Merge branch 'comfyanonymous:master' into master

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patientx 2025-09-04 12:41:48 +03:00 committed by GitHub
commit d79e93a0a9
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5 changed files with 37 additions and 21 deletions

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@ -632,7 +632,7 @@ class ContinuousTransformer(nn.Module):
# Attention layers
if self.rotary_pos_emb is not None:
rotary_pos_emb = self.rotary_pos_emb.forward_from_seq_len(x.shape[1], dtype=x.dtype, device=x.device)
rotary_pos_emb = self.rotary_pos_emb.forward_from_seq_len(x.shape[1], dtype=torch.float, device=x.device)
else:
rotary_pos_emb = None

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@ -1,6 +1,10 @@
#from: https://research.nvidia.com/labs/toronto-ai/AlignYourSteps/howto.html
import numpy as np
import torch
from typing_extensions import override
from comfy_api.latest import ComfyExtension, io
def loglinear_interp(t_steps, num_steps):
"""
@ -19,25 +23,30 @@ NOISE_LEVELS = {"SD1": [14.6146412293, 6.4745760956, 3.8636745985, 2.694615152
"SDXL":[14.6146412293, 6.3184485287, 3.7681790315, 2.1811480769, 1.3405244945, 0.8620721141, 0.5550693289, 0.3798540708, 0.2332364134, 0.1114188177, 0.0291671582],
"SVD": [700.00, 54.5, 15.886, 7.977, 4.248, 1.789, 0.981, 0.403, 0.173, 0.034, 0.002]}
class AlignYourStepsScheduler:
class AlignYourStepsScheduler(io.ComfyNode):
@classmethod
def INPUT_TYPES(s):
return {"required":
{"model_type": (["SD1", "SDXL", "SVD"], ),
"steps": ("INT", {"default": 10, "min": 1, "max": 10000}),
"denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
}
}
RETURN_TYPES = ("SIGMAS",)
CATEGORY = "sampling/custom_sampling/schedulers"
FUNCTION = "get_sigmas"
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id="AlignYourStepsScheduler",
category="sampling/custom_sampling/schedulers",
inputs=[
io.Combo.Input("model_type", options=["SD1", "SDXL", "SVD"]),
io.Int.Input("steps", default=10, min=1, max=10000),
io.Float.Input("denoise", default=1.0, min=0.0, max=1.0, step=0.01),
],
outputs=[io.Sigmas.Output()],
)
def get_sigmas(self, model_type, steps, denoise):
# Deprecated: use the V3 schema's `execute` method instead of this.
return AlignYourStepsScheduler().execute(model_type, steps, denoise).result
@classmethod
def execute(cls, model_type, steps, denoise) -> io.NodeOutput:
total_steps = steps
if denoise < 1.0:
if denoise <= 0.0:
return (torch.FloatTensor([]),)
return io.NodeOutput(torch.FloatTensor([]))
total_steps = round(steps * denoise)
sigmas = NOISE_LEVELS[model_type][:]
@ -46,8 +55,15 @@ class AlignYourStepsScheduler:
sigmas = sigmas[-(total_steps + 1):]
sigmas[-1] = 0
return (torch.FloatTensor(sigmas), )
return io.NodeOutput(torch.FloatTensor(sigmas))
NODE_CLASS_MAPPINGS = {
"AlignYourStepsScheduler": AlignYourStepsScheduler,
}
class AlignYourStepsExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[io.ComfyNode]]:
return [
AlignYourStepsScheduler,
]
async def comfy_entrypoint() -> AlignYourStepsExtension:
return AlignYourStepsExtension()

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@ -1,3 +1,3 @@
# This file is automatically generated by the build process when version is
# updated in pyproject.toml.
__version__ = "0.3.56"
__version__ = "0.3.57"

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@ -1,6 +1,6 @@
[project]
name = "ComfyUI"
version = "0.3.56"
version = "0.3.57"
readme = "README.md"
license = { file = "LICENSE" }
requires-python = ">=3.9"

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@ -1,5 +1,5 @@
comfyui-frontend-package==1.25.11
comfyui-workflow-templates==0.1.73
comfyui-workflow-templates==0.1.75
comfyui-embedded-docs==0.2.6
torch
torchsde