Sample Settings 🎭🅐🅓

Documentation

• Class name: ADE_AnimateDiffSamplingSettings
• Category: Animate Diff 🎭🅐🅓
• Output node: False

This node is designed to configure and apply advanced sampling settings for the AnimateDiff process, enabling precise control over the animation generation process through detailed sampling parameters.

Input types

Required

• batch_offset
  • Specifies the offset for the batch processing, allowing for sequential or staggered processing of animation frames.
  • Comfy dtype: INT
  • Python dtype: int
• noise_type
  • Defines the type of noise to be applied during the sampling process, influencing the texture and details of the generated animation.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• seed_gen
  • Determines the seed generation strategy, ensuring reproducibility or variability in the animation outcomes.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• seed_offset
  • Adjusts the seed value by a specified offset, enabling variations in the animation while maintaining a degree of control.
  • Comfy dtype: INT
  • Python dtype: int

Optional

• noise_layers
  • Optional parameter that allows for the customization of noise layers, further refining the animation's visual characteristics.
  • Comfy dtype: NOISE_LAYERS
  • Python dtype: NoiseLayerGroup
• iteration_opts
  • Provides additional iteration options to fine-tune the animation process, such as step adjustments and caching strategies.
  • Comfy dtype: ITERATION_OPTS
  • Python dtype: IterationOptions
• seed_override
  • Directly overrides the seed value, offering an alternative method for controlling the animation's randomness.
  • Comfy dtype: INT
  • Python dtype: int
• adapt_denoise_steps
  • Enables or disables the adaptation of denoise steps based on the animation's requirements, optimizing the generation process.
  • Comfy dtype: BOOLEAN
  • Python dtype: bool
• custom_cfg
  • Allows for the integration of custom configuration settings, enhancing the flexibility and creativity of the animation.
  • Comfy dtype: CUSTOM_CFG
  • Python dtype: CustomCFGKeyframeGroup
• sigma_schedule
  • Specifies a sigma schedule to be used during sampling, affecting the diffusion process and the animation's smoothness.
  • Comfy dtype: SIGMA_SCHEDULE
  • Python dtype: SigmaSchedule

Output types

• settings
  • Comfy dtype: SAMPLE_SETTINGS
  • Returns the configured sampling settings, ready to be applied to the AnimateDiff process.
  • Python dtype: SampleSettings

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class SampleSettingsNode:
    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "batch_offset": ("INT", {"default": 0, "min": 0, "max": BIGMAX}),
                "noise_type": (NoiseLayerType.LIST,),
                "seed_gen": (SeedNoiseGeneration.LIST,),
                "seed_offset": ("INT", {"default": 0, "min": BIGMIN, "max": BIGMAX}),
            },
            "optional": {
                "noise_layers": ("NOISE_LAYERS",),
                "iteration_opts": ("ITERATION_OPTS",),
                "seed_override": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "forceInput": True}),
                "adapt_denoise_steps": ("BOOLEAN", {"default": False},),
                "custom_cfg": ("CUSTOM_CFG",),
                "sigma_schedule": ("SIGMA_SCHEDULE",),
            }
        }

    RETURN_TYPES = ("SAMPLE_SETTINGS",)
    RETURN_NAMES = ("settings",)
    CATEGORY = "Animate Diff 🎭🅐🅓"
    FUNCTION = "create_settings"

    def create_settings(self, batch_offset: int, noise_type: str, seed_gen: str, seed_offset: int, noise_layers: NoiseLayerGroup=None,
                        iteration_opts: IterationOptions=None, seed_override: int=None, adapt_denoise_steps=False,
                        custom_cfg: CustomCFGKeyframeGroup=None, sigma_schedule: SigmaSchedule=None):
        sampling_settings = SampleSettings(batch_offset=batch_offset, noise_type=noise_type, seed_gen=seed_gen, seed_offset=seed_offset, noise_layers=noise_layers,
                                           iteration_opts=iteration_opts, seed_override=seed_override, adapt_denoise_steps=adapt_denoise_steps,
                                           custom_cfg=custom_cfg, sigma_schedule=sigma_schedule)
        return (sampling_settings,)