_HEIGHT, DEFAULT_WIDTH, True, True),
(1, 2, DEFAULT_HEIGHT, DEFAULT_WIDTH, True, True), # Ring-2 - performance test
(2, 2, DEFAULT_HEIGHT, DEFAULT_WIDTH, False, False), # Hybrid - correctness only
# Hybrid - correctness only
(2, 2, DEFAULT_HEIGHT, DEFAULT_WIDTH, False, False),
(4, 1, 272, 272, False, False), # Ulysses-4 - shape and correctness
]
@@ -162,6 +165,10 @@ def _get_sp_mode(ulysses_degree: int, ring_degree: int) -> str:
return f"hybrid-{ulysses_degree}x{ring_degree}"
@pytest.mark.core_model
@pytest.mark.diffusion
@pytest.mark.parallel
@hardware_test(res={"cuda": "L4", "rocm": "MI325"}, num_cards={"cuda": 4, "rocm": 2})
@pytest.mark.parametrize("model_name", MODELS)
def test_sp_correctness(model_name: str):
"""Test that SP inference produces correct outputs and measure performance.