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Bump version from 0.2.6 to 0.2.7

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silveroxides
2026-01-23 19:21:02 +01:00
parent 4097326a82
commit 6a119e63f5
3 changed files with 33 additions and 21 deletions
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nodes/merger.py
+20 -20
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@@ -249,7 +249,7 @@ class CheckpointTwoMerger(io.ComfyNode):
@classmethod
def execute(cls, execution_mode: str, model_a: str, model_b: str,
calc_mode: str, mismatch_mode: str, alpha: float, beta: float,
calc_mode: str, mismatch_mode: str, alignment_mode: str, alpha: float, beta: float,
gamma: float, delta: float, seed: int, output_filename: str, save_dtype: str,
process_device: str, exclude_patterns: str, discard_patterns: str) -> io.NodeOutput:
doc = load_documentation_from_file('merger_2_model_modes.md')
@@ -258,7 +258,7 @@ class CheckpointTwoMerger(io.ComfyNode):
recipe_params = {
"model_a": model_a, "model_b": model_b, "calc_mode": calc_mode,
"mismatch_mode": mismatch_mode, "alignment_mode": recipe_params.get('alignment_mode', 'pad/crop'),
"mismatch_mode": mismatch_mode, "alignment_mode": alignment_mode,
"alpha": alpha, "beta": beta, "gamma": gamma, "delta": delta, "seed": seed,
"output_filename": output_filename, "save_dtype": save_dtype,
"device": process_device, "dtype": torch.float32,
@@ -304,7 +304,7 @@ class ModelTwoMerger(io.ComfyNode):
@classmethod
def execute(cls, execution_mode: str, model_a: str, model_b: str,
calc_mode: str, mismatch_mode: str, alpha: float, beta: float,
calc_mode: str, mismatch_mode: str, alignment_mode: str, alpha: float, beta: float,
gamma: float, delta: float, seed: int, output_filename: str, save_dtype: str,
process_device: str, exclude_patterns: str, discard_patterns: str) -> io.NodeOutput:
doc = load_documentation_from_file('merger_2_model_modes.md')
@@ -313,7 +313,7 @@ class ModelTwoMerger(io.ComfyNode):
recipe_params = {
"model_a": model_a, "model_b": model_b, "calc_mode": calc_mode,
"mismatch_mode": mismatch_mode, "alignment_mode": recipe_params.get('alignment_mode', 'pad/crop'),
"mismatch_mode": mismatch_mode, "alignment_mode": alignment_mode,
"alpha": alpha, "beta": beta, "gamma": gamma, "delta": delta, "seed": seed,
"output_filename": output_filename, "save_dtype": save_dtype,
"device": process_device, "dtype": torch.float32,
@@ -359,7 +359,7 @@ class TextEncoderTwoMerger(io.ComfyNode):
@classmethod
def execute(cls, execution_mode: str, model_a: str, model_b: str,
calc_mode: str, mismatch_mode: str, alpha: float, beta: float,
calc_mode: str, mismatch_mode: str, alignment_mode: str, alpha: float, beta: float,
gamma: float, delta: float, seed: int, output_filename: str, save_dtype: str,
process_device: str, exclude_patterns: str, discard_patterns: str) -> io.NodeOutput:
doc = load_documentation_from_file('merger_2_model_modes.md')
@@ -368,7 +368,7 @@ class TextEncoderTwoMerger(io.ComfyNode):
recipe_params = {
"model_a": model_a, "model_b": model_b, "calc_mode": calc_mode,
"mismatch_mode": mismatch_mode, "alignment_mode": recipe_params.get('alignment_mode', 'pad/crop'),
"mismatch_mode": mismatch_mode, "alignment_mode": alignment_mode,
