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import torch import torch.nn as nn import torchvision import torchvision.transforms as transforms

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# Train the model for epoch in range(10): for i, data in enumerate(trainloader): inputs, labels = data optimizer.zero_grad() outputs = model(inputs) loss = criterion(outputs, labels) loss.backward() optimizer.step() data in enumerate(trainloader): inputs