5f95115e70
Signed-off-by: leffff <levnovitskiy@gmail.com> Signed-off-by: Artem Borisov <divotionchannel@gmail.com> Co-authored-by: leffff <levnovitskiy@gmail.com> Co-authored-by: Artem Borisov <divotionchannel@gmail.com>
80 lines
2.2 KiB
Python
80 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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"""Offline smoke for Kandinsky 6 TI2VA.
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Short request (256x256, 5 frames, 2 steps) so it finishes inside the default
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online poll window. Pro geometry (480x864, 125 frames, 50 steps) stays the
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serving default, not this smoke.
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"""
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import os
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from pathlib import Path
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import pytest
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from tests.helpers.mark import hardware_test
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from tests.helpers.runtime import OfflineOmniClient, get_model_prefix
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from vllm_omni.inputs.data import OmniDiffusionSamplingParams
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_HUB_MODEL = "kandinskylab/Kandinsky-6.0-Pro-5s-Diffusers"
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_LOCAL_BUNDLE = Path(__file__).resolve().parents[4] / "kandinsky6_bundle"
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def _resolve_model() -> str:
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env = os.environ.get("KANDINSKY6_MODEL")
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if env:
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return env
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if _LOCAL_BUNDLE.is_dir():
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return str(_LOCAL_BUNDLE)
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return _HUB_MODEL
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def _checkpoint_on_disk(model: str) -> bool:
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if Path(model).is_dir():
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return True
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prefix = get_model_prefix()
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return bool(prefix) and Path(prefix + model).is_dir()
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MODEL = _resolve_model()
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PROMPT = "A golden retriever runs along a sunny beach, waves crashing."
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pytestmark = [
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pytest.mark.skipif(
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not _checkpoint_on_disk(MODEL),
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reason=(
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"Kandinsky 6 Diffusers weights are gated. Set KANDINSKY6_MODEL or "
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"MODEL_PREFIX to a local copy of "
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"kandinskylab/Kandinsky-6.0-Pro-5s-Diffusers."
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),
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),
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]
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@pytest.mark.advanced_model
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@pytest.mark.diffusion
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@hardware_test(res={"cuda": "H100"}, num_cards={"cuda": 1})
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@pytest.mark.parametrize(
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"omni_runner",
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[(MODEL, None, {"enable_cpu_offload": True, "enforce_eager": True})],
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indirect=True,
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)
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def test_text_to_video_and_audio_001(offline_client: OfflineOmniClient):
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sampling = OmniDiffusionSamplingParams(
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height=256,
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width=256,
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num_frames=5,
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fps=24,
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num_inference_steps=2,
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guidance_scale=5.0,
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seed=42,
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extra_args={"sample_audio": True},
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)
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request_config = {
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"model": MODEL,
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"prompt": PROMPT,
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"sampling_params": sampling,
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}
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offline_client.send_diffusion_request(request_config)
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