leoandleo
50b8a150f9
Signed-off-by: leo <92263211+napleon-liu@users.noreply.github.com> Signed-off-by: leo <92263211+liuyao0322@users.noreply.github.com> Signed-off-by: liuyao0322 <yaoliu548926@gmail.com> Co-authored-by: leo <92263211+napleon-liu@users.noreply.github.com>
127 lines
4.2 KiB
Python
127 lines
4.2 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""SANA-Video 2B online smoke tests for the native and Diffusers backends."""
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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.media import generate_synthetic_image
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from tests.helpers.runtime import OmniServer, OmniServerParams, OpenAIClientHandler
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pytestmark = [pytest.mark.diffusion, pytest.mark.slow]
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os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"
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MODEL_480P = os.environ.get(
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"SANA_VIDEO_480P_MODEL",
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"Efficient-Large-Model/SANA-Video_2B_480p_diffusers",
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)
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MODEL_720P = os.environ.get(
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"SANA_VIDEO_720P_MODEL",
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"Efficient-Large-Model/SANA-Video_2B_720p_diffusers",
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)
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PROMPT = "A cat walking on grass toward the camera. motion score: 30."
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NEGATIVE_PROMPT = "blurry, low quality, temporal artifacts"
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SINGLE_CARD_MARKS = hardware_marks(res={"cuda": "H100"})
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def _t2v_backend_cases():
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cases = []
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for variant, model in (("480p", MODEL_480P), ("720p", MODEL_720P)):
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cases.extend(
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[
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pytest.param(
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OmniServerParams(model=model, server_args=["--model-class-name", "SanaVideoPipeline"]),
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id=f"native-{variant}",
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marks=SINGLE_CARD_MARKS,
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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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"--diffusion-load-format",
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"diffusers",
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"--diffusion-attention-backend",
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"TORCH_SDPA",
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],
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),
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id=f"diffusers-adapter-{variant}",
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marks=SINGLE_CARD_MARKS,
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),
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]
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)
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return cases
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@pytest.mark.parametrize("omni_server", _t2v_backend_cases(), indirect=True)
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def test_sana_video_t2v_backends(omni_server: OmniServer, openai_client: OpenAIClientHandler) -> 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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"negative_prompt": NEGATIVE_PROMPT,
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"height": 192,
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"width": 320,
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"num_frames": 9,
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"fps": 8,
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"num_inference_steps": 2,
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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_video_diffusion_request(request_config)
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def _i2v_cases():
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cases = []
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for variant, model in (("480p", MODEL_480P), ("720p", MODEL_720P)):
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cases.extend(
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[
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pytest.param(
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OmniServerParams(model=model, server_args=["--model-class-name", "SanaImageToVideoPipeline"]),
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id=f"native-{variant}",
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marks=SINGLE_CARD_MARKS,
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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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"SanaImageToVideoPipeline",
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"--diffusion-load-format",
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"diffusers",
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"--diffusion-attention-backend",
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"TORCH_SDPA",
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],
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),
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id=f"diffusers-adapter-{variant}",
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marks=SINGLE_CARD_MARKS,
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),
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]
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)
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return cases
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@pytest.mark.parametrize("omni_server", _i2v_cases(), indirect=True)
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def test_sana_video_i2v_variants(omni_server: OmniServer, openai_client: OpenAIClientHandler) -> 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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"negative_prompt": NEGATIVE_PROMPT,
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"height": 192,
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"width": 320,
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"num_frames": 9,
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"fps": 8,
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"num_inference_steps": 2,
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"guidance_scale": 4.0,
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"seed": 42,
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},
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"image_reference": (f"data:image/jpeg;base64,{generate_synthetic_image(320, 192, seed=42)['base64']}"),
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}
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openai_client.send_video_diffusion_request(request_config)
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