tf.linalg.diag

TensorFlow 1 version

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

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.linalg.eigh, tf.compat.v1.self_adjoint_eig

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

Used in the notebooks

Used in the tutorials
Quantum data

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`

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tf.linalg / diag

View aliases

Used in the notebooks

Args

Returns