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# PyTorch torch.eig Function * * PyTorch torch Reference Manual](#) `torch.eig` is a PyTorch function for computing eigenvalues and eigenvectors of square matrices. It returns all eigenvalues and right eigenvectors of a matrix. ### Function Definition torch.eig(A, eigenvectors=False, out=None) **Parameters**: * `A` (Tensor): Input square matrix. * `eigenvectors` (bool, optional): If True, computes eigenvectors as well. Default is False. * `out` (tuple, optional): Output tuple. **Returns**: * `tuple`: Returns (eigenvalues, eigenvectors) tuple. * * * ## Usage Example ## Example import torch # Create square matrix A = torch.tensor([[1.0,2.0],[3.0,4.0]]) # Calculate eigenvalues eigenvalues, eigenvectors = torch.eig(A, eigenvectors=True) print("Matrix A:") print(A) print("nEigenvalues:") print(eigenvalues) print("nEigenvectors:") print(eigenvectors) Output: Matrix A: tensor([[1., 2.], [3., 4.]])Eigenvalues: tensor([[-0.3723, 0.0000], [ 5.3723, 0.0000]])Eigenvectors: tensor([[-0.8246, -0.4159], [ 0.5658, -0.9094]]) * * PyTorch torch Reference Manual](#) AI Processing... [](#)(#) [PyTorch torch.nn Reference Manual](#)[](#) [ByteArk Coding Plan supports Doubao, GLM, DeepSeek, Kimi, MiniMax mainstream large models, official direct supply stable and reliable. Configuration Guide ¥9.9/month Immediate Activation](https://maas.xfyun.cn/modelSquare?ch=maas_lm_l2E)