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tf.self_adjoint_eigvals

Aliases:

  • tf.linalg.eigvalsh
  • tf.self_adjoint_eigvals
self_adjoint_eigvals(
    tensor,
    name=None
)

Defined in tensorflow/python/ops/linalg_ops.py.

See the guide: Math > Matrix Math Functions

Computes the eigenvalues of one or more self-adjoint matrices.

Note: If your program backpropagates through this function, you should replace it with a call to tf.self_adjoint_eig (possibly ignoring the second output) to avoid computing the eigen decomposition twice. This is because the eigenvectors are used to compute the gradient w.r.t. the eigenvalues. See _SelfAdjointEigV2Grad in linalg_grad.py.

Args:

  • tensor: Tensor of shape [..., N, N].
  • name: string, optional name of the operation.

Returns:

  • e: Eigenvalues. Shape is [..., N]. The vector e[..., :] contains the N eigenvalues of tensor[..., :, :].

© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/self_adjoint_eigvals