Pytorch, Machine Learning, Gradient Descent, Python, Hands On Tutorials.
performing: model = torch.nn.Linear(1, 1) ... models = [[model.weight.item(), model.bias.item()]] for epoch in range(epochs): ... print('epoch {}, loss {}'.format(epoch, loss.item())) models.append([model.weight.item(), model.bias.item()]) # Plot model parameters against the loss map. cm =