Files

87 lines
2.8 KiB
Python
Raw Permalink Normal View History

"""
Recommended tests of diffusion features that are available in online serving mode
and are supported by the following model:
- LongCat-Image-Edit: image-to-image edit with a single image + single edit prompt input
Coverage:
- Default smoke (1 GPU)
- CPU offloading (model-level sequential offload via --enable-cpu-offload)
- Cache-DiT
- SP (Ulysses)
This validates:
- Successful image generation at the expected 1024x1024 resolution with recommended feature combinations
"""
import pytest
from tests.helpers.mark import hardware_marks
from tests.helpers.media import generate_synthetic_image
from tests.helpers.runtime import OmniServer, OmniServerParams, OpenAIClientHandler, dummy_messages_from_mix_data
pytestmark = [pytest.mark.diffusion, pytest.mark.slow]
EDIT_PROMPT = "Transform this modern image into a cinematic animation style with vibrant colors and soft lighting."
NEGATIVE_PROMPT = "blurry, low quality, distorted, oversaturated"
SINGLE_CARD_FEATURE_MARKS = hardware_marks(res={"cuda": "H100"})
PARALLEL_FEATURE_MARKS = hardware_marks(res={"cuda": "H100"}, num_cards=2)
MODEL = "meituan-longcat/LongCat-Image-Edit"
def _get_diffusion_feature_cases(model: str):
"""Return diffusion feature cases for LongCat-Image-Edit."""
return [
pytest.param(
OmniServerParams(model=model),
id="default",
marks=SINGLE_CARD_FEATURE_MARKS,
),
pytest.param(
OmniServerParams(
model=model,
server_args=["--enable-cpu-offload"],
),
id="single_card_001",
marks=SINGLE_CARD_FEATURE_MARKS,
),
pytest.param(
OmniServerParams(
model=model,
server_args=[
"--cache-backend",
"cache_dit",
"--ulysses-degree",
"2",
],
),
id="parallel_001",
marks=PARALLEL_FEATURE_MARKS,
),
]
@pytest.mark.parametrize(
"omni_server",
_get_diffusion_feature_cases(MODEL),
indirect=True,
)
def test_longcat_image_edit(omni_server: OmniServer, openai_client: OpenAIClientHandler):
"""Test the recommended feature combinations for LongCat-Image-Edit."""
image_data_url = f"data:image/jpeg;base64,{generate_synthetic_image(512, 512)['base64']}"
messages = dummy_messages_from_mix_data(image_data_url=image_data_url, content_text=EDIT_PROMPT)
request_config = {
"model": omni_server.model,
"messages": messages,
"extra_body": {
"height": 1024,
"width": 1024,
"num_inference_steps": 2,
"negative_prompt": NEGATIVE_PROMPT,
"guidance_scale": 4.0,
"seed": 42,
},
}
openai_client.send_diffusion_request(request_config)