wangyuandHuang, Zeyu
6f2ad7b403
Signed-off-by: wangyu <410167048@qq.com> Signed-off-by: Huang, Zeyu <11222265+fhfuih@users.noreply.github.com> Signed-off-by: wangyu <53896905+yenuo26@users.noreply.github.com> Co-authored-by: Huang, Zeyu <11222265+fhfuih@users.noreply.github.com>
62 lines
1.7 KiB
Python
62 lines
1.7 KiB
Python
"""
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Tests for Stable Diffusion 3.5 medium model.
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"""
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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 (
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OmniServer,
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OmniServerParams,
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OpenAIClientHandler,
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dummy_messages_from_mix_data,
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)
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FOUR_CARD_FEATURE_MARKS = hardware_marks(res={"cuda": "L4"}, num_cards=4)
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POSITIVE_PROMPT = "A serene mountain landscape at sunset"
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NEGATIVE_PROMPT = "blurry, low quality, distorted"
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# For now, we only test one or two good configurations for this model to keep
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# the CI light. The test cases focus on the most common feature combinations
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# that provide good performance improvements.
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def _get_diffusion_feature_cases(model: str):
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return [
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# Cache-DiT + CFG Parallel + Tensor Parallel
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pytest.param(
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OmniServerParams(
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model=model,
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),
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id="default",
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marks=FOUR_CARD_FEATURE_MARKS,
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),
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]
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@pytest.mark.advanced_model
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@pytest.mark.core_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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_get_diffusion_feature_cases(
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model="stabilityai/stable-diffusion-3.5-medium",
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),
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indirect=True,
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)
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def test_text_to_image_001(omni_server: OmniServer, openai_client: OpenAIClientHandler):
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messages = dummy_messages_from_mix_data(content_text=POSITIVE_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": 1024,
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"width": 1024,
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"num_inference_steps": 28,
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"negative_prompt": NEGATIVE_PROMPT,
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"guidance_scale": 4.5,
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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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