Pytorch, Machine Learning, Gradient Descent, Python, Hands On Tutorials.
model.bias.data.fill_(-3.0) loss_fn = torch.nn.MSELoss() learning_rate = 0.1 epochs = 100 optimizer = torch.optim.SGD(model.parameters(), lr=learning_rate) for epoch in range(epochs): inputs = torch.from_numpy(x).requires_grad_().reshape(-1, 1) labels = torch.from_numpy(y).reshape(-1, 1)