PyTorch torch.svd Function
PyTorch torch Reference Manual
torch.svdIt is a function in PyTorch used to compute the singular value decomposition of a matrix.
Function Definition
torch.svd(input, some, compute_uv, out)
Usage Example
Example
import torch
A = torch.randn(3, 4)
# SVD decomposition
U, S, V = torch.svd(A)
print("U shape:", U.shape)
print("S shape:", S.shape)
print("V shape:", V.shape)
A = torch.randn(3, 4)
# SVD decomposition
U, S, V = torch.svd(A)
print("U shape:", U.shape)
print("S shape:", S.shape)
print("V shape:", V.shape)
The output is:
U 形状: torch.Size([3, 3]) S 形状: torch.Size([3]) V 形状: torch.Size([4, 4])
Other Extensions