88 lines
2.9 KiB
Python
88 lines
2.9 KiB
Python
import os
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import sys
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from pathlib import Path
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import pytest
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import torch
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from tests.utils import hardware_test
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from vllm_omni.inputs.data import OmniDiffusionSamplingParams
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from vllm_omni.outputs import OmniRequestOutput
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from vllm_omni.platforms import current_omni_platform
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# ruff: noqa: E402
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REPO_ROOT = Path(__file__).resolve().parents[2]
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if str(REPO_ROOT) not in sys.path:
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sys.path.insert(0, str(REPO_ROOT))
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from vllm_omni import Omni
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os.environ["VLLM_TEST_CLEAN_GPU_MEMORY"] = "1"
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models = ["Tongyi-MAI/Z-Image-Turbo", "riverclouds/qwen_image_random"]
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# Modelscope can't find riverclouds/qwen_image_random
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# TODO: When NPU support is ready, remove this branch.
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if current_omni_platform.is_npu():
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models = ["Tongyi-MAI/Z-Image-Turbo", "Qwen/Qwen-Image"]
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elif current_omni_platform.is_rocm():
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# TODO: When ROCm support is ready, remove this branch.
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# vLLM V0.11.0 has issues running riverclouds/qwen_image_random
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# on ROCm
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models = ["Tongyi-MAI/Z-Image-Turbo"]
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@pytest.mark.core_model
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@pytest.mark.advanced_model
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@pytest.mark.diffusion
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@hardware_test(res={"cuda": "L4", "rocm": "MI325"}, num_cards={"cuda": 1, "rocm": 2})
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@pytest.mark.parametrize("model_name", models)
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def test_diffusion_model(model_name: str, run_level):
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if run_level == "core_model" and model_name != "riverclouds/qwen_image_random":
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pytest.skip()
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if run_level == "advanced_model" and model_name == "riverclouds/qwen_image_random":
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pytest.skip()
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m = None
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try:
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m = Omni(model=model_name)
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# high resolution may cause OOM on L4
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height = 256
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width = 256
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outputs = m.generate(
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"a photo of a cat sitting on a laptop keyboard",
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OmniDiffusionSamplingParams(
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height=height,
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width=width,
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num_inference_steps=2,
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guidance_scale=0.0,
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generator=torch.Generator(current_omni_platform.device_type).manual_seed(42),
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num_outputs_per_prompt=2,
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),
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)
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# Extract images from request_output[0]['images']
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first_output = outputs[0]
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assert first_output.final_output_type == "image"
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if not hasattr(first_output, "request_output") or not first_output.request_output:
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raise ValueError("No request_output found in OmniRequestOutput")
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req_out = first_output.request_output[0]
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if not isinstance(req_out, OmniRequestOutput) or not hasattr(req_out, "images"):
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raise ValueError("Invalid request_output structure or missing 'images' key")
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images = req_out.images
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assert len(images) == 2
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# check image size
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assert images[0].width == width
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assert images[0].height == height
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images[0].save("image_output.png")
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except Exception as e:
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print(f"Test failed with error: {e}")
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raise
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finally:
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if m is not None and hasattr(m, "close"):
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m.close()
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