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[diffusion] feat: support resolution check for video model (#14881)

Browse Source 
Co-authored-by: Brain97 <Brain97@users.noreply.github.com>
Co-authored-by: Mick <mickjagger19@icloud.com>
This commit is contained in:
blahblah
2025-12-14 17:50:13 +08:00
committed by GitHub
parent 5c75907e62
commit 19c16748ce
11 changed files with 469 additions and 377 deletions
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18
python/sglang/multimodal_gen/configs/sample/hunyuan.py
View File

@@ -18,6 +18,24 @@ class HunyuanSamplingParams(SamplingParams):
guidance_scale: float = 1.0
# HunyuanVideo supported resolutions
supported_resolutions: list[tuple[int, int]] | None = field(
default_factory=lambda: [
# 540p resolutions
(960, 544), # 9:16
(544, 960), # 16:9
(832, 624), # 4:3
(624, 832), # 3:4
(720, 720), # 1:1
# 720p resolutions (recommended)
(1280, 720), # 9:16
(720, 1280), # 16:9
(832, 1104), # 4:3
(1104, 832), # 3:4
(960, 960), # 1:1
]
)
teacache_params: TeaCacheParams = field(
default_factory=lambda: TeaCacheParams(
teacache_thresh=0.15,

30
python/sglang/multimodal_gen/configs/sample/sampling_params.py
View File

@@ -115,6 +115,11 @@ class SamplingParams:
width_not_provided: bool = False
fps: int = 24
# Resolution validation
supported_resolutions: list[tuple[int, int]] | None = (
None # None means all resolutions allowed
)
# Denoising parameters
num_inference_steps: int = None
guidance_scale: float = None
@@ -223,6 +228,27 @@ class SamplingParams:
f"num_frames={self.num_frames}"
)
# Validate resolution against pipeline-specific supported resolutions
if self.height is None and self.width is None:
if self.supported_resolutions is not None:
self.width, self.height = self.supported_resolutions[0]
logger.info(
f"Resolution unspecified, using default: {self.supported_resolutions[0]}"
)
if self.height is not None and self.width is not None:
if self.supported_resolutions is not None:
if (self.width, self.height) not in self.supported_resolutions:
supported_str = ", ".join(
[f"{w}x{h}" for w, h in self.supported_resolutions]
)
error_msg = (
f"Unsupported resolution: {self.width}x{self.height}. "
f"Supported resolutions: {supported_str}"
)
logger.error(error_msg)
raise ValueError(error_msg)
if pipeline_config.task_type.is_image_gen():
# settle num_frames
logger.debug(f"Setting num_frames to 1 because this is an image-gen model")
@@ -558,7 +584,9 @@ class SamplingParams:
args.width = 1280
args.height = 720
attrs = [attr.name for attr in dataclasses.fields(cls)]
sampling_params_fields = {attr.name for attr in dataclasses.fields(cls)}
args_attrs = set(vars(args).keys())
attrs = sampling_params_fields & args_attrs
args.height_not_provided = False
args.width_not_provided = False
return {attr: getattr(args, attr) for attr in attrs}

