Model workflow

 

1. Data (preparing and loading)

 

 

2. Build model

3. Train model

 

PyTorch training loop

 

PyTorch testing loop

 

4. Inference

# 1. Set the model in evaluation mode
model_0.eval()

# 2. Setup the inference mode context manager
with torch.inference_mode():
  # 3. Make sure the calculations are done with the model and data on the same device
  # in our case, we haven't setup device-agnostic code yet so our data and model are
  # on the CPU by default.
  # model_0.to(device)
  # X_test = X_test.to(device)
  y_preds = model_0(X_test)
y_preds

 

5. Saving and loading a PyTorch model