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Dynamically select conditioning inputs based on parameter for AI art projects.
The Conditioning Switch (JPS) node is designed to dynamically select and output one of several conditioning inputs based on a specified selection parameter. This node is particularly useful in scenarios where you need to switch between different conditioning data sets or configurations during the execution of your AI art generation process. By providing a flexible and efficient way to manage multiple conditioning inputs, the Conditioning Switch (JPS) node helps streamline workflows and enhances the versatility of your AI art projects.
The select
parameter is an integer that determines which conditioning input will be selected and output by the node. The value of select
can range from 1 to 5, with each number corresponding to a different conditioning input. For example, if select
is set to 1, the node will output con_1
; if select
is set to 2, it will output con_2
, and so on. This parameter is required and must be specified for the node to function correctly.
The con_1
parameter is the first conditioning input. This input is required and will be selected if the select
parameter is set to 1. It represents the default conditioning data that the node will output if no other selection is made.
The con_2
parameter is an optional conditioning input. This input will be selected if the select
parameter is set to 2. It allows you to provide an alternative conditioning data set that can be dynamically chosen during execution.
The con_3
parameter is an optional conditioning input. This input will be selected if the select
parameter is set to 3. It provides another alternative conditioning data set for dynamic selection.
The con_4
parameter is an optional conditioning input. This input will be selected if the select
parameter is set to 4. It offers yet another alternative conditioning data set for dynamic selection.
The con_5
parameter is an optional conditioning input. This input will be selected if the select
parameter is set to 5. It provides a fifth alternative conditioning data set for dynamic selection.
The con_out
parameter is the output of the node, representing the selected conditioning input based on the value of the select
parameter. This output is crucial as it determines which conditioning data set will be used in subsequent nodes or processes. The con_out
parameter ensures that the correct conditioning data is dynamically chosen and passed along, enhancing the flexibility and efficiency of your AI art generation workflow.
con_1
to con_5
) even if some of them are optional. This will allow you to switch between different conditioning data sets seamlessly.select
parameter to dynamically change the conditioning input during the execution of your workflow. This can be particularly useful in scenarios where different stages of your AI art generation process require different conditioning data.con_1
parameter is required and must be provided for the node to function correctly.con_1
parameter.select
parameter must be an integer between 1 and 5. - Solution: Verify that the value of the select
parameter is within the valid range and adjust it if necessary.None
).con_2
to con_5
) are provided if they might be selected by the select
parameter.© Copyright 2024 RunComfy. All Rights Reserved.