Image Classification and CNN
Building a CNN Classifier with PyTorch: Part 1
Building a CNN Classifier with PyTorch: Part 2
Introduction to DDP with PyTorch
Single Node Multi-GPU Training with torchrun
Multi-node Distributed Training with PyTorch
Lab Setup

Training the Neural Network

Define Loss Function and Optimizer

Now that we have our dataloaders set up and our model architecture built, we are ready to train our model. To train the model, we need to set up a loss function and an optimizer to optimize that loss function. Below we instantiate the Cross Entropy Loss function and the Adam optimizer.

Note that we are using the learning rate hyperparameter specified at the the top of this notebook.

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CVW material development is supported by NSF OAC awards 1854828, 2321040, 2323116 (UT Austin) and 2005506 (Indiana University)