Configuring the optimizer
Now that we have training logic, we need to specify how to optimize the model's parameters.
In this exercise, you'll complete the configure_optimizers method within a PyTorch Lightning module used for image classification tasks. Your goal is to set up an optimizer that will update the model's parameters during training. To complete this you'll use the Adam optimizer with a learning rate of 1e-3.
Bu egzersiz
Scalable AI Models with PyTorch Lightning
kursunun bir parçasıdırEgzersiz talimatları
- Create an Adam optimizer using the model's parameters, setting the learning rate to
1e-3.
Uygulamalı interaktif egzersiz
Bu örnek kodu tamamlayarak bu egzersizi bitirin.
import torch
def configure_optimizers(self):
# Create an Adam optimizer for model parameters
optimizer = ____
return optimizer