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Add support for Chroma Radiance (#9682)

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* Initial Chroma Radiance support

* Minor Chroma Radiance cleanups

* Update Radiance nodes to ensure latents/images are on the intermediate device

* Fix Chroma Radiance memory estimation.

* Increase Chroma Radiance memory usage factor

* Increase Chroma Radiance memory usage factor once again

* Ensure images are multiples of 16 for Chroma Radiance
Add batch dimension and fix channels when necessary in ChromaRadianceImageToLatent node

* Tile Chroma Radiance NeRF to reduce memory consumption, update memory usage factor

* Update Radiance to support conv nerf final head type.

* Allow setting NeRF embedder dtype for Radiance
Bump Radiance nerf tile size to 32
Support EasyCache/LazyCache on Radiance (maybe)

* Add ChromaRadianceStubVAE node

* Crop Radiance image inputs to multiples of 16 instead of erroring to be in line with existing VAE behavior

* Convert Chroma Radiance nodes to V3 schema.

* Add ChromaRadianceOptions node and backend support.
Cleanups/refactoring to reduce code duplication with Chroma.

* Fix overriding the NeRF embedder dtype for Chroma Radiance

* Minor Chroma Radiance cleanups

* Move Chroma Radiance to its own directory in ldm
Minor code cleanups and tooltip improvements

* Fix Chroma Radiance embedder dtype overriding

* Remove Radiance dynamic nerf_embedder dtype override feature

* Unbork Radiance NeRF embedder init

* Remove Chroma Radiance image conversion and stub VAE nodes
Add a chroma_radiance option to the VAELoader builtin node which uses comfy.sd.PixelspaceConversionVAE
Add a PixelspaceConversionVAE to comfy.sd for converting BHWC 0..1 <-> BCHW -1..1
This commit is contained in:
blepping
2025-09-13 15:58:43 -06:00
committed by GitHub
parent e5e70636e7
commit c1297f4eb3
10 changed files with 770 additions and 9 deletions
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9
comfy/model_base.py
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@@ -42,6 +42,7 @@ import comfy.ldm.wan.model
import comfy.ldm.hunyuan3d.model
import comfy.ldm.hidream.model
import comfy.ldm.chroma.model
import comfy.ldm.chroma_radiance.model
import comfy.ldm.ace.model
import comfy.ldm.omnigen.omnigen2
import comfy.ldm.qwen_image.model
@@ -1320,8 +1321,8 @@ class HiDream(BaseModel):
return out
class Chroma(Flux):
def __init__(self, model_config, model_type=ModelType.FLUX, device=None):
super().__init__(model_config, model_type, device=device, unet_model=comfy.ldm.chroma.model.Chroma)
def __init__(self, model_config, model_type=ModelType.FLUX, device=None, unet_model=comfy.ldm.chroma.model.Chroma):
super().__init__(model_config, model_type, device=device, unet_model=unet_model)
def extra_conds(self, **kwargs):
out = super().extra_conds(**kwargs)
@@ -1331,6 +1332,10 @@ class Chroma(Flux):
out['guidance'] = comfy.conds.CONDRegular(torch.FloatTensor([guidance]))
return out
class ChromaRadiance(Chroma):
def __init__(self, model_config, model_type=ModelType.FLUX, device=None):
super().__init__(model_config, model_type, device=device, unet_model=comfy.ldm.chroma_radiance.model.ChromaRadiance)
class ACEStep(BaseModel):
def __init__(self, model_config, model_type=ModelType.FLOW, device=None):
super().__init__(model_config, model_type, device=device, unet_model=comfy.ldm.ace.model.ACEStepTransformer2DModel)