Default Iteration Options 🎭🅐🅓

Documentation

• Class name: ADE_IterationOptsDefault
• Category: Animate Diff 🎭🅐🅓/iteration opts
• Output node: False

This node provides the default iteration options for the AnimateDiff process, allowing users to configure the iteration parameters for their animation generation tasks.

Input types

Required

• iterations
  • Specifies the number of iterations to perform, affecting the depth of the animation generation process.
  • Comfy dtype: INT
  • Python dtype: int

Optional

• iter_batch_offset
  • Determines the starting offset for batch processing within the iterations, enabling fine-tuned control over the animation generation sequence.
  • Comfy dtype: INT
  • Python dtype: int
• iter_seed_offset
  • Sets the seed offset for iterations, offering a way to influence the randomness and variation in the generated animations.
  • Comfy dtype: INT
  • Python dtype: int

Output types

• iteration_opts
  • Comfy dtype: ITERATION_OPTS
  • Outputs the configured iteration options, encapsulating the settings for the animation generation process.
  • Python dtype: IterationOptions

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class IterationOptionsNode:
    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "iterations": ("INT", {"default": 1, "min": 1}),
            },
            "optional": {
                "iter_batch_offset": ("INT", {"default": 0, "min": 0, "max": BIGMAX}),
                "iter_seed_offset": ("INT", {"default": 0, "min": BIGMIN, "max": BIGMAX}),
            }
        }

    RETURN_TYPES = ("ITERATION_OPTS",)
    CATEGORY = "Animate Diff 🎭🅐🅓/iteration opts"
    FUNCTION = "create_iter_opts"

    def create_iter_opts(self, iterations: int, iter_batch_offset: int=0, iter_seed_offset: int=0):
        iter_opts = IterationOptions(iterations=iterations, iter_batch_offset=iter_batch_offset, iter_seed_offset=iter_seed_offset)
        return (iter_opts,)