Pytorch, Machine Learning, Gradient Descent, Python, Hands On Tutorials.
'SmoothL1Loss', ax4), ]: losses = get_loss_map(loss_fn, x, y) model, models = learn( loss_fn, x, y, lr=lr, epochs=epochs, momentum=momentum, weight_decay=weight_decay, dampening=dampening, nesterov=nesterov) cm = pylab.get_cmap('terrain') i = ax.imshow(losses, cmap=cm, interpolation='nearest',