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| Classic with PyTorch Tensor | PyTorch Enhanced |
|---|---|
| import torch | |
| t_c = [0.5, 14.0, 15.0, 28.0, 11.0, 8.0, 3.0, -4.0, 6.0, 13.0, 21.0] t_u = [35.7, 55.9, 58.2, 81.9, 56.3, 48.9, 33.9, 21.8, 48.4, 60.4, 68.4] t_c = torch.tensor(t_c) t_u = torch.tensor(t_u) |
|
| def model(t_u, w, b): return w * t_u + b |
|
| def loss_fn(t_p, t_c): squared_diffs = (t_p - t_c)**2 return squared_diffs.mean() |
|
| w = torch.ones(()) b = torch.zeros(()) print(w, b) t_p = model(t_u, w, b) |
params = torch.tensor([1.0, 0.0], requires_grad=True) params.grad is None |
| loss = loss_fn(t_p, t_c) | loss = loss_fn(model(t_u, *params), t_c) loss.backward() params.grad |
| elta = 0.1 learning_rate = 1e-2 |
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