"alpha": alpha, "beta": beta, "gamma": gamma, "delta": delta, "seed": seed,
"output_filename": output_filename, "save_dtype": save_dtype,
"device": process_device, "dtype": torch.float32,
@@ -414,7 +414,7 @@ class LoRATwoMerger(io.ComfyNode):
@classmethod
def execute(cls, execution_mode: str, model_a: str, model_b: str,
calc_mode: str, mismatch_mode: str, alpha: float, beta: float,
calc_mode: str, mismatch_mode: str, alignment_mode: str, alpha: float, beta: float,
gamma: float, delta: float, seed: int, output_filename: str, save_dtype: str,
process_device: str, exclude_patterns: str, discard_patterns: str) -> io.NodeOutput:
doc = load_documentation_from_file('merger_2_model_modes.md')
@@ -423,7 +423,7 @@ class LoRATwoMerger(io.ComfyNode):
recipe_params = {
"model_a": model_a, "model_b": model_b, "calc_mode": calc_mode,
"mismatch_mode": mismatch_mode, "alignment_mode": recipe_params.get('alignment_mode', 'pad/crop'),
"mismatch_mode": mismatch_mode, "alignment_mode": alignment_mode,
"alpha": alpha, "beta": beta, "gamma": gamma, "delta": delta, "seed": seed,
"output_filename": output_filename, "save_dtype": save_dtype,
"device": process_device, "dtype": torch.float32,
@@ -469,7 +469,7 @@ class EmbeddingTwoMerger(io.ComfyNode):
@classmethod
def execute(cls, execution_mode: str, model_a: str, model_b: str,
calc_mode: str, mismatch_mode: str, alpha: float, beta: float,
calc_mode: str, mismatch_mode: str, alignment_mode: str, alpha: float, beta: float,
gamma: float, delta: float, seed: int, output_filename: str, save_dtype: str,
process_device: str, exclude_patterns: str, discard_patterns: str) -> io.NodeOutput:
doc = load_documentation_from_file('merger_2_model_modes.md')
@@ -478,7 +478,7 @@ class EmbeddingTwoMerger(io.ComfyNode):
recipe_params = {
"model_a": model_a, "model_b": model_b, "calc_mode": calc_mode,
"mismatch_mode": mismatch_mode, "alignment_mode": recipe_params.get('alignment_mode', 'pad/crop'),
"mismatch_mode": mismatch_mode, "alignment_mode": alignment_mode,
"alpha": alpha, "beta": beta, "gamma": gamma, "delta": delta, "seed": seed,
"output_filename": output_filename, "save_dtype": save_dtype,
"device": process_device, "dtype": torch.float32,
@@ -527,7 +527,7 @@ class CheckpointThreeMerger(io.ComfyNode):
@classmethod
def execute(cls, execution_mode: str, model_a: str, model_b: str, model_c: str,
calc_mode: str, mismatch_mode: str, alpha: float, beta: float,
calc_mode: str, mismatch_mode: str, alignment_mode: str, alpha: float, beta: float,
gamma: float, delta: float, seed: int, output_filename: str, save_dtype: str,
process_device: str, exclude_patterns: str, discard_patterns: str) -> io.NodeOutput:
doc = load_documentation_from_file('merger_3_model_modes.md')
@@ -536,7 +536,7 @@ class CheckpointThreeMerger(io.ComfyNode):
recipe_params = {
"model_a": model_a, "model_b": model_b, "model_c": model_c, "calc_mode": calc_mode,
"mismatch_mode": mismatch_mode, "alignment_mode": recipe_params.get('alignment_mode', 'pad/crop'),
"mismatch_mode": mismatch_mode, "alignment_mode": alignment_mode,
"alpha": alpha, "beta": beta, "gamma": gamma, "delta": delta, "seed": seed,
"output_filename": output_filename, "save_dtype": save_dtype,
"device": process_device, "dtype": torch.float32,
@@ -583,7 +583,7 @@ class ModelThreeMerger(io.ComfyNode):
