Deep Learning, Regularization Techniques, Python Programming, Data Science, Technology.
batch_size=10, shuffle=True, num_workers=1) # Initialize the MLP mlp = MLP() # Define the loss function and optimizer loss_function = nn.CrossEntropyLoss() optimizer = torch.optim.Adam(mlp.parameters(), lr=1e-4) # Run the training loop for epoch in range(0, 5): # 5 epochs at maximum # Print epoch