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Merge branch 'master' into toolkit/wire-essentials-categorization
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guill 2026-03-15 16:08:47 -07:00 committed by GitHub
commit 7de1a7dbe4
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4 changed files with 17 additions and 10 deletions
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2
comfy/model_management.py
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@ -400,7 +400,7 @@ try:
if args.use_split_cross_attention == False and args.use_quad_cross_attention == False:
if aotriton_supported(arch): # AMD efficient attention implementation depends on aotriton.
if torch_version_numeric >= (2, 7): # works on 2.6 but doesn't actually seem to improve much
if any((a in arch) for a in ["gfx90a", "gfx942", "gfx950", "gfx1100", "gfx1101", "gfx1151"]): # TODO: more arches, TODO: gfx950
if any((a in arch) for a in ["gfx90a", "gfx942", "gfx950", "gfx1100", "gfx1101", "gfx1150", "gfx1151"]): # TODO: more arches, TODO: gfx950
ENABLE_PYTORCH_ATTENTION = True
if rocm_version >= (7, 0):
if any((a in arch) for a in ["gfx1200", "gfx1201"]):

18
comfy/ops.py
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@ -336,7 +336,10 @@ class disable_weight_init:
class Linear(torch.nn.Linear, CastWeightBiasOp):
def __init__(self, in_features, out_features, bias=True, device=None, dtype=None):
if not comfy.model_management.WINDOWS or not comfy.memory_management.aimdo_enabled:
# don't trust subclasses that BYO state dict loader to call us.
if (not comfy.model_management.WINDOWS
or not comfy.memory_management.aimdo_enabled
or type(self)._load_from_state_dict is not disable_weight_init.Linear._load_from_state_dict):
super().__init__(in_features, out_features, bias, device, dtype)
return
@ -357,7 +360,9 @@ class disable_weight_init:
def _load_from_state_dict(self, state_dict, prefix, local_metadata,
strict, missing_keys, unexpected_keys, error_msgs):
if not comfy.model_management.WINDOWS or not comfy.memory_management.aimdo_enabled:
if (not comfy.model_management.WINDOWS
or not comfy.memory_management.aimdo_enabled
or type(self)._load_from_state_dict is not disable_weight_init.Linear._load_from_state_dict):
return super()._load_from_state_dict(state_dict, prefix, local_metadata, strict,
missing_keys, unexpected_keys, error_msgs)
disable_weight_init._lazy_load_from_state_dict(
@ -564,7 +569,10 @@ class disable_weight_init:
def __init__(self, num_embeddings, embedding_dim, padding_idx=None, max_norm=None,
norm_type=2.0, scale_grad_by_freq=False, sparse=False, _weight=None,
_freeze=False, device=None, dtype=None):
if not comfy.model_management.WINDOWS or not comfy.memory_management.aimdo_enabled:
# don't trust subclasses that BYO state dict loader to call us.
if (not comfy.model_management.WINDOWS
or not comfy.memory_management.aimdo_enabled
or type(self)._load_from_state_dict is not disable_weight_init.Embedding._load_from_state_dict):
super().__init__(num_embeddings, embedding_dim, padding_idx, max_norm,
norm_type, scale_grad_by_freq, sparse, _weight,
_freeze, device, dtype)
@ -590,7 +598,9 @@ class disable_weight_init:
def _load_from_state_dict(self, state_dict, prefix, local_metadata,
strict, missing_keys, unexpected_keys, error_msgs):
if not comfy.model_management.WINDOWS or not comfy.memory_management.aimdo_enabled:
if (not comfy.model_management.WINDOWS
or not comfy.memory_management.aimdo_enabled
or type(self)._load_from_state_dict is not disable_weight_init.Embedding._load_from_state_dict):
return super()._load_from_state_dict(state_dict, prefix, local_metadata, strict,
missing_keys, unexpected_keys, error_msgs)
disable_weight_init._lazy_load_from_state_dict(

2
manager_requirements.txt
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@ -1 +1 @@
comfyui_manager==4.1b4
comfyui_manager==4.1b5

5
nodes.py
View File

@ -1212,9 +1212,6 @@ class GLIGENTextBoxApply:
return (c, )
class EmptyLatentImage:
def __init__(self):
self.device = comfy.model_management.intermediate_device()
@classmethod
def INPUT_TYPES(s):
return {
@ -1233,7 +1230,7 @@ class EmptyLatentImage:
SEARCH_ALIASES = ["empty", "empty latent", "new latent", "create latent", "blank latent", "blank"]
def generate(self, width, height, batch_size=1):
latent = torch.zeros([batch_size, 4, height // 8, width // 8], device=self.device)
latent = torch.zeros([batch_size, 4, height // 8, width // 8], device=comfy.model_management.intermediate_device(), dtype=comfy.model_management.intermediate_dtype())
return ({"samples": latent, "downscale_ratio_spacial": 8}, )