wangbo/ComfyUI
1
0
Fork 0
mirror of https://github.com/comfyanonymous/ComfyUI.git synced 2026-01-12 07:10:52 +08:00
Code Issues Actions 9 Packages Projects Releases Wiki Activity

Merge branch 'comfyanonymous:master' into master

Browse Source
This commit is contained in:
patientx 2025-05-02 23:58:33 +03:00 committed by GitHub
commit f98aad15d5
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
5 changed files with 73 additions and 27 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

34
comfy/weight_adapter/boft.py
View File

@ -24,7 +24,7 @@ class BOFTAdapter(WeightAdapterBase):
) -> Optional["BOFTAdapter"]:
if loaded_keys is None:
loaded_keys = set()
blocks_name = "{}.boft_blocks".format(x)
blocks_name = "{}.oft_blocks".format(x)
rescale_name = "{}.rescale".format(x)
blocks = None
@ -32,17 +32,18 @@ class BOFTAdapter(WeightAdapterBase):
blocks = lora[blocks_name]
if blocks.ndim == 4:
loaded_keys.add(blocks_name)
else:
blocks = None
if blocks is None:
return None
rescale = None
if rescale_name in lora.keys():
rescale = lora[rescale_name]
loaded_keys.add(rescale_name)
if blocks is not None:
weights = (blocks, rescale, alpha, dora_scale)
return cls(loaded_keys, weights)
else:
return None
weights = (blocks, rescale, alpha, dora_scale)
return cls(loaded_keys, weights)
def calculate_weight(
self,
@ -71,7 +72,7 @@ class BOFTAdapter(WeightAdapterBase):
# Get r
I = torch.eye(boft_b, device=blocks.device, dtype=blocks.dtype)
# for Q = -Q^T
q = blocks - blocks.transpose(1, 2)
q = blocks - blocks.transpose(-1, -2)
normed_q = q
if alpha > 0: # alpha in boft/bboft is for constraint
q_norm = torch.norm(q) + 1e-8
@ -79,9 +80,8 @@ class BOFTAdapter(WeightAdapterBase):
normed_q = q * alpha / q_norm
# use float() to prevent unsupported type in .inverse()
r = (I + normed_q) @ (I - normed_q).float().inverse()
r = r.to(original_weight)
inp = org = original_weight
r = r.to(weight)
inp = org = weight
r_b = boft_b//2
for i in range(boft_m):
@ -91,14 +91,14 @@ class BOFTAdapter(WeightAdapterBase):
if strength != 1:
bi = bi * strength + (1-strength) * I
inp = (
inp.unflatten(-1, (-1, g, k))
.transpose(-2, -1)
.flatten(-3)
.unflatten(-1, (-1, boft_b))
inp.unflatten(0, (-1, g, k))
.transpose(1, 2)
.flatten(0, 2)
.unflatten(0, (-1, boft_b))
)
inp = torch.einsum("b n m, b n ... -> b m ...", inp, bi)
inp = torch.einsum("b i j, b j ...-> b i ...", bi, inp)
inp = (
inp.flatten(-2).unflatten(-1, (-1, k, g)).transpose(-2, -1).flatten(-3)
inp.flatten(0, 1).unflatten(0, (-1, k, g)).transpose(1, 2).flatten(0, 2)
)
if rescale is not None:
@ -109,7 +109,7 @@ class BOFTAdapter(WeightAdapterBase):
if dora_scale is not None:
weight = weight_decompose(dora_scale, weight, lora_diff, alpha, strength, intermediate_dtype, function)
else:
weight += function(((strength * alpha) * lora_diff).type(weight.dtype))
weight += function((strength * lora_diff).type(weight.dtype))
except Exception as e:
logging.error("ERROR {} {} {}".format(self.name, key, e))
return weight

20
comfy/weight_adapter/oft.py
View File

@ -32,17 +32,18 @@ class OFTAdapter(WeightAdapterBase):
blocks = lora[blocks_name]
if blocks.ndim == 3:
loaded_keys.add(blocks_name)
else:
blocks = None
if blocks is None:
return None
rescale = None
if rescale_name in lora.keys():
rescale = lora[rescale_name]
loaded_keys.add(rescale_name)
if blocks is not None:
weights = (blocks, rescale, alpha, dora_scale)
return cls(loaded_keys, weights)
else:
return None
weights = (blocks, rescale, alpha, dora_scale)
return cls(loaded_keys, weights)
def calculate_weight(
self,
@ -79,16 +80,17 @@ class OFTAdapter(WeightAdapterBase):
normed_q = q * alpha / q_norm
# use float() to prevent unsupported type in .inverse()
r = (I + normed_q) @ (I - normed_q).float().inverse()
r = r.to(original_weight)
r = r.to(weight)
_, *shape = weight.shape
lora_diff = torch.einsum(
"k n m, k n ... -> k m ...",
(r * strength) - strength * I,
original_weight,
)
weight.view(block_num, block_size, *shape),
).view(-1, *shape)
if dora_scale is not None:
weight = weight_decompose(dora_scale, weight, lora_diff, alpha, strength, intermediate_dtype, function)
else:
weight += function(((strength * alpha) * lora_diff).type(weight.dtype))
weight += function((strength * lora_diff).type(weight.dtype))
except Exception as e:
logging.error("ERROR {} {} {}".format(self.name, key, e))
return weight

43
comfy_extras/nodes_preview_any.py Normal file
View File

@ -0,0 +1,43 @@
import json
from comfy.comfy_types.node_typing import IO
# Preview Any - original implement from
# https://github.com/rgthree/rgthree-comfy/blob/main/py/display_any.py
# upstream requested in https://github.com/Kosinkadink/rfcs/blob/main/rfcs/0000-corenodes.md#preview-nodes
class PreviewAny():
@classmethod
def INPUT_TYPES(cls):
return {
"required": {"source": (IO.ANY, {})},
}
RETURN_TYPES = ()
FUNCTION = "main"
OUTPUT_NODE = True
CATEGORY = "utils"
def main(self, source=None):
value = 'None'
if isinstance(source, str):
value = source
elif isinstance(source, (int, float, bool)):
value = str(source)
elif source is not None:
try:
value = json.dumps(source)
except Exception:
try:
value = str(source)
except Exception:
value = 'source exists, but could not be serialized.'
return {"ui": {"text": (value,)}}
NODE_CLASS_MAPPINGS = {
"PreviewAny": PreviewAny,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"PreviewAny": "Preview Any",
}

1
nodes.py
View File

@ -2258,6 +2258,7 @@ def init_builtin_extra_nodes():
"nodes_optimalsteps.py",
"nodes_hidream.py",
"nodes_fresca.py",
"nodes_preview_any.py",
]
api_nodes_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "comfy_api_nodes")

2
requirements.txt
View File

@ -1,4 +1,4 @@
comfyui-frontend-package==1.18.5
comfyui-frontend-package==1.18.6
comfyui-workflow-templates==0.1.3
torch
torchsde