wangbo/ComfyUI
1
0
Fork 0
mirror of https://github.com/comfyanonymous/ComfyUI.git synced 2025-12-16 01:37:04 +08:00
Code Issues Actions 8 Packages Projects Releases Wiki Activity

Better chroma radiance and other models vram estimation. (#11278)
Some checks are pending
Python Linting / Run Ruff (push) Waiting to run
Details
Python Linting / Run Pylint (push) Waiting to run
Details
Full Comfy CI Workflow Runs / test-stable (12.1, , linux, 3.10, [self-hosted Linux], stable) (push) Waiting to run
Details
Full Comfy CI Workflow Runs / test-stable (12.1, , linux, 3.11, [self-hosted Linux], stable) (push) Waiting to run
Details
Full Comfy CI Workflow Runs / test-stable (12.1, , linux, 3.12, [self-hosted Linux], stable) (push) Waiting to run
Details
Full Comfy CI Workflow Runs / test-unix-nightly (12.1, , linux, 3.11, [self-hosted Linux], nightly) (push) Waiting to run
Details
Execution Tests / test (macos-latest) (push) Waiting to run
Details
Execution Tests / test (ubuntu-latest) (push) Waiting to run
Details
Test server launches without errors / test (push) Waiting to run
Details
Unit Tests / test (macos-latest) (push) Waiting to run
Details
Unit Tests / test (ubuntu-latest) (push) Waiting to run
Details
Unit Tests / test (windows-2022) (push) Waiting to run
Details
Execution Tests / test (windows-latest) (push) Waiting to run
Details

Browse Source
This commit is contained in:
comfyanonymous 2025-12-11 14:33:09 -08:00 committed by GitHub
parent ae65433a60
commit eeb020b9b7
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 6 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
comfy/supported_models.py
View File

@ -965,7 +965,7 @@ class CosmosT2IPredict2(supported_models_base.BASE):
def __init__(self, unet_config): def __init__(self, unet_config):
super().__init__(unet_config) super().__init__(unet_config)
self.memory_usage_factor = (unet_config.get("model_channels", 2048) / 2048) * 0.9 self.memory_usage_factor = (unet_config.get("model_channels", 2048) / 2048) * 0.95
def get_model(self, state_dict, prefix="", device=None): def get_model(self, state_dict, prefix="", device=None):
out = model_base.CosmosPredict2(self, device=device) out = model_base.CosmosPredict2(self, device=device)
@ -1289,7 +1289,7 @@ class ChromaRadiance(Chroma):
latent_format = comfy.latent_formats.ChromaRadiance latent_format = comfy.latent_formats.ChromaRadiance
# Pixel-space model, no spatial compression for model input. # Pixel-space model, no spatial compression for model input.
memory_usage_factor = 0.038 memory_usage_factor = 0.044
def get_model(self, state_dict, prefix="", device=None): def get_model(self, state_dict, prefix="", device=None):
return model_base.ChromaRadiance(self, device=device) return model_base.ChromaRadiance(self, device=device)
@ -1332,7 +1332,7 @@ class Omnigen2(supported_models_base.BASE):
"shift": 2.6, "shift": 2.6,
} }
memory_usage_factor = 1.65 #TODO memory_usage_factor = 1.95 #TODO
unet_extra_config = {} unet_extra_config = {}
latent_format = latent_formats.Flux latent_format = latent_formats.Flux
@ -1397,7 +1397,7 @@ class HunyuanImage21(HunyuanVideo):
latent_format = latent_formats.HunyuanImage21 latent_format = latent_formats.HunyuanImage21
memory_usage_factor = 7.7 memory_usage_factor = 8.7
supported_inference_dtypes = [torch.bfloat16, torch.float32] supported_inference_dtypes = [torch.bfloat16, torch.float32]
@ -1488,7 +1488,7 @@ class Kandinsky5(supported_models_base.BASE):
unet_extra_config = {} unet_extra_config = {}
latent_format = latent_formats.HunyuanVideo latent_format = latent_formats.HunyuanVideo
memory_usage_factor = 1.1 #TODO memory_usage_factor = 1.25 #TODO
supported_inference_dtypes = [torch.bfloat16, torch.float32] supported_inference_dtypes = [torch.bfloat16, torch.float32]
@ -1517,7 +1517,7 @@ class Kandinsky5Image(Kandinsky5):
} }
latent_format = latent_formats.Flux latent_format = latent_formats.Flux
memory_usage_factor = 1.1 #TODO memory_usage_factor = 1.25 #TODO
def get_model(self, state_dict, prefix="", device=None): def get_model(self, state_dict, prefix="", device=None):
out = model_base.Kandinsky5Image(self, device=device) out = model_base.Kandinsky5Image(self, device=device)