64
python/sglang/multimodal_gen/configs/sample/wan.py
View File

@@ -22,6 +22,14 @@ class WanT2V_1_3B_SamplingParams(SamplingParams):
)
num_inference_steps: int = 50
# Wan T2V 1.3B supported resolutions
supported_resolutions: list[tuple[int, int]] | None = field(
default_factory=lambda: [
(832, 480), # 16:9
(480, 832), # 9:16
]
)
teacache_params: WanTeaCacheParams = field(
default_factory=lambda: WanTeaCacheParams(
teacache_thresh=0.08,
@@ -58,6 +66,16 @@ class WanT2V_14B_SamplingParams(SamplingParams):
)
num_inference_steps: int = 50
# Wan T2V 14B supported resolutions
supported_resolutions: list[tuple[int, int]] | None = field(
default_factory=lambda: [
(1280, 720), # 16:9
(720, 1280), # 9:16
(832, 480), # 16:9
(480, 832), # 9:16
]
)
teacache_params: WanTeaCacheParams = field(
default_factory=lambda: WanTeaCacheParams(
teacache_thresh=0.20,
@@ -87,6 +105,14 @@ class WanI2V_14B_480P_SamplingParam(WanT2V_1_3B_SamplingParams):
num_inference_steps: int = 50
# num_inference_steps: int = 40
# Wan I2V 480P supported resolutions (override parent)
supported_resolutions: list[tuple[int, int]] | None = field(
default_factory=lambda: [
(832, 480), # 16:9
(480, 832), # 9:16
]
)
teacache_params: WanTeaCacheParams = field(
default_factory=lambda: WanTeaCacheParams(
teacache_thresh=0.26,
@@ -115,6 +141,16 @@ class WanI2V_14B_720P_SamplingParam(WanT2V_14B_SamplingParams):
num_inference_steps: int = 50
# num_inference_steps: int = 40
# Wan I2V 720P supported resolutions (override parent)
supported_resolutions: list[tuple[int, int]] | None = field(
default_factory=lambda: [
(1280, 720), # 16:9
(720, 1280), # 9:16
(832, 480), # 16:9
(480, 832), # 9:16
]
)
teacache_params: WanTeaCacheParams = field(
default_factory=lambda: WanTeaCacheParams(
teacache_thresh=0.3,
@@ -188,6 +224,14 @@ class Wan2_2_TI2V_5B_SamplingParam(Wan2_2_Base_SamplingParams):
guidance_scale: float = 5.0
num_inference_steps: int = 50
# Wan2.2 TI2V 5B supported resolutions
supported_resolutions: list[tuple[int, int]] | None = field(
default_factory=lambda: [
(1280, 704), # 16:9-ish
(704, 1280), # 9:16-ish
]
)
@dataclass
class Wan2_2_T2V_A14B_SamplingParam(Wan2_2_Base_SamplingParams):
@@ -198,6 +242,16 @@ class Wan2_2_T2V_A14B_SamplingParam(Wan2_2_Base_SamplingParams):
# NOTE(will): default boundary timestep is tracked by PipelineConfig, but
# can be overridden during sampling
# Wan2.2 T2V A14B supported resolutions
supported_resolutions: list[tuple[int, int]] | None = field(
default_factory=lambda: [
(1280, 720), # 16:9
(720, 1280), # 9:16
(832, 480), # 16:9
(480, 832), # 9:16
]
)
@dataclass
class Wan2_2_I2V_A14B_SamplingParam(Wan2_2_Base_SamplingParams):
@@ -208,6 +262,16 @@ class Wan2_2_I2V_A14B_SamplingParam(Wan2_2_Base_SamplingParams):
# NOTE(will): default boundary timestep is tracked by PipelineConfig, but
# can be overridden during sampling
# Wan2.2 I2V A14B supported resolutions
supported_resolutions: list[tuple[int, int]] | None = field(
default_factory=lambda: [
(1280, 720), # 16:9
(720, 1280), # 9:16
(832, 480), # 16:9
(480, 832), # 9:16
]
)
# =============================================
# ============= Causal Self-Forcing =============

18
python/sglang/multimodal_gen/runtime/entrypoints/http_server.py
View File

@@ -6,8 +6,7 @@ from contextlib import asynccontextmanager
from fastapi import APIRouter, FastAPI
from sglang.multimodal_gen.runtime.entrypoints.openai import image_api, video_api
from sglang.multimodal_gen.runtime.server_args import ServerArgs, prepare_server_args
from sglang.multimodal_gen.runtime.utils.logging_utils import configure_logger
from sglang.multimodal_gen.runtime.server_args import ServerArgs
@asynccontextmanager
@@ -63,18 +62,3 @@ def create_app(server_args: ServerArgs):
app.state.server_args = server_args
return app
if __name__ == "__main__":
import uvicorn
server_args = prepare_server_args([])
configure_logger(server_args)
app = create_app(server_args)
uvicorn.run(
app,
host=server_args.host,
port=server_args.port,
use_colors=True,
reload=False, # Set to True during development for auto-reloading
)

4
python/sglang/multimodal_gen/runtime/entrypoints/openai/protocol.py
View File

@@ -39,7 +39,7 @@ class VideoResponse(BaseModel):
status: str = "queued"
progress: int = 0
created_at: int = Field(default_factory=lambda: int(time.time()))
size: str = "720x1280"
size: str = ""
seconds: str = "4"
quality: str = "standard"
remixed_from_video_id: Optional[str] = None
@@ -53,7 +53,7 @@ class VideoGenerationsRequest(BaseModel):
input_reference: Optional[str] = None
model: Optional[str] = None
seconds: Optional[int] = 4
size: Optional[str] = "720x1280"
size: Optional[str] = ""
fps: Optional[int] = None
num_frames: Optional[int] = None
seed: Optional[int] = 1024

