Repeater 🐍

Documentation

• Class name: Repeater_pysssss
• Category: utils
• Output node: False

The Repeater node is designed to duplicate a given input source a specified number of times, with the ability to output either as a single node or multiple nodes based on the mode selected. It abstracts the functionality of repeating data, facilitating the creation of multiple instances of data or nodes within a workflow.

Input types

Required

• source
  • The source input represents the data to be repeated. Its role is crucial as it determines the base content that will be duplicated according to the specified repeat count.
  • Comfy dtype: *
  • Python dtype: AnyType
• repeats
  • Specifies the number of times the source input should be repeated. This parameter directly influences the output by determining the quantity of the duplicated data.
  • Comfy dtype: INT
  • Python dtype: int
• output
  • Determines whether the repeated data should be output as a single node or multiple nodes, affecting the structure of the output.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• node_mode
  • Controls whether the repeated nodes are reused or newly created, impacting the way nodes are added to the graph when serialized.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str

Output types

• *
  • Comfy dtype: *
  • The output is a list of repeated data, which can vary in structure based on the output and node_mode parameters.
  • Python dtype: List[AnyType]

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class Repeater:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": {
            "source": (any, {}),
            "repeats": ("INT", {"min": 0, "max": 5000, "default": 2}),
            "output": (["single", "multi"], {}),
            "node_mode": (["reuse", "create"], {}),
        }}

    RETURN_TYPES = (any,)
    FUNCTION = "repeat"
    OUTPUT_NODE = False
    OUTPUT_IS_LIST = (True,)

    CATEGORY = "utils"

    def repeat(self, repeats, output, node_mode, **kwargs):
        if output == "multi":
            # Multi outputs are split to indiviual nodes on the frontend when serializing
            return ([kwargs["source"]],)
        elif node_mode == "reuse":
            # When reusing we have a single input node, repeat that N times
            return ([kwargs["source"]] * repeats,)
        else:
            # When creating new nodes, they'll be added dynamically when the graph is serialized
            return ((list(kwargs.values())),)