Note: If your program backpropagates through this function, you should replace it with a call to tf.linalg.eigh (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[..., :, :].
