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Fix for HunyuanVideo1.5 meanflow distil (#11212)

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Jukka Seppänen 2025-12-09 23:59:16 +02:00 committed by GitHub
parent 9d252f3b70
commit e2a800e7ef
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2 changed files with 4 additions and 1 deletions
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3
comfy/ldm/hunyuan_video/model.py
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@ -43,6 +43,7 @@ class HunyuanVideoParams:
meanflow: bool meanflow: bool
use_cond_type_embedding: bool use_cond_type_embedding: bool
vision_in_dim: int vision_in_dim: int
meanflow_sum: bool
class SelfAttentionRef(nn.Module): class SelfAttentionRef(nn.Module):
@ -317,7 +318,7 @@ class HunyuanVideo(nn.Module):
timesteps_r = transformer_options['sample_sigmas'][w[0] + 1] timesteps_r = transformer_options['sample_sigmas'][w[0] + 1]
timesteps_r = timesteps_r.unsqueeze(0).to(device=timesteps.device, dtype=timesteps.dtype) timesteps_r = timesteps_r.unsqueeze(0).to(device=timesteps.device, dtype=timesteps.dtype)
vec_r = self.time_r_in(timestep_embedding(timesteps_r, 256, time_factor=1000.0).to(img.dtype)) vec_r = self.time_r_in(timestep_embedding(timesteps_r, 256, time_factor=1000.0).to(img.dtype))
vec = (vec + vec_r) / 2 vec = (vec + vec_r) if self.params.meanflow_sum else (vec + vec_r) / 2
if ref_latent is not None: if ref_latent is not None:
ref_latent_ids = self.img_ids(ref_latent) ref_latent_ids = self.img_ids(ref_latent)

2
comfy/model_detection.py
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@ -180,8 +180,10 @@ def detect_unet_config(state_dict, key_prefix, metadata=None):
dit_config["use_cond_type_embedding"] = False dit_config["use_cond_type_embedding"] = False
if '{}vision_in.proj.0.weight'.format(key_prefix) in state_dict_keys: if '{}vision_in.proj.0.weight'.format(key_prefix) in state_dict_keys:
dit_config["vision_in_dim"] = state_dict['{}vision_in.proj.0.weight'.format(key_prefix)].shape[0] dit_config["vision_in_dim"] = state_dict['{}vision_in.proj.0.weight'.format(key_prefix)].shape[0]
dit_config["meanflow_sum"] = True
else: else:
dit_config["vision_in_dim"] = None dit_config["vision_in_dim"] = None
dit_config["meanflow_sum"] = False
return dit_config return dit_config
if '{}double_blocks.0.img_attn.norm.key_norm.scale'.format(key_prefix) in state_dict_keys and ('{}img_in.weight'.format(key_prefix) in state_dict_keys or f"{key_prefix}distilled_guidance_layer.norms.0.scale" in state_dict_keys): #Flux, Chroma or Chroma Radiance (has no img_in.weight) if '{}double_blocks.0.img_attn.norm.key_norm.scale'.format(key_prefix) in state_dict_keys and ('{}img_in.weight'.format(key_prefix) in state_dict_keys or f"{key_prefix}distilled_guidance_layer.norms.0.scale" in state_dict_keys): #Flux, Chroma or Chroma Radiance (has no img_in.weight)