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wang-chen
requested changes
Dec 7, 2023
wang-chen
requested changes
Dec 8, 2023
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This test doesn't follow the existing style. Refer to this test or this test with predefined data. Use class style.
pypose/optim/solver.py
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| if self.maxiter is None: | ||
| maxiter = n*10 | ||
| else: | ||
| maxiter = self.maxiter | ||
| r = b - bmv(A, x) if x.any() else b.clone() | ||
| rho_prev, p = None, None | ||
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| for iteration in range(maxiter): | ||
| if (torch.linalg.norm(r, dim=-1) < atol).all(): | ||
| return x | ||
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| z = bmv(M, r) if M is not None else r | ||
| rho_cur = vecdot(r, z) | ||
| if iteration > 0: | ||
| beta = rho_cur / rho_prev | ||
| p = p * beta.unsqueeze(-1) + z | ||
| else: # First spin | ||
| p = torch.empty_like(r) | ||
| p[:] = z[:] | ||
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| q = bmv(A, p) | ||
| alpha = rho_cur / vecdot(p, q) | ||
| x += alpha.unsqueeze(-1)*p | ||
| r -= alpha.unsqueeze(-1)*q | ||
| rho_prev = rho_cur | ||
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| else: # for loop exhausted | ||
| # Return incomplete progress | ||
| return x |
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how about
if self.maxiter is None:
maxiter = n * 10
else:
maxiter = self.maxiter
r = b - bmv(A, x) if x.any() else b.clone()
p = torch.empty_like(r)
rho_prev, p[:]= None, z[:]
for iteration in range(maxiter):
if (torch.linalg.norm(r, dim=-1) < atol).all():
return x
z = bmv(M, r) if M is not None else r
rho_cur = vecdot(r, z)
beta = rho_cur / rho_prev
p = p * beta.unsqueeze(-1) + z
q = bmv(A, p)
alpha = rho_cur / vecdot(p, q)
x += alpha.unsqueeze(-1)*p
r -= alpha.unsqueeze(-1)*q
rho_prev = rho_cur
return x
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Author
There was a problem hiding this comment.
z has to be defined before it is used in rho_prev, p[:]= None, z[:]
wang-chen
approved these changes
Dec 8, 2023
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Add cg solver
Solve #311