tf.linalg.eig

Computes the eigen decomposition of a batch of matrices.

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tf.eig

tf.linalg.eig(
    tensor, name=None
)

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]. Sorted in non-decreasing order.
v	Eigenvectors. Shape is [..., N, N]. The columns of the inner most matrices contain eigenvectors of the corresponding matrices in tensor