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Extracts detailed input data info for debugging & understanding, useful for complex data types & AI model optimization.
The LayerUtility: PrintInfo node is designed to provide detailed information about the input data it receives, making it an invaluable tool for debugging and understanding the structure of your data. This node is particularly useful when working with complex data types such as tensors, as it can extract and display key attributes like dimensions and shapes. By converting tensor data into a more readable format, it helps you gain insights into the data's characteristics, which can be crucial for troubleshooting and optimizing your AI models. Additionally, the node attempts to serialize other data types into JSON format, offering a versatile solution for inspecting various kinds of input data.
The anything
parameter accepts any type of input data, including but not limited to tensors, lists, dictionaries, and other Python objects. This parameter is crucial for the node's operation as it determines the type and structure of the data to be analyzed. When a tensor is provided, the node will extract and display detailed information about its dimensions and shape. For other data types, the node will attempt to serialize the data into a JSON format for easier inspection. There are no specific minimum, maximum, or default values for this parameter, as it is designed to be highly flexible and accommodate a wide range of input types.
The text
output parameter provides a string that contains detailed information about the input data. This string includes the type of the input data and, if the input is a tensor, additional details such as its dimensions and shape. For other data types, the node attempts to serialize the data into a JSON format. This output is essential for understanding the characteristics of the input data, making it easier to debug and optimize your AI models.
None
or not provided.None
. Ensure that the preceding nodes in your workflow are producing valid output.© Copyright 2024 RunComfy. All Rights Reserved.