@classmethod
def execute(cls, execution_mode: str, model_a: str, model_b: str, model_c: str,
calc_mode: str, mismatch_mode: str, alpha: float, beta: float,
calc_mode: str, mismatch_mode: str, alignment_mode: str, alpha: float, beta: float,
gamma: float, delta: float, seed: int, output_filename: str, save_dtype: str,
process_device: str, exclude_patterns: str, discard_patterns: str) -> io.NodeOutput:
doc = load_documentation_from_file('merger_3_model_modes.md')
@@ -592,7 +592,7 @@ class ModelThreeMerger(io.ComfyNode):
recipe_params = {
"model_a": model_a, "model_b": model_b, "model_c": model_c, "calc_mode": calc_mode,
"mismatch_mode": mismatch_mode, "alignment_mode": recipe_params.get('alignment_mode', 'pad/crop'),
"mismatch_mode": mismatch_mode, "alignment_mode": alignment_mode,
"alpha": alpha, "beta": beta, "gamma": gamma, "delta": delta, "seed": seed,
"output_filename": output_filename, "save_dtype": save_dtype,
"device": process_device, "dtype": torch.float32,
@@ -639,7 +639,7 @@ class TextEncoderThreeMerger(io.ComfyNode):
@classmethod
def execute(cls, execution_mode: str, model_a: str, model_b: str, model_c: str,
calc_mode: str, mismatch_mode: str, alpha: float, beta: float,
calc_mode: str, mismatch_mode: str, alignment_mode: str, alpha: float, beta: float,
gamma: float, delta: float, seed: int, output_filename: str, save_dtype: str,
process_device: str, exclude_patterns: str, discard_patterns: str) -> io.NodeOutput:
doc = load_documentation_from_file('merger_3_model_modes.md')
@@ -648,7 +648,7 @@ class TextEncoderThreeMerger(io.ComfyNode):
recipe_params = {
"model_a": model_a, "model_b": model_b, "model_c": model_c, "calc_mode": calc_mode,
"mismatch_mode": mismatch_mode, "alignment_mode": recipe_params.get('alignment_mode', 'pad/crop'),
"mismatch_mode": mismatch_mode, "alignment_mode": alignment_mode,
"alpha": alpha, "beta": beta, "gamma": gamma, "delta": delta, "seed": seed,
"output_filename": output_filename, "save_dtype": save_dtype,
"device": process_device, "dtype": torch.float32,
@@ -695,7 +695,7 @@ class LoRAThreeMerger(io.ComfyNode):
@classmethod
def execute(cls, execution_mode: str, model_a: str, model_b: str, model_c: str,
calc_mode: str, mismatch_mode: str, alpha: float, beta: float,
calc_mode: str, mismatch_mode: str, alignment_mode: str, alpha: float, beta: float,
gamma: float, delta: float, seed: int, output_filename: str, save_dtype: str,
process_device: str, exclude_patterns: str, discard_patterns: str) -> io.NodeOutput:
doc = load_documentation_from_file('merger_3_model_modes.md')
@@ -704,7 +704,7 @@ class LoRAThreeMerger(io.ComfyNode):
recipe_params = {
"model_a": model_a, "model_b": model_b, "model_c": model_c, "calc_mode": calc_mode,
"mismatch_mode": mismatch_mode, "alignment_mode": recipe_params.get('alignment_mode', 'pad/crop'),
"mismatch_mode": mismatch_mode, "alignment_mode": alignment_mode,
"alpha": alpha, "beta": beta, "gamma": gamma, "delta": delta, "seed": seed,
"output_filename": output_filename, "save_dtype": save_dtype,
"device": process_device, "dtype": torch.float32,
@@ -751,7 +751,7 @@ class EmbeddingThreeMerger(io.ComfyNode):
@classmethod
def execute(cls, execution_mode: str, model_a: str, model_b: str, model_c: str,
calc_mode: str, mismatch_mode: str, alpha: float, beta: float,