4
python/sglang/multimodal_gen/runtime/entrypoints/openai/utils.py
View File

@@ -79,7 +79,7 @@ def post_process_sample(
return frames
def _parse_size(size: str) -> tuple[int, int]:
def _parse_size(size: str) -> tuple[int, int] | tuple[None, None]:
try:
parts = size.lower().replace(" ", "").split("x")
if len(parts) != 2:
@@ -88,7 +88,7 @@ def _parse_size(size: str) -> tuple[int, int]:
return w, h
except Exception:
# Fallback to default portrait 720x1280
return 720, 1280
return None, None
# Helpers

2
python/sglang/multimodal_gen/runtime/entrypoints/openai/video_api.py
View File

@@ -166,7 +166,7 @@ async def create_video(
input_reference=input_path,
model=model,
seconds=seconds if seconds is not None else 4,
size=size or "720x1280",
size=size,
fps=fps_val,
num_frames=num_frames_val,
)

1
python/sglang/multimodal_gen/test/run_suite.py
View File

@@ -117,6 +117,7 @@ def run_pytest(files):
if not is_perf_assertion:
return returncode
logger.info(f"Max retry exceeded")
return returncode

695
python/sglang/multimodal_gen/test/server/perf_baselines.json
View File

@@ -523,70 +523,70 @@
},
"wan2_1_t2v_1.3b": {
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"TextEncodingStage": 3595.12,
"ConditioningStage": 0.02,
"TimestepPreparationStage": 2.39,
"LatentPreparationStage": 15.27,
"DenoisingStage": 91099.4,
"DecodingStage": 4330.65,
"InputValidationStage": 0.07,
"TextEncodingStage": 2237.78,
"ConditioningStage": 0.01,
"TimestepPreparationStage": 2.1,
"LatentPreparationStage": 0.84,
"DenoisingStage": 13041.23,
"DecodingStage": 1274.63,
"per_frame_generation": null
},
"denoise_step_ms": {
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"expected_avg_denoise_ms": 260.76,
"expected_median_denoise_ms": 247.84
},
"wan2_2_ti2v_5b": {
"stages_ms": {
@@ -677,82 +677,84 @@
},
"fast_hunyuan_video": {
"stages_ms": {
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"TextEncodingStage": 845.64,
"ConditioningStage": 0.04,
"TimestepPreparationStage": 125.22,
"LatentPreparationStage": 29.34,
"DenoisingStage": 3860.64,
"DecodingStage": 2580.55
"InputValidationStage": 0.34,
"TextEncodingStage": 550.63,
"ConditioningStage": 0.02,
"TimestepPreparationStage": 44.28,
"LatentPreparationStage": 0.29,
"DenoisingStage": 9054.39,
"DecodingStage": 5995.09,
"per_frame_generation": null
},
"denoise_step_ms": {
"0": 2063.08,
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"1": 578.59,
"2": 1485.76,
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},
"expected_e2e_ms": 7487.87,
"expected_avg_denoise_ms": 642.29,
"expected_median_denoise_ms": 407.25
"expected_e2e_ms": 15672.15,
"expected_avg_denoise_ms": 1508.46,
"expected_median_denoise_ms": 1488.48
},
"wan2_2_i2v_a14b_2gpu": {
"stages_ms": {
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"TextEncodingStage": 6062.41,
"ConditioningStage": 0.02,
"TimestepPreparationStage": 2.2,
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"LatentPreparationStage": 1.25,
"ImageVAEEncodingStage": 1655.89,
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},
"wan2_1_i2v_14b_480P_2gpu": {
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@@ -894,58 +896,59 @@
"wan2_2_t2v_a14b_2gpu": {
"stages_ms": {
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"TextEncodingStage": 2507.83,
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"ConditioningStage": 0.01,
"TimestepPreparationStage": 1.99,
"LatentPreparationStage": 1.26,
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@@ -1016,196 +1019,196 @@
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"12": 2408.27,
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"14": 2405.92,
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"26": 36387.55,
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"expected_e2e_ms": 84633.71,
"expected_avg_denoise_ms": 2006.04,
"expected_median_denoise_ms": 758.24
"expected_e2e_ms": 159643.06,
"expected_avg_denoise_ms": 3851.87,
"expected_median_denoise_ms": 2400.09
},
"wan2_1_t2v_1_3b_lora_1gpu": {
"stages_ms": {
"InputValidationStage": 0.08,
"TextEncodingStage": 2392.95,
"InputValidationStage": 0.06,
"TextEncodingStage": 2467.44,
"ConditioningStage": 0.02,
"TimestepPreparationStage": 2.19,
"LatentPreparationStage": 1.28,
"DenoisingStage": 8752.65,
"DecodingStage": 743.42,
"TimestepPreparationStage": 2.96,
"LatentPreparationStage": 1.87,
"DenoisingStage": 14859.47,
"DecodingStage": 1199.31,
"per_frame_generation": null
},
"denoise_step_ms": {
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"1": 149.53,
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"3": 143.89,
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"32": 145.89,
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"expected_e2e_ms": 11905.69,
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"expected_median_denoise_ms": 142.57
"expected_e2e_ms": 18547.46,
"expected_avg_denoise_ms": 297.09,
"expected_median_denoise_ms": 257.42
},
"wan2_1_i2v_14b_lora_2gpu": {
"stages_ms": {
"InputValidationStage": 37.9,
"TextEncodingStage": 2581.79,
"ImageEncodingStage": 1607.56,
"InputValidationStage": 23.97,
"TextEncodingStage": 2485.39,
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"DenoisingStage": 188146.58,
"DecodingStage": 3392.12,
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"expected_avg_denoise_ms": 3751.95,
"expected_median_denoise_ms": 3724.06
"expected_e2e_ms": 204257.12,
"expected_avg_denoise_ms": 3855.55,
"expected_median_denoise_ms": 3774.03
}
}
}

