Model Training and Predictions
Learn about running a classy pipeline for the model training and making predictions steps.
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Starting steps
We start by instantiating the StepByStep class with the corresponding arguments. Next, we set its loaders using the appropriately named function set_loaders. Then, we set up an interface with TensorBoard, and then name our experiment “classy.”
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sbs = StepByStep(model, loss_fn, optimizer)sbs.set_loaders(train_loader, val_loader)sbs.set_tensorboard('classy')
One important thing to notice is that the model attribute of the sbs object is the same object as the model variable created in the model configuration. It is not a ...