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UpdatedAugust 4, 2025
Mono Loss Input 2D
Description
Execute inference forward with Mono 2D Float Input Data (Academic Training Session).
Input parameters
Academic Training in : object, academic training session.
2D Input Data : array, 2D array of data with any type : integers (signed/unsigned), floats, doubles, booleans, or strings.
Output parameters
Academic Training out : object, academic training session.
Example
All these exemples are snippets PNG, you can drop these Snippet onto the block diagram and get the depicted code added to your VI (Do not forget to install Deep Learning library to run it).
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