finished chapter 5

04_backpropagation.py

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+import torch
+
+x = torch.tensor(1.0)
+y = torch.tensor(2.0)
+
+w = torch.tensor(1.0, requires_grad=True)
+
+#forward path and compute loss
+y_hat = w*x
+loss = (y_hat-y)**2
+
+print(loss)
+
+#backward path
+loss.backward()
+print(w.grad)
+
+### update weights
+### next forward and backwards