From 8bfc199d1fdad7fa252296141b6b39b305da5554 Mon Sep 17 00:00:00 2001
From: kijai <40791699+kijai@users.noreply.github.com>
Date: Sun, 25 Aug 2024 15:24:15 +0300
Subject: [PATCH] Remove backwards compatibility attempt on patching

possible causing issues, expect ComfyUI to be on latest version now
---
 nodes.py         | 18 ++++-----------
 pyproject.toml   |  2 +-
 utils/patches.py | 60 +-----------------------------------------------
 3 files changed, 7 insertions(+), 73 deletions(-)

diff --git a/nodes.py b/nodes.py
index 751b8e2..ffdf814 100644
--- a/nodes.py
+++ b/nodes.py
@@ -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):
diff --git a/pyproject.toml b/pyproject.toml
index 519f5f8..a48776f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -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"]
 
diff --git a/utils/patches.py b/utils/patches.py
index 9be8a62..0c6dd97 100644
--- a/utils/patches.py
+++ b/utils/patches.py
@@ -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)