Pytorch, Machine Learning, Gradient Descent, Python, Hands On Tutorials.
epochs=100, momentum=0, weight_decay=0, dampening=0, nesterov=False): fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2) for loss_fn, title, ax in [ (torch.nn.MSELoss(), 'MSELoss', ax1), (torch.nn.L1Loss(), 'L1Loss', ax2), (torch.nn.HuberLoss(), 'HuberLoss', ax3), (torch.nn.SmoothL1Loss(),