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Create Academic Training Session From Model

Description

Initialize an Academic Training Session from a DeepLearning Toolkit Model. Type : polymorphic.

 

Input parameters

 

Β Execution Device : enum, selects the hardware device on which the model will run.
Β Model in : object, model architecture.

Β Parameters :Β cluster,

Β max_norm :Β float,Β maximum global gradient norm (enables clipping if > 0).
Β norm_type :Β enum,Β type of norm used to computeΒ grad_normΒ (commonly 1 = L1, 2 = L2).
Β display_norm :Β boolean,Β addsΒ grad_normΒ as a model output if set to 1.
Β independent_loss_model :Β boolean,Β if true, splits the model into 3 stages (forward, loss, backward) instead of 2 (forward+loss, backward).

checkpoint generationΒ :Β enum,Β definesΒ what is saved in the checkpoint: "Weight" (weights only) or "Weight + Momentum" (weights and optimizer momentums). Momentums must already be set in the "Model in".

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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