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FromBasicPipe

Documentation

  • Class name: FromBasicPipe
  • Category: ImpactPack/Pipe
  • Output node: False

The FromBasicPipe node is designed to decompose a basic pipe structure into its constituent components, facilitating access to individual elements such as models, clips, and VAEs for further processing or analysis.

Input types

Required

  • basic_pipe
    • Represents the basic pipe structure encapsulating a model, clip, VAE, and positive and negative conditioning elements. It serves as the input for decomposition into its constituent components.
    • Comfy dtype: BASIC_PIPE
    • Python dtype: Tuple[torch.nn.Module, torch.nn.Module, torch.nn.Module, torch.Tensor, torch.Tensor]

Output types

  • model
    • Comfy dtype: MODEL
    • The model component extracted from the basic pipe.
    • Python dtype: torch.nn.Module
  • clip
    • Comfy dtype: CLIP
    • The clip component extracted from the basic pipe.
    • Python dtype: torch.nn.Module
  • vae
    • Comfy dtype: VAE
    • The VAE component extracted from the basic pipe.
    • Python dtype: torch.nn.Module
  • positive
    • Comfy dtype: CONDITIONING
    • The positive conditioning element extracted from the basic pipe.
    • Python dtype: torch.Tensor
  • negative
    • Comfy dtype: CONDITIONING
    • The negative conditioning element extracted from the basic pipe.
    • Python dtype: torch.Tensor

Usage tips

Source code

class FromBasicPipe:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": {"basic_pipe": ("BASIC_PIPE",), }, }

    RETURN_TYPES = ("MODEL", "CLIP", "VAE", "CONDITIONING", "CONDITIONING")
    RETURN_NAMES = ("model", "clip", "vae", "positive", "negative")
    FUNCTION = "doit"

    CATEGORY = "ImpactPack/Pipe"

    def doit(self, basic_pipe):
        model, clip, vae, positive, negative = basic_pipe
        return model, clip, vae, positive, negative