1
python/sglang/multimodal_gen/test/server/test_server_common.py
View File

@@ -491,6 +491,7 @@ Consider updating perf_baselines.json with the snippets below:
case.id,
generate_fn,
)
self._validate_and_record(case, perf_record)
# LoRA API functionality test with E2E validation (only for LoRA-enabled cases)

9
python/sglang/multimodal_gen/test/server/testcase_configs.py
View File

@@ -227,7 +227,6 @@ TI2I_sampling_params = DiffusionSamplingParams(
T2V_PROMPT = "A curious raccoon"
TI2V_sampling_params = DiffusionSamplingParams(
output_size="832x1104",
prompt="The man in the picture slowly turns his head, his expression enigmatic and otherworldly. The camera performs a slow, cinematic dolly out, focusing on his face. Moody lighting, neon signs glowing in the background, shallow depth of field.",
image_path="https://is1-ssl.mzstatic.com/image/thumb/Music114/v4/5f/fa/56/5ffa56c2-ea1f-7a17-6bad-192ff9b6476d/825646124206.jpg/600x600bb.jpg",
)
@@ -302,7 +301,6 @@ ONE_GPU_CASES_B: list[DiffusionTestCase] = [
),
DiffusionSamplingParams(
prompt=T2V_PROMPT,
output_size="848x480",
),
),
# LoRA test case for single transformer + merge/unmerge API test
@@ -319,7 +317,6 @@ ONE_GPU_CASES_B: list[DiffusionTestCase] = [
),
DiffusionSamplingParams(
prompt="csetiarcane Nfj1nx with blue hair, a woman walking in a cyberpunk city at night",
output_size="480x320",
num_frames=8,
),
),
@@ -355,7 +352,6 @@ ONE_GPU_CASES_B: list[DiffusionTestCase] = [
),
DiffusionSamplingParams(
prompt=T2V_PROMPT,
output_size="720x480",
),
),
# === Text and Image to Video (TI2V) ===
@@ -384,7 +380,6 @@ ONE_GPU_CASES_B: list[DiffusionTestCase] = [
]
TWO_GPU_CASES_A = [
# TODO: Timeout with Torch2.9. Add back when it can pass CI
DiffusionTestCase(
"wan2_2_i2v_a14b_2gpu",
DiffusionServerArgs(
@@ -408,7 +403,6 @@ TWO_GPU_CASES_A = [
),
DiffusionSamplingParams(
prompt=T2V_PROMPT,
output_size="720x480",
),
),
# LoRA test case for transformer_2 support
@@ -425,7 +419,6 @@ TWO_GPU_CASES_A = [
),
DiffusionSamplingParams(
prompt="Nfj1nx with blue hair, a woman walking in a cyberpunk city at night",
output_size="720x480",
),
),
DiffusionTestCase(
@@ -440,7 +433,7 @@ TWO_GPU_CASES_A = [
),
DiffusionSamplingParams(
prompt=T2V_PROMPT,
output_size="720x480",
output_size="832x480",
),
),
]