nodes/kijai-ComfyUI-IC-Light
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Remove backwards compatibility attempt on patching

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possible causing issues, expect ComfyUI to be on latest version now
This commit is contained in:
kijai
2024-08-25 15:24:15 +03:00
parent 419b7e004f
commit 8bfc199d1f
3 changed files with 7 additions and 73 deletions
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nodes.py
+5 -13
View File
@@ -7,7 +7,7 @@ import numpy as np
import torch.nn.functional as F
from comfy.utils import load_torch_file
from .utils.convert_unet import convert_iclight_unet
from .utils.patches import calculate_weight_adjust_channel_old, calculate_weight_adjust_channel_new
from .utils.patches import calculate_weight_adjust_channel
from .utils.image import generate_gradient_image, LightPosition
from nodes import MAX_RESOLUTION
from comfy.model_patcher import ModelPatcher
@@ -69,18 +69,10 @@ Used with ICLightConditioning -node
print("LoadAndApplyICLightUnet: Added LoadICLightUnet patches")
#Patch ComfyUI's LoRA weight application to accept multi-channel inputs. Thanks @huchenlei
if hasattr(ModelPatcher, 'calculate_weight'):
try:
ModelPatcher.calculate_weight = calculate_weight_adjust_channel_old(ModelPatcher.calculate_weight)
except:
raise Exception("IC-Light: Could not patch calculate_weight")
# the function was moved to lora module in commit https://github.com/comfyanonymous/ComfyUI/commit/c26ca272076262c8b21a8f2e094cf538d88b9e46
else:
try:
lora.calculate_weight = calculate_weight_adjust_channel_new(lora.calculate_weight)
except:
raise Exception("IC-Light: Could not patch calculate_weight")
try:
lora.calculate_weight = calculate_weight_adjust_channel(lora.calculate_weight)
except:
raise Exception("IC-Light: Could not patch calculate_weight")
# Mimic the existing IP2P class to enable extra_conds
def bound_extra_conds(self, **kwargs):
pyproject.toml
+1 -1
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@@ -1,7 +1,7 @@
[project]
name = "comfyui-ic-light"
description = "ComfyUI native nodes for IC-Light"
version = "1.0.0"
version = "1.0.1"
license = { text = "Apache License 2.0" }
dependencies = ["opencv-python"]
utils/patches.py
+1 -59
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@@ -7,65 +7,7 @@ import functools
from comfy.model_patcher import ModelPatcher
import comfy.model_management
def calculate_weight_adjust_channel_old(func):
"""Patches ComfyUI's LoRA weight application to accept multi-channel inputs."""
@functools.wraps(func)
def calculate_weight(
self: ModelPatcher, patches, weight: torch.Tensor, key: str
) -> torch.Tensor:
weight = func(self, patches, weight, key)
for p in patches:
alpha = p[0]
v = p[1]
# The recursion call should be handled in the main func call.
if isinstance(v, list):
continue
if len(v) == 1:
patch_type = "diff"
elif len(v) == 2:
patch_type = v[0]
v = v[1]
if patch_type == "diff":
w1 = v[0]
if all(
(
alpha != 0.0,
w1.shape != weight.shape,
w1.ndim == weight.ndim == 4,
)
):
new_shape = [max(n, m) for n, m in zip(weight.shape, w1.shape)]
print(
f"IC-Light: Merged with {key} channel changed from {weight.shape} to {new_shape}"
)
new_diff = alpha * comfy.model_management.cast_to_device(
w1, weight.device, weight.dtype
)
new_weight = torch.zeros(size=new_shape).to(weight)
new_weight[
: weight.shape[0],
: weight.shape[1],
: weight.shape[2],
: weight.shape[3],
] = weight
new_weight[
: new_diff.shape[0],
: new_diff.shape[1],
: new_diff.shape[2],
: new_diff.shape[3],
] += new_diff
new_weight = new_weight.contiguous().clone()
weight = new_weight
return weight
return calculate_weight
def calculate_weight_adjust_channel_new(func):
def calculate_weight_adjust_channel(func):
"""Patches ComfyUI's LoRA weight application to accept multi-channel inputs."""
@functools.wraps(func)