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Mono Loss Input 4D

Description

Execute train backward with Mono 4D Float Input Data (Academic Training Session).

Input parameters

 

Β Academic Training inΒ :Β object,Β academic training session.
Β update? :Β boolean,Β indicating whether to update the model weights at this step. If set toΒ false, gradients are only accumulated without updating the weights.
4D Loss Input Data : array, 4D 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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