tf.linalg.eig
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Computes the eigen decomposition of a batch of matrices.
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Main aliases
tf.eig
tf.linalg.eig( tensor, name=None )
Used in the notebooks
The eigenvalues and eigenvectors for a non-Hermitian matrix in general are complex. The eigenvectors are not guaranteed to be linearly independent.
Computes the eigenvalues and right eigenvectors of the innermost N-by-N matrices in tensor such that tensor[...,:,:] * v[..., :,i] = e[..., i] * v[...,:,i], for i=0...N-1.
Args |
|---|
tensor | Tensor of shape [..., N, N]. Only the lower triangular part of each inner inner matrix is referenced. |
name | string, optional name of the operation. |
Returns |
|---|
e | Eigenvalues. Shape is [..., N]. The eigenvalues are not necessarily ordered. |
v | Eigenvectors. Shape is [..., N, N]. The columns of the inner most matrices contain eigenvectors of the corresponding matrices in tensor |
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Last updated 2024-04-26 UTC.
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