Hongsheng Liu
d4096e01fe
Signed-off-by: Hongsheng Liu <liuhongsheng4@huawei.com> Signed-off-by: hsliuustc0106 <liuhongsheng4@huawei.com>
78 lines
2.2 KiB
Python
78 lines
2.2 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
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"""Released-checkpoint MAGI-2 Preview serving smoke on four H100 GPUs.
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This is a one-step 272p load/dispatch test, not a quality or performance test.
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It exercises the recommended resident SP4 topology through ``/v1/videos``.
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From ``tests/``::
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pytest -s -v e2e/online_serving/test_magi2.py -m "advanced_model and diffusion" --run-level=advanced_model
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"""
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import json
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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, OnlineOmniClient
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os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"
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MODEL = "sand-ai/MAGI-2-preview"
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PROMPT = "A red fox walks through fresh snow while wind moves the pine branches."
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FOUR_CARD_MARKS = hardware_marks(res={"cuda": "H100"}, num_cards=4)
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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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@pytest.mark.parametrize(
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"omni_server",
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[
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pytest.param(
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OmniServerParams(
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model=MODEL,
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server_args=[
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"--model-class-name",
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"Magi2Pipeline",
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"--num-gpus",
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"4",
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"--tensor-parallel-size",
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"1",
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"--ulysses-degree",
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"4",
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],
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init_timeout=1800,
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),
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id="resident_sp4_272p_one_step",
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marks=FOUR_CARD_MARKS,
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)
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],
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indirect=True,
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)
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def test_magi2_preview_serving_smoke(
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omni_server: OmniServer,
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online_client: OnlineOmniClient,
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) -> None:
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request_config = {
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"model": omni_server.model,
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"form_data": {
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"prompt": PROMPT,
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"height": 256,
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"width": 448,
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"num_frames": 125,
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"fps": 12.5,
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"num_inference_steps": 1,
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"seed": 42,
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"extra_params": json.dumps({"resolution": "272p"}),
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},
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"expected_audio": {"sample_rate": 44100, "channels": 2},
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"fps_tolerance": 0.01,
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}
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online_client.send_video_diffusion_request(request_config)
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