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[Hunyuanimage-3.0] Accuracy fix #3373

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Merged
gcanlin merged 2 commits into from
May 6, 2026
Merged

[Hunyuanimage-3.0] Accuracy fix #3373

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99c43eb
accuracy fix
Bounty-hunter May 6, 2026
b2b292e
Merge branch 'main' into main_5_5_adapt
Bounty-hunter May 6, 2026
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2 changes: 1 addition & 1 deletion examples/offline_inference/hunyuan_image3/end2end.py
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Original file line number Diff line number Diff line change
Expand Up @@ -149,7 +149,7 @@ def main():
for p in prompts:
token_ids = build_prompt_tokens(p, tokenizer, task=task, sys_type=args.sys_type)

prompt_dict: dict = {"prompt_token_ids": token_ids}
prompt_dict: dict = {"prompt_token_ids": token_ids, "prompt": p}

if args.modality == "text2img":
prompt_dict["modalities"] = ["image"]
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6 changes: 0 additions & 6 deletions vllm_omni/diffusion/models/hunyuan_image3/hunyuan_fused_moe.py
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Expand Up @@ -29,12 +29,6 @@ class HunyuanFusedMoEDefault(FusedMoE):
def __init__(self, *, prefix: str = "", **kwargs: Any) -> None:
super().__init__(prefix=prefix, **kwargs)
self._prefix = prefix
self._init_hook_handle = self.register_forward_pre_hook(self._initialize_kernel_hook, with_kwargs=True)

def _initialize_kernel_hook(self, module: Any, args: Any, kwargs: Any) -> None:
if self.quant_method:
self.quant_method.process_weights_after_loading(self)
self._init_hook_handle.remove()

def forward(self, hidden_states: Any, router_logits: Any) -> Any:
_set_forward_context_num_tokens(hidden_states.shape[0])
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6 changes: 0 additions & 6 deletions vllm_omni/diffusion/models/hunyuan_image3/hunyuan_image3_transformer.py
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Expand Up @@ -1514,7 +1514,6 @@ def __init__(
top_k=top_k,
hidden_size=config.hidden_size,
intermediate_size=intermediate_size,
reduce_results=False,
renormalize=top_k > 1,
quant_config=quant_config,
prefix=f"{prefix}.experts",
Expand All @@ -1532,11 +1531,6 @@ def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
# router_logits: (num_tokens, n_experts)
router_logits, _ = self.gate(hidden_states)
final_hidden_states = self.experts(hidden_states=hidden_states, router_logits=router_logits)
if self.shared_mlp is not None:
final_hidden_states = final_hidden_states[0] + final_hidden_states[1]

if self.tp_size > 1:
final_hidden_states = self.experts.maybe_all_reduce_tensor_model_parallel(final_hidden_states)

return final_hidden_states.view(orig_shape)

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6 changes: 2 additions & 4 deletions vllm_omni/diffusion/models/hunyuan_image3/pipeline_hunyuan_image3.py
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Expand Up @@ -11,7 +11,6 @@
from diffusers.schedulers.scheduling_flow_match_euler_discrete import FlowMatchEulerDiscreteScheduler
from transformers.generation.configuration_utils import GenerationConfig
from transformers.generation.utils import ALL_CACHE_NAMES, GenerationMixin
from transformers.models.siglip2 import Siglip2VisionConfig, Siglip2VisionModel
from transformers.utils.generic import ModelOutput
from vllm.config.vllm import get_current_vllm_config
from vllm.model_executor.models.utils import AutoWeightsLoader, WeightsMapper
Expand All @@ -22,6 +21,7 @@
from vllm_omni.diffusion.model_loader.diffusers_loader import DiffusersPipelineLoader
from vllm_omni.diffusion.profiler.diffusion_pipeline_profiler import DiffusionPipelineProfilerMixin
from vllm_omni.diffusion.request import OmniDiffusionRequest
from vllm_omni.model_executor.models.hunyuan_image3.siglip2 import Siglip2VisionTransformer

from .autoencoder import AutoencoderKLConv3D
from .hunyuan_image3_tokenizer import TokenizerWrapper
Expand Down Expand Up @@ -111,9 +111,7 @@ def __init__(self, od_config: OmniDiffusionConfig) -> None:
self._pipeline = None
self._tkwrapper = TokenizerWrapper(od_config.model)
self.image_processor = HunyuanImage3ImageProcessor(self.hf_config)
self.hf_config.vit.pop("use_return_dict", None)
vision_config = Siglip2VisionConfig(**self.hf_config.vit)
self.vision_model = Siglip2VisionModel(vision_config).vision_model
self.vision_model = Siglip2VisionTransformer(self.hf_config.vit)
# self.vision_model = vision_model.vision_model
self.vision_aligner = LightProjector(self.hf_config.vit_aligner)
self.timestep_emb = TimestepEmbedder(hidden_size=self.hf_config.hidden_size)
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