comfyanonymous/ComfyUI
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Merge remote-tracking branch 'origin/master' into worksplit-multigpu

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This commit is contained in:
Jedrzej Kosinski
2025-08-29 23:36:19 -07:00
parent ac14ee68c0 885015eecf
commit 9e9c129cd0
64 changed files with 4422 additions and 1038 deletions
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17
comfy/controlnet.py
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@@ -37,6 +37,7 @@ import comfy.ldm.cascade.controlnet
import comfy.cldm.mmdit
import comfy.ldm.hydit.controlnet
import comfy.ldm.flux.controlnet
import comfy.ldm.qwen_image.controlnet
import comfy.cldm.dit_embedder
from typing import TYPE_CHECKING, Union
if TYPE_CHECKING:
@@ -271,11 +272,11 @@ class ControlNet(ControlBase):
self.cond_hint = None
compression_ratio = self.compression_ratio
if self.vae is not None:
compression_ratio *= self.vae.downscale_ratio
compression_ratio *= self.vae.spacial_compression_encode()
else:
if self.latent_format is not None:
raise ValueError("This Controlnet needs a VAE but none was provided, please use a ControlNetApply node with a VAE input and connect it.")
self.cond_hint = comfy.utils.common_upscale(self.cond_hint_original, x_noisy.shape[3] * compression_ratio, x_noisy.shape[2] * compression_ratio, self.upscale_algorithm, "center")
self.cond_hint = comfy.utils.common_upscale(self.cond_hint_original, x_noisy.shape[-1] * compression_ratio, x_noisy.shape[-2] * compression_ratio, self.upscale_algorithm, "center")
self.cond_hint = self.preprocess_image(self.cond_hint)
if self.vae is not None:
loaded_models = comfy.model_management.loaded_models(only_currently_used=True)
@@ -625,6 +626,15 @@ def load_controlnet_flux_instantx(sd, model_options={}):
control = ControlNet(control_model, compression_ratio=1, latent_format=latent_format, concat_mask=concat_mask, load_device=load_device, manual_cast_dtype=manual_cast_dtype, extra_conds=extra_conds)
return control
def load_controlnet_qwen_instantx(sd, model_options={}):
model_config, operations, load_device, unet_dtype, manual_cast_dtype, offload_device = controlnet_config(sd, model_options=model_options)
control_model = comfy.ldm.qwen_image.controlnet.QwenImageControlNetModel(operations=operations, device=offload_device, dtype=unet_dtype, **model_config.unet_config)
control_model = controlnet_load_state_dict(control_model, sd)
latent_format = comfy.latent_formats.Wan21()
extra_conds = []
control = ControlNet(control_model, compression_ratio=1, latent_format=latent_format, load_device=load_device, manual_cast_dtype=manual_cast_dtype, extra_conds=extra_conds)
return control
def convert_mistoline(sd):
return comfy.utils.state_dict_prefix_replace(sd, {"single_controlnet_blocks.": "controlnet_single_blocks."})
@@ -698,8 +708,11 @@ def load_controlnet_state_dict(state_dict, model=None, model_options={}):
return load_controlnet_sd35(controlnet_data, model_options=model_options) #Stability sd3.5 format
else:
return load_controlnet_mmdit(controlnet_data, model_options=model_options) #SD3 diffusers controlnet
elif "transformer_blocks.0.img_mlp.net.0.proj.weight" in controlnet_data:
return load_controlnet_qwen_instantx(controlnet_data, model_options=model_options)
elif "controlnet_x_embedder.weight" in controlnet_data:
return load_controlnet_flux_instantx(controlnet_data, model_options=model_options)
elif "controlnet_blocks.0.linear.weight" in controlnet_data: #mistoline flux
return load_controlnet_flux_xlabs_mistoline(convert_mistoline(controlnet_data), mistoline=True, model_options=model_options)