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[..., :, :]`.
"""
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[..., :, :]`.
"""
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`
"""
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`
"""
e, v = gen_linalg_ops.batch_self_adjoint_eig_v2(
tensor, compute_v=True, name=name)
return e, v
