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Mono Loss Input 1D

Description

Execute train forward with Mono 1D Float Input Data (Academic Training Session).

Input parameters

 

Β Academic Training inΒ :Β object,Β academic training session.
1D Input Data : array, 1D array of data with any type : integers (signed/unsigned), floats, doubles, booleans, or strings.

 

Output parameters

 

Β Academic TrainingΒ outΒ :Β object,Β 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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