Support Multi/InfiniteTalk (#10179)

* re-init

* Update model_multitalk.py

* whitespace...

* Update model_multitalk.py

* remove print

* this is redundant

* remove import

* Restore preview functionality

* Move block_idx to transformer_options

* Remove LoopingSamplerCustomAdvanced

* Remove looping functionality, keep extension functionality

* Update model_multitalk.py

* Handle ref_attn_mask with separate patch to avoid having to always return q and k from self_attn

* Chunk attention map calculation for multiple speakers to reduce peak VRAM usage

* Update model_multitalk.py

* Add ModelPatch type back

* Fix for latest upstream

* Use DynamicCombo for cleaner node

Basically just so that single_speaker mode hides mask inputs and 2nd audio input

* Update nodes_wan.py
This commit is contained in:
Jukka Seppänen
2026-01-22 06:09:48 +02:00
committed by GitHub
parent 245f6139b6
commit 16b9aabd52
5 changed files with 727 additions and 3 deletions

View File

@@ -7,6 +7,7 @@ import comfy.model_management
import comfy.ldm.common_dit
import comfy.latent_formats
import comfy.ldm.lumina.controlnet
from comfy.ldm.wan.model_multitalk import WanMultiTalkAttentionBlock, MultiTalkAudioProjModel
class BlockWiseControlBlock(torch.nn.Module):
@@ -257,6 +258,14 @@ class ModelPatchLoader:
if torch.count_nonzero(ref_weight) == 0:
config['broken'] = True
model = comfy.ldm.lumina.controlnet.ZImage_Control(device=comfy.model_management.unet_offload_device(), dtype=dtype, operations=comfy.ops.manual_cast, **config)
elif "audio_proj.proj1.weight" in sd:
model = MultiTalkModelPatch(
audio_window=5, context_tokens=32, vae_scale=4,
in_dim=sd["blocks.0.audio_cross_attn.proj.weight"].shape[0],
intermediate_dim=sd["audio_proj.proj1.weight"].shape[0],
out_dim=sd["audio_proj.norm.weight"].shape[0],
device=comfy.model_management.unet_offload_device(),
operations=comfy.ops.manual_cast)
model.load_state_dict(sd)
model = comfy.model_patcher.ModelPatcher(model, load_device=comfy.model_management.get_torch_device(), offload_device=comfy.model_management.unet_offload_device())
@@ -524,6 +533,38 @@ class USOStyleReference:
return (model_patched,)
class MultiTalkModelPatch(torch.nn.Module):
def __init__(
self,
audio_window: int = 5,
intermediate_dim: int = 512,
in_dim: int = 5120,
out_dim: int = 768,
context_tokens: int = 32,
vae_scale: int = 4,
num_layers: int = 40,
device=None, dtype=None, operations=None
):
super().__init__()
self.audio_proj = MultiTalkAudioProjModel(
seq_len=audio_window,
seq_len_vf=audio_window+vae_scale-1,
intermediate_dim=intermediate_dim,
out_dim=out_dim,
context_tokens=context_tokens,
device=device,
dtype=dtype,
operations=operations
)
self.blocks = torch.nn.ModuleList(
[
WanMultiTalkAttentionBlock(in_dim, out_dim, device=device, dtype=dtype, operations=operations)
for _ in range(num_layers)
]
)
NODE_CLASS_MAPPINGS = {
"ModelPatchLoader": ModelPatchLoader,
"QwenImageDiffsynthControlnet": QwenImageDiffsynthControlnet,