wangyuandHongsheng Liu
7619ed6b82
Signed-off-by: [Your Name] <your.email@example.com> Signed-off-by: wangyu <410167048@qq.com> Signed-off-by: wangyu <53896905+yenuo26@users.noreply.github.com> Signed-off-by: Hongsheng Liu <liuhongsheng4@huawei.com> Signed-off-by: [Your Name] <[Your Email]> Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>
132 lines
3.9 KiB
Python
132 lines
3.9 KiB
Python
"""
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Tests for Flux2 Klein; currently Dev is implemented separately,
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but ideally these models will fold together in the future.
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Coverage:
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- FP8 + CacheDiT + Ulysses=2 + TP=2
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- Layerwise CPU offload + Ulysses=2 + Ring=2
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- Layerwise CPU offload + TP=2
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- Layerwise CPU offload + HSDP
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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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pytestmark = [pytest.mark.diffusion, pytest.mark.slow]
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FOUR_CARD_FEATURE_MARKS = hardware_marks(res={"cuda": "L4"}, num_cards=4)
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POSITIVE_PROMPT = "A cat sitting on a windowsill"
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NEGATIVE_PROMPT = "blurry, low quality"
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# For now, we only test a good configuration for this model to keep the CI
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# light, but in the near future may explore using random models to check
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# cross-feature compatibility more generally.
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def _get_diffusion_feature_cases(model: str):
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return [
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# CPU offload + TP=2 (model needs TP=2)
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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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"--enable-cpu-offload",
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"--tensor-parallel-size",
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"2",
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],
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),
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id="cpu_offload",
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marks=FOUR_CARD_FEATURE_MARKS,
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),
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# FP8 / Hybrid sequence parallelism
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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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"--quantization",
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"fp8",
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# NOTE: TP added for test coverage here since it doesn't
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# slow things down too much, but fp8 + ulysses SP +
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# cache_dit will generally get you the highest speedup here
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"--tensor-parallel-size",
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"2",
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],
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),
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marks=FOUR_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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"--enable-layerwise-offload",
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"--ulysses-degree",
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"2",
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"--ring",
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"2",
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],
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),
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id="layerwise_ulysses2_ring2",
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marks=FOUR_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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"--enable-layerwise-offload",
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"--tensor-parallel-size",
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"2",
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],
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),
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id="layerwise_tp2",
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marks=FOUR_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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"--enable-layerwise-offload",
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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="layerwise_hsdp",
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marks=FOUR_CARD_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(
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model="black-forest-labs/FLUX.2-klein-4B",
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),
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indirect=True,
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)
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def test_flux2_klein(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": 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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