calc_mode: str, mismatch_mode: str, alignment_mode: str, alpha: float, beta: float,
gamma: float, delta: float, seed: int, output_filename: str, save_dtype: str,
process_device: str, exclude_patterns: str, discard_patterns: str) -> io.NodeOutput:
doc = load_documentation_from_file('merger_3_model_modes.md')
@@ -760,7 +760,7 @@ class EmbeddingThreeMerger(io.ComfyNode):
recipe_params = {
"model_a": model_a, "model_b": model_b, "model_c": model_c, "calc_mode": calc_mode,
"mismatch_mode": mismatch_mode, "alignment_mode": recipe_params.get('alignment_mode', 'pad/crop'),
"mismatch_mode": mismatch_mode, "alignment_mode": alignment_mode,
"alpha": alpha, "beta": beta, "gamma": gamma, "delta": delta, "seed": seed,
"output_filename": output_filename, "save_dtype": save_dtype,
"device": process_device, "dtype": torch.float32,
nodes/merger_ops.py
+12
View File
@@ -40,6 +40,14 @@ def resize_by_interpolation(tensor1, tensor2):
t2_f = t2_f.view(view_shape)
# Select mode based on dimensions
if dims1 == 4:
# [Out, In, H, W] -> [1, 1, Out, In, H*W] (5D)
view_shape = [1, 1, tensor2.shape[0], tensor2.shape[1], tensor2.shape[2] * tensor2.shape[3]]
target_size = [tensor1.shape[0], tensor1.shape[1], tensor1.shape[2] * tensor1.shape[3]]
t2_f = t2_f.view(view_shape)
t2_res = F.interpolate(t2_f, size=target_size, mode='trilinear', align_corners=False)
return tensor1, t2_res.view(tensor1.shape).to(orig_dtype)
if dims1 == 1:
mode = 'linear'
elif dims1 == 2:
@@ -448,6 +456,7 @@ class AddDifference(CalcMode):
b = LoadTensor(key, kwargs['model_b'], **loader_args_bc)
c = LoadTensor(key, kwargs['model_c'], **loader_args_bc)
diff = Sub(key, b, c)
diff.alignment_mode = alignment_mode
if kwargs['beta'] == 1: diff = Smooth(key, diff)
diffm = Multiply(key, kwargs['alpha'], diff)
res = Add(key, a, diffm)
@@ -474,6 +483,7 @@ class TrainDifference(CalcMode):
b = LoadTensor(key, kwargs['model_b'], **loader_args_bc)
c = LoadTensor(key, kwargs['model_c'], **loader_args_bc)
diff = TrainDiff(key, a, b, c)
diff.alignment_mode = alignment_mode
diffm = Multiply(key, kwargs['alpha'], diff)
res = Add(key, a, diffm)
res.alignment_mode = alignment_mode
@@ -523,6 +533,7 @@ class Extract(CalcMode):
b = LoadTensor(key, kwargs['model_b'], **loader_args_bc)
c = LoadTensor(key, kwargs['model_c'], **loader_args_bc)
extracted = ExtractOp(key, kwargs['alpha'], kwargs['beta'], kwargs['gamma'] * 15, a, b, c)
extracted.alignment_mode = alignment_mode
multiplied = Multiply(key, kwargs['delta'], extracted)
res = Add(key, a, multiplied)
res.alignment_mode = alignment_mode
@@ -548,6 +559,7 @@ class AddDisimilarity(CalcMode):
b = LoadTensor(key, kwargs['model_b'], **loader_args_bc)
c = LoadTensor(key, kwargs['model_c'], **loader_args_bc)
extracted = Similarities(key, kwargs['alpha'], 1, kwargs['gamma'] * 15, b, c)
extracted.alignment_mode = alignment_mode
multiplied = Multiply(key, kwargs['beta'], extracted)
res = Add(key, a, multiplied)
res.alignment_mode = alignment_mode
pyproject.toml
+1 -1
View File
@@ -1,7 +1,7 @@
[project]
name = "ComfyUI-ModelUtils"
description = "[WIP]Custom nodes for handling, inspecting, modifying and creating various model files."
version = "0.2.6"
version = "0.2.7"
license = { file = "LICENSE" }
[project.urls]