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convert nodes_freelunch.py to the V3 schema (#10904)

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Alexander Piskun 2025-12-06 06:22:02 +02:00 committed by GitHub
parent ae676ed105
commit 117bf3f2bd
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2 changed files with 57 additions and 37 deletions
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89
comfy_extras/nodes_freelunch.py
View File

@ -2,6 +2,8 @@
import torch
import logging
from typing_extensions import override
from comfy_api.latest import ComfyExtension, IO
def Fourier_filter(x, threshold, scale):
# FFT
@ -22,21 +24,26 @@ def Fourier_filter(x, threshold, scale):
return x_filtered.to(x.dtype)
class FreeU:
class FreeU(IO.ComfyNode):
@classmethod
def INPUT_TYPES(s):
return {"required": { "model": ("MODEL",),
"b1": ("FLOAT", {"default": 1.1, "min": 0.0, "max": 10.0, "step": 0.01}),
"b2": ("FLOAT", {"default": 1.2, "min": 0.0, "max": 10.0, "step": 0.01}),
"s1": ("FLOAT", {"default": 0.9, "min": 0.0, "max": 10.0, "step": 0.01}),
"s2": ("FLOAT", {"default": 0.2, "min": 0.0, "max": 10.0, "step": 0.01}),
}}
RETURN_TYPES = ("MODEL",)
FUNCTION = "patch"
def define_schema(cls):
return IO.Schema(
node_id="FreeU",
category="model_patches/unet",
inputs=[
IO.Model.Input("model"),
IO.Float.Input("b1", default=1.1, min=0.0, max=10.0, step=0.01),
IO.Float.Input("b2", default=1.2, min=0.0, max=10.0, step=0.01),
IO.Float.Input("s1", default=0.9, min=0.0, max=10.0, step=0.01),
IO.Float.Input("s2", default=0.2, min=0.0, max=10.0, step=0.01),
],
outputs=[
IO.Model.Output(),
],
)
CATEGORY = "model_patches/unet"
def patch(self, model, b1, b2, s1, s2):
@classmethod
def execute(cls, model, b1, b2, s1, s2) -> IO.NodeOutput:
model_channels = model.model.model_config.unet_config["model_channels"]
scale_dict = {model_channels * 4: (b1, s1), model_channels * 2: (b2, s2)}
on_cpu_devices = {}
@ -59,23 +66,31 @@ class FreeU:
m = model.clone()
m.set_model_output_block_patch(output_block_patch)
return (m, )
return IO.NodeOutput(m)
class FreeU_V2:
patch = execute # TODO: remove
class FreeU_V2(IO.ComfyNode):
@classmethod
def INPUT_TYPES(s):
return {"required": { "model": ("MODEL",),
"b1": ("FLOAT", {"default": 1.3, "min": 0.0, "max": 10.0, "step": 0.01}),
"b2": ("FLOAT", {"default": 1.4, "min": 0.0, "max": 10.0, "step": 0.01}),
"s1": ("FLOAT", {"default": 0.9, "min": 0.0, "max": 10.0, "step": 0.01}),
"s2": ("FLOAT", {"default": 0.2, "min": 0.0, "max": 10.0, "step": 0.01}),
}}
RETURN_TYPES = ("MODEL",)
FUNCTION = "patch"
def define_schema(cls):
return IO.Schema(
node_id="FreeU_V2",
category="model_patches/unet",
inputs=[
IO.Model.Input("model"),
IO.Float.Input("b1", default=1.3, min=0.0, max=10.0, step=0.01),
IO.Float.Input("b2", default=1.4, min=0.0, max=10.0, step=0.01),
IO.Float.Input("s1", default=0.9, min=0.0, max=10.0, step=0.01),
IO.Float.Input("s2", default=0.2, min=0.0, max=10.0, step=0.01),
],
outputs=[
IO.Model.Output(),
],
)
CATEGORY = "model_patches/unet"
def patch(self, model, b1, b2, s1, s2):
@classmethod
def execute(cls, model, b1, b2, s1, s2) -> IO.NodeOutput:
model_channels = model.model.model_config.unet_config["model_channels"]
scale_dict = {model_channels * 4: (b1, s1), model_channels * 2: (b2, s2)}
on_cpu_devices = {}
@ -105,9 +120,19 @@ class FreeU_V2:
m = model.clone()
m.set_model_output_block_patch(output_block_patch)
return (m, )
return IO.NodeOutput(m)
NODE_CLASS_MAPPINGS = {
"FreeU": FreeU,
"FreeU_V2": FreeU_V2,
}
patch = execute # TODO: remove
class FreelunchExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
return [
FreeU,
FreeU_V2,
]
async def comfy_entrypoint() -> FreelunchExtension:
return FreelunchExtension()

5
comfy_extras/nodes_model_downscale.py
View File

@ -53,11 +53,6 @@ class PatchModelAddDownscale(io.ComfyNode):
return io.NodeOutput(m)
NODE_DISPLAY_NAME_MAPPINGS = {
# Sampling
"PatchModelAddDownscale": "",
}
class ModelDownscaleExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[io.ComfyNode]]: