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src/core/test_optimization.py

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+import torch
+from optimization import conjugate_gradient
+
+def test_cg_eye():
+    A = torch.eye(2)
+    b = torch.tensor([1., 2.])
+    x1 = conjugate_gradient(lambda x: A @ x, b, 2)
+    x2 = torch.inverse(A) @ b
+    assert torch.allclose(x1, x2)
+
+def test_cg_eyep1():
+    A = torch.eye(2) + 1
+    b = torch.tensor([1., 2.])
+    x1 = conjugate_gradient(lambda x: A @ x, b, 2)
+    x2 = torch.inverse(A) @ b
+    assert torch.allclose(x1, x2, atol=1e-7)
+
+def test_cg3():
+    A = torch.tensor([[4., 2.], [2., 4.]])
+    b = torch.tensor([2., 1.])
+    x1 = conjugate_gradient(lambda x: A @ x, b, 100)
+    x2 = torch.inverse(A) @ b
+    assert torch.allclose(x1, x2)