PyTorch torch.linalg.eig Function
Pytorch torch Reference Manual
torch.linalg.eigIt is a function in the PyTorch linear algebra module used to compute the eigenvalue decomposition of square matrices. It returns all eigenvalues and right eigenvectors of the matrix.
Function Definition
torch.linalg.eig(A, out=None)
Parameters:
A(Tensor): Input square matrix.out(tuple, optional): Output tuple.
Return Value:
tuple: Returns a tuple of (eigenvalues, eigenvectors).
Usage Example
Example
import torch
# Create a square matrix
A = torch.tensor([[1.0, 2.0], [3.0, 4.0]], dtype=torch.complex128)
# Eigenvalue decomposition
eigenvalues, eigenvectors = torch.linalg.eig(A)
print(Matrix A:)
print(A)
print(nEigenvalues:)
print(eigenvalues)
print(nEigenvectors:)
print(eigenvectors)
# Create a square matrix
A = torch.tensor([[1.0, 2.0], [3.0, 4.0]], dtype=torch.complex128)
# Eigenvalue decomposition
eigenvalues, eigenvectors = torch.linalg.eig(A)
print(Matrix A:)
print(A)
print(nEigenvalues:)
print(eigenvalues)
print(nEigenvectors:)
print(eigenvectors)
The output result is:
矩阵 A:
tensor([[1., 2.],
[3., 4.]], dtype=torch.complex128)
特征值:
tensor([-0.3723+0.j, 5.3723+0.j], dtype=torch.complex128)
特征向量:
tensor([[-0.8246+0.j, -0.4159+0.j],
[ 0.5658+0.j, -0.9094+0.j]], dtype=torch.complex128)
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