wangyuandCursor
4616823125
Signed-off-by: wangyu <410167048@qq.com> Signed-off-by: [Your Name] <your.email@example.com> Co-authored-by: Cursor <cursoragent@cursor.com>
95 lines
3.4 KiB
Python
95 lines
3.4 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""
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Online serving tests for ``Boogu/Boogu-Image-0.1-Base`` (text-to-image).
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- ``test_text_to_image_001``: single chat request, default server (``_get_default_case``).
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- ``test_batch_001``: concurrent prompts via ``send_diffusion_request([cfg0, cfg1, ...])`` — one
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dict per prompt; each entry carries its own ``messages`` / ``negative_prompt`` (see
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``TEST_PROMPTS``).
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Boogu-Image's pipeline reads ``sp.guidance_scale`` (not ``true_cfg_scale``), so the
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``extra_body`` uses ``guidance_scale``. These are smoke tests (minimal steps); numeric
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parity vs. the Diffusers baseline is covered separately (see the support plan, step 14).
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From ``tests/``::
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pytest -s -v e2e/online_serving/test_boogu_image.py \
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-m "slow and diffusion and H100"
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"""
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import os
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import pytest
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from tests.helpers.mark import hardware_marks
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from tests.helpers.runtime import OmniServer, OmniServerParams, OpenAIClientHandler, dummy_messages_from_mix_data
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os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"
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pytestmark = [pytest.mark.diffusion, pytest.mark.slow]
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MODEL = "Boogu/Boogu-Image-0.1-Base"
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T2I_PROMPT = "A mountain lake at sunset, photorealistic, cinematic lighting"
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NEGATIVE_PROMPT = ""
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SINGLE_CARD_FEATURE_MARKS = hardware_marks(res={"cuda": "H100"})
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TEST_PROMPTS: list[dict[str, str]] = [
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{"prompt": "a cup of coffee on a table", "negative_prompt": ""},
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{"prompt": "a toy dinosaur on a sandy beach", "negative_prompt": ""},
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{"prompt": "a futuristic city skyline at sunset", "negative_prompt": ""},
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]
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def _get_default_case(model: str):
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"""Return a single default ``OmniServerParams`` row (no extra ``server_args``)."""
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return [
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pytest.param(
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OmniServerParams(model=model),
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id="default",
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marks=SINGLE_CARD_FEATURE_MARKS,
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),
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]
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@pytest.mark.parametrize("omni_server", _get_default_case(MODEL), indirect=True)
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def test_text_to_image_001(omni_server: OmniServer, openai_client: OpenAIClientHandler) -> None:
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"""Default Boogu-Image T2I smoke (single ``default`` server config)."""
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messages = dummy_messages_from_mix_data(content_text=T2I_PROMPT)
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request_config = {
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"model": omni_server.model,
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"messages": messages,
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"extra_body": {
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"height": 512,
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"width": 512,
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"num_inference_steps": 2,
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"negative_prompt": NEGATIVE_PROMPT,
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"guidance_scale": 4.0,
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"seed": 42,
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},
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}
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openai_client.send_diffusion_request(request_config)
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@pytest.mark.parametrize("omni_server", _get_default_case(MODEL), indirect=True)
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def test_batch_001(omni_server: OmniServer, openai_client: OpenAIClientHandler) -> None:
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"""Concurrent T2I: one ``request_config`` dict per prompt (``send_diffusion_request`` list mode)."""
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request_config = [
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{
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"model": omni_server.model,
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"messages": dummy_messages_from_mix_data(content_text=prompt["prompt"]),
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"extra_body": {
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"height": 512,
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"width": 512,
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"num_inference_steps": 2,
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"negative_prompt": prompt["negative_prompt"],
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"guidance_scale": 4.0,
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"seed": 42,
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},
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}
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for prompt in TEST_PROMPTS
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]
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openai_client.send_diffusion_request(request_config)
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