Skip to content

ToLatentList

Documentation

  • Class name: ToLatentList
  • Category: Bmad/Lists/Make or Intercalate
  • Output node: False

The ToLatentList node is designed to aggregate individual latent representations into a structured list format. This node facilitates the organization and manipulation of latent data by converting disparate latent samples into a cohesive list, making it easier to handle and process multiple latent samples collectively.

Input types

Required

  • inputs_len
    • The inputs_len parameter represents the individual latent samples to be aggregated into a list. This parameter is crucial for collecting and structuring latent data into a format that is more manageable for further processing or analysis.
    • Comfy dtype: INT
    • Python dtype: List[torch.Tensor]

Output types

  • latent
    • Comfy dtype: LATENT
    • The latent output represents the aggregated list of latent samples. This structured format allows for easier manipulation and analysis of multiple latent samples as a collective unit.
    • Python dtype: List[torch.Tensor]

Usage tips

  • Infra type: CPU
  • Common nodes: unknown

Source code

class ToLatentList(metaclass=MakeListMeta): TYPE = "LATENT"