Create Sigma Schedule 🎭🅐🅓¶
Documentation¶
- Class name:
ADE_SigmaSchedule
- Category:
Animate Diff 🎭🅐🅓/sample settings/sigma schedule
- Output node:
False
The ADE_SigmaSchedule node is designed to generate a sigma schedule based on a given beta schedule. It abstracts the complexity of sigma schedule creation, offering a straightforward way to obtain a sigma schedule tailored to specific model sampling types and configurations.
Input types¶
Required¶
beta_schedule
- Specifies the beta schedule to be used for generating the sigma schedule. This parameter is crucial as it determines the base configuration from which the sigma schedule will be derived.
- Comfy dtype:
COMBO[STRING]
- Python dtype:
BetaSchedules.ALIAS_ACTIVE_LIST
Output types¶
sigma_schedule
- Comfy dtype:
SIGMA_SCHEDULE
- Outputs a sigma schedule object, which is essential for defining the progression of noise levels in diffusion-based generative models.
- Python dtype:
SigmaSchedule (custom type from the animatediff package)
- Comfy dtype:
Usage tips¶
- Infra type:
CPU
- Common nodes: unknown
Source code¶
class SigmaScheduleNode:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"beta_schedule": (BetaSchedules.ALIAS_ACTIVE_LIST,),
}
}
RETURN_TYPES = ("SIGMA_SCHEDULE",)
CATEGORY = "Animate Diff 🎭🅐🅓/sample settings/sigma schedule"
FUNCTION = "get_sigma_schedule"
def get_sigma_schedule(self, beta_schedule: str):
model_type = ModelSamplingType.from_alias(ModelSamplingType.EPS)
new_model_sampling = BetaSchedules._to_model_sampling(alias=beta_schedule,
model_type=model_type)
return (SigmaSchedule(model_sampling=new_model_sampling, model_type=model_type),)