Karpathy_ZtH_Learning/My_Experiments/pytorch2.ipynb

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import torch

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X = torch.tensor([[1.0],[2.0],[3.0]])
y = torch.tensor([[4.0],[5.0],[6.0]])

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w = torch.randn(1, requires_grad=True)
b = torch.randn(1, requires_grad=True)

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for _ in range(100):
    y_pred = X @ w + b
    loss = ((y_pred - y) ** 2).mean()
    loss.backward()
    with torch.no_grad():
        w -= 0.05 * w.grad
        b -= 0.05 * w.grad
        w.grad.zero_()
        b.grad.zero_()

print(w.item(),b.item())

0.4485014081001282 3.9534966945648193

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