def batch_self_adjoint_eigvals(tensor, name=None): """Computes the eigenvalues of a batch of self-adjoint matrices. 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[..., :, :]`. """ # pylint: disable=protected-access e, _ = gen_linalg_ops._batch_self_adjoint_eig_v2( tensor, compute_v=False, name=name) return e
def batch_self_adjoint_eigvals(tensor, name=None): """Computes the eigenvalues of a batch of self-adjoint matrices. 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[..., :, :]`. """ # pylint: disable=protected-access e, _ = gen_linalg_ops._batch_self_adjoint_eig_v2(tensor, compute_v=False, name=name) return e
def batch_self_adjoint_eig(tensor, name=None): """Computes the eigen decomposition of a batch of self-adjoint matrices. 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]`. name: string, optional name of the operation. Returns: e: Eigenvalues. Shape is `[..., N]`. v: Eigenvectors. Shape is `[..., N, N]`. The columns of the inner most matrices contain eigenvectors of the corresponding matrices in `tensor` """ # pylint: disable=protected-access e, v = gen_linalg_ops._batch_self_adjoint_eig_v2( tensor, compute_v=True, name=name) return e, v
def batch_self_adjoint_eig(tensor, name=None): """Computes the eigen decomposition of a batch of self-adjoint matrices. 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]`. name: string, optional name of the operation. Returns: e: Eigenvalues. Shape is `[..., N]`. v: Eigenvectors. Shape is `[..., N, N]`. The columns of the inner most matrices contain eigenvectors of the corresponding matrices in `tensor` """ # pylint: disable=protected-access e, v = gen_linalg_ops._batch_self_adjoint_eig_v2(tensor, compute_v=True, name=name) return e, v