30 lines
455 B
Python
30 lines
455 B
Python
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#!/usr/bin/python3
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import torch
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m = torch.tensor([[2., 1.], [-1., 2.]])
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def fun(x):
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return m @ x
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def loss(y):
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return torch.sum((y - torch.tensor([3., 2.]))**2)
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x = torch.rand(2, requires_grad=True)
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learning_rate = torch.tensor(0.01)
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for _ in range(100):
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y = fun(x)
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cost = loss(y)
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print(x, " => ", y, " ", cost)
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cost.backward()
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with torch.no_grad():
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x = x - learning_rate * x.grad
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x.requires_grad_(True)
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