170 lines
5.7 KiB
Python
170 lines
5.7 KiB
Python
"""
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Comprehensive tests of diffusion features that are available in online serving mode
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and are supported by the following models:
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- Qwen-Image-Edit: single image input
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- Qwen-Image-Edit-2509: two image inputs
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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.media import generate_synthetic_image
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from tests.helpers.runtime import OmniServer, OmniServerParams, OpenAIClientHandler, dummy_messages_from_mix_data
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pytestmark = [pytest.mark.diffusion, pytest.mark.full_model]
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EDIT_PROMPT = "Transform this modern, geometrist image into a Vincent van Gogh style impressionist painting."
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MULTI_EDIT_PROMPT = (
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"Transform the first image into a Dadaism collage art. "
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"Transform the second image into a Vincent van Gogh style painting. "
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"Then juxtapose the two transformed images into a single artwork for visual contrast."
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)
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NEGATIVE_PROMPT = "blurry, low quality, modern, geometrist"
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SINGLE_CARD_FEATURE_MARKS = hardware_marks(res={"cuda": "H100"})
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PARALLEL_FEATURE_MARKS = hardware_marks(res={"cuda": "H100"}, num_cards=2)
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# This test file targets two models, so I write a helper function.
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# If a similar test only involves one model, one can just define a global list variable.
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def _get_diffusion_feature_cases(model: str):
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return [
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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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"--cache-backend",
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"tea_cache", # [TODO] may consider changing to cache_dit after #1779 is resolved. Currently cache_dit and layerwise offload cannot work together.
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"--enable-layerwise-offload",
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],
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),
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id="single_card_001",
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marks=SINGLE_CARD_FEATURE_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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"--cache-backend",
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"cache_dit",
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"--ulysses-degree",
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"2",
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],
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),
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id="parallel_001",
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marks=PARALLEL_FEATURE_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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"--cache-backend",
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"cache_dit",
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"--ring",
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"2",
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],
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),
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id="parallel_002",
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marks=PARALLEL_FEATURE_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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"--cache-backend",
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"tea_cache",
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"--cfg-parallel-size",
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"2",
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],
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),
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id="parallel_003",
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marks=PARALLEL_FEATURE_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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"--cache-backend",
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"cache_dit",
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"--tensor-parallel-size",
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"2",
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"--vae-patch-parallel-size",
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"2",
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"--vae-use-tiling",
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],
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),
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id="parallel_004",
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marks=PARALLEL_FEATURE_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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"--use-hsdp",
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"--hsdp-shard-size",
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"2",
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],
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),
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id="parallel_005",
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marks=PARALLEL_FEATURE_MARKS,
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),
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]
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@pytest.mark.parametrize(
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"omni_server",
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_get_diffusion_feature_cases("Qwen/Qwen-Image-Edit"),
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indirect=True,
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)
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def test_qwen_image_edit(omni_server: OmniServer, openai_client: OpenAIClientHandler):
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"""Test all diffusion features with Qwen-Image-Edit in regular end-user scenarios."""
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image_data_url = f"data:image/jpeg;base64,{generate_synthetic_image(512, 512)['base64']}"
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messages = dummy_messages_from_mix_data(image_data_url=image_data_url, content_text=EDIT_PROMPT)
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# CFG parallel is only activated when a negative prompt and true_cfg_scale > 1.0 are both present
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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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"true_cfg_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(
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"omni_server",
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_get_diffusion_feature_cases("Qwen/Qwen-Image-Edit-2509"),
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indirect=True,
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)
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def test_qwen_image_edit_2509(omni_server: OmniServer, openai_client: OpenAIClientHandler):
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"""Test all diffusion features with Qwen-Image-Edit-2509 in regular end-user scenarios."""
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image_data_url_1 = f"data:image/jpeg;base64,{generate_synthetic_image(512, 512)['base64']}"
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image_data_url_2 = f"data:image/jpeg;base64,{generate_synthetic_image(512, 512)['base64']}"
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messages = dummy_messages_from_mix_data(
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image_data_url=[image_data_url_1, image_data_url_2], content_text=MULTI_EDIT_PROMPT
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)
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# CFG parallel is only activated when a negative prompt and true_cfg_scale > 1.0 are both present
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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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"true_cfg_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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