Model

Create Academic Training Session From Model

Description

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

 

Documentation illustration (illustration unavailable in the archive).

Input parameters

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

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

checkpoint generation : enum, defines 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".
Documentation illustration (illustration unavailable in the archive).

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).