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Code Issues Actions 14 Packages Projects Releases Wiki Activity

Merge upstream/master, keep local README.md

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GitHub Actions 2025-12-12 00:37:21 +00:00
commit 63aef61d6d
6 changed files with 33 additions and 14 deletions
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10
.ci/update_windows/update.py
View File

@ -53,6 +53,16 @@ try:
repo.stash(ident)
except KeyError:
print("nothing to stash") # noqa: T201
except:
print("Could not stash, cleaning index and trying again.") # noqa: T201
repo.state_cleanup()
repo.index.read_tree(repo.head.peel().tree)
repo.index.write()
try:
repo.stash(ident)
except KeyError:
print("nothing to stash.") # noqa: T201
backup_branch_name = 'backup_branch_{}'.format(datetime.today().strftime('%Y-%m-%d_%H_%M_%S'))
print("creating backup branch: {}".format(backup_branch_name)) # noqa: T201
try:

7
api_server/routes/internal/internal_routes.py
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@ -58,8 +58,13 @@ class InternalRoutes:
return web.json_response({"error": "Invalid directory type"}, status=400)
directory = get_directory_by_type(directory_type)
def is_visible_file(entry: os.DirEntry) -> bool:
"""Filter out hidden files (e.g., .DS_Store on macOS)."""
return entry.is_file() and not entry.name.startswith('.')
sorted_files = sorted(
(entry for entry in os.scandir(directory) if entry.is_file()),
(entry for entry in os.scandir(directory) if is_visible_file(entry)),
key=lambda entry: -entry.stat().st_mtime
)
return web.json_response([entry.name for entry in sorted_files], status=200)

6
comfy/model_detection.py
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@ -259,8 +259,10 @@ def detect_unet_config(state_dict, key_prefix, metadata=None):
dit_config["nerf_tile_size"] = 512
dit_config["nerf_final_head_type"] = "conv" if f"{key_prefix}nerf_final_layer_conv.norm.scale" in state_dict_keys else "linear"
dit_config["nerf_embedder_dtype"] = torch.float32
if "__x0__" in state_dict_keys: # x0 pred
dit_config["use_x0"] = True
if "__x0__" in state_dict_keys: # x0 pred
dit_config["use_x0"] = True
else:
dit_config["use_x0"] = False
else:
dit_config["guidance_embed"] = "{}guidance_in.in_layer.weight".format(key_prefix) in state_dict_keys
dit_config["yak_mlp"] = '{}double_blocks.0.img_mlp.gate_proj.weight'.format(key_prefix) in state_dict_keys

6
comfy/sd.py
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@ -549,8 +549,10 @@ class VAE:
ddconfig = {"dim": dim, "z_dim": self.latent_channels, "dim_mult": [1, 2, 4, 4], "num_res_blocks": 2, "attn_scales": [], "temperal_downsample": [False, True, True], "dropout": 0.0}
self.first_stage_model = comfy.ldm.wan.vae.WanVAE(**ddconfig)
self.working_dtypes = [torch.bfloat16, torch.float16, torch.float32]
self.memory_used_encode = lambda shape, dtype: 6000 * shape[3] * shape[4] * model_management.dtype_size(dtype)
self.memory_used_decode = lambda shape, dtype: 7000 * shape[3] * shape[4] * (8 * 8) * model_management.dtype_size(dtype)
self.memory_used_encode = lambda shape, dtype: (1500 if shape[2]<=4 else 6000) * shape[3] * shape[4] * model_management.dtype_size(dtype)
self.memory_used_decode = lambda shape, dtype: (2200 if shape[2]<=4 else 7000) * shape[3] * shape[4] * (8*8) * model_management.dtype_size(dtype)
# Hunyuan 3d v2 2.0 & 2.1
elif "geo_decoder.cross_attn_decoder.ln_1.bias" in sd:

16
comfy/supported_models.py
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@ -541,7 +541,7 @@ class SD3(supported_models_base.BASE):
unet_extra_config = {}
latent_format = latent_formats.SD3
memory_usage_factor = 1.2
memory_usage_factor = 1.6
text_encoder_key_prefix = ["text_encoders."]
@ -965,7 +965,7 @@ class CosmosT2IPredict2(supported_models_base.BASE):
def __init__(self, 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):
out = model_base.CosmosPredict2(self, device=device)
@ -1026,7 +1026,7 @@ class ZImage(Lumina2):
"shift": 3.0,
}
memory_usage_factor = 1.7
memory_usage_factor = 2.0
supported_inference_dtypes = [torch.bfloat16, torch.float16, torch.float32]
@ -1289,7 +1289,7 @@ class ChromaRadiance(Chroma):
latent_format = comfy.latent_formats.ChromaRadiance
# 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):
return model_base.ChromaRadiance(self, device=device)
@ -1332,7 +1332,7 @@ class Omnigen2(supported_models_base.BASE):
"shift": 2.6,
}
memory_usage_factor = 1.65 #TODO
memory_usage_factor = 1.95 #TODO
unet_extra_config = {}
latent_format = latent_formats.Flux
@ -1397,7 +1397,7 @@ class HunyuanImage21(HunyuanVideo):
latent_format = latent_formats.HunyuanImage21
memory_usage_factor = 7.7
memory_usage_factor = 8.7
supported_inference_dtypes = [torch.bfloat16, torch.float32]
@ -1488,7 +1488,7 @@ class Kandinsky5(supported_models_base.BASE):
unet_extra_config = {}
latent_format = latent_formats.HunyuanVideo
memory_usage_factor = 1.1 #TODO
memory_usage_factor = 1.25 #TODO
supported_inference_dtypes = [torch.bfloat16, torch.float32]
@ -1517,7 +1517,7 @@ class Kandinsky5Image(Kandinsky5):
}
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):
out = model_base.Kandinsky5Image(self, device=device)

2
comfy_api_nodes/nodes_kling.py
View File

@ -2056,7 +2056,7 @@ class KlingExtension(ComfyExtension):
OmniProImageToVideoNode,
OmniProVideoToVideoNode,
OmniProEditVideoNode,
# OmniProImageNode, # need support from backend
OmniProImageNode,
]