tf.eig

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Computes the eigen decomposition of a batch of matrices.

Aliases:

  • tf.compat.v2.eig
  • tf.compat.v2.linalg.eig
  • tf.linalg.eig
tf.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