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ROCm always use numpy on cholesky

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Disty0
2025-09-28 14:05:20 +03:00
parent a47959b114
commit 4a70e82b0c
2 changed files with 7 additions and 8 deletions
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modules/devices.py
+2
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@@ -48,9 +48,11 @@ def has_mps() -> bool:
def has_xpu() -> bool:
return bool(hasattr(torch, 'xpu') and torch.xpu.is_available())
def has_rocm() -> bool:
return bool(torch.version.hip is not None and torch.cuda.is_available())
def has_zluda() -> bool:
if not cuda_ok:
return False
modules/rocm.py
+5 -8
View File
@@ -251,12 +251,10 @@ if sys.platform == "win32":
cholesky_ex_gpu = torch.linalg.cholesky_ex
@wraps(cholesky_ex_gpu)
def cholesky_ex(A: torch.Tensor, upper=False, check_errors=False, out=None) -> torch.return_types.linalg_cholesky_ex:
if A.device.type != 'cpu':
return cholesky_ex_gpu(A, upper=upper, check_errors=check_errors, out=out)
assert not check_errors
L = torch.from_numpy(np.linalg.cholesky(A.numpy(), upper=upper))
info = torch.tensor(0, dtype=torch.int32, device='cpu')
return_device = A.device
L = torch.from_numpy(np.linalg.cholesky(A.to("cpu").numpy(), upper=upper)).to(return_device)
info = torch.tensor(0, dtype=torch.int32, device=return_device)
if out is not None:
out[0].copy_(L)
out[1].copy_(info)
@@ -266,9 +264,8 @@ if sys.platform == "win32":
cholesky_gpu = torch.linalg.cholesky
@wraps(cholesky_gpu)
def cholesky(A: torch.Tensor, upper=False, out=None) -> torch.Tensor:
if A.device.type != 'cpu':
return cholesky_gpu(A, upper=upper, out=out)
L = torch.from_numpy(np.linalg.cholesky(A.numpy(), upper=upper))
return_device = A.device
L = torch.from_numpy(np.linalg.cholesky(A.to("cpu").numpy(), upper=upper)).to(return_device)
if out is not None:
out.copy_(L)
return L