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vllm-omni/tests/e2e/offline_inference/test_t2i_model.py
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2025-12-12 14:25:52 +08:00

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Python

import os
import sys
from pathlib import Path
import pytest
import torch
# ruff: noqa: E402
REPO_ROOT = Path(__file__).resolve().parents[2]
if str(REPO_ROOT) not in sys.path:
sys.path.insert(0, str(REPO_ROOT))
from vllm_omni import Omni
os.environ["VLLM_TEST_CLEAN_GPU_MEMORY"] = "1"
models = ["Tongyi-MAI/Z-Image-Turbo", "riverclouds/qwen_image_random"]
@pytest.mark.parametrize("model_name", models)
def test_diffusion_model(model_name: str):
m = Omni(model=model_name)
# high resolution may cause OOM on L4
height = 256
width = 256
images = m.generate(
"a photo of a cat sitting on a laptop keyboard",
height=height,
width=width,
num_inference_steps=2,
guidance_scale=0.0,
generator=torch.Generator("cuda").manual_seed(42),
num_outputs_per_prompt=2,
)
assert len(images) == 2
# check image size
assert images[0].width == width
assert images[0].height == height
images[0].save("image_output.png")