Select Every Nth Latent 🎥🅥🅗🅢

Documentation

• Class name: VHS_SelectEveryNthLatent
• Category: Video Helper Suite 🎥🅥🅗🅢/latent
• Output node: False

This node is designed to filter through a batch of latents, selecting every Nth latent according to a specified interval. It's useful for thinning out dense latent batches for more efficient processing or targeted analysis.

Input types

Required

• latents
  • The input latents to be filtered. This parameter is crucial for determining which latents will be processed and ultimately selected based on the interval.
  • Comfy dtype: LATENT
  • Python dtype: dict
• select_every_nth
  • Specifies the interval at which latents are selected. This parameter directly influences the density of the output latent batch, allowing for customizable thinning of the input.
  • Comfy dtype: INT
  • Python dtype: int

Output types

• LATENT
  • Comfy dtype: LATENT
  • The filtered set of latents, containing only every Nth latent based on the specified interval.
  • Python dtype: dict
• count
  • Comfy dtype: INT
  • The total count of latents selected after applying the specified interval. This provides a quick reference to the size of the output batch.
  • Python dtype: int

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class SelectEveryNthLatent:
    @classmethod
    def INPUT_TYPES(s):
        return {
                "required": {
                    "latents": ("LATENT",),
                    "select_every_nth": ("INT", {"default": 1, "min": 1, "max": BIGMAX, "step": 1}),
                },
            }

    CATEGORY = "Video Helper Suite 🎥🅥🅗🅢/latent"

    RETURN_TYPES = ("LATENT", "INT",)
    RETURN_NAMES = ("LATENT", "count",)
    FUNCTION = "select_latents"

    def select_latents(self, latents: dict, select_every_nth: int):
        sub_latents = latents.copy()["samples"][0::select_every_nth]
        return ({"samples": sub_latents}, sub_latents.size(0))