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for epoch in range(10): # loop over the dataset multiple times train(model, device, trainloader, optimizer, criterion) Meanwhile, Coloso Torrent had given her access to
# For feature extraction, you would pass data through the model and grab outputs from certain layers # For simplicity, let's say you want features from the first convolutional layer def extract_features(model, data): model.eval() with torch.no_grad(): features = model.conv1(data) return features teaching not just how to model
