TensorFlow 2.0 Beta is available Learn more

tf.linalg.eigh

TensorFlow 2.0 version View source on GitHub

Computes the eigen decomposition of a batch of self-adjoint matrices.

Aliases:

  • tf.compat.v1.linalg.eigh
  • tf.compat.v1.self_adjoint_eig
  • tf.compat.v2.linalg.eigh
  • tf.self_adjoint_eig
tf.linalg.eigh(
    tensor,
    name=None
)

Computes the eigenvalues and 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