def _set_graph_parents(self, graph_parents):
"""Set self._graph_parents. Called during derived class init.
This method allows derived classes to set graph_parents, without triggering
a deprecation warning (which is invoked if `graph_parents` is passed during
`__init__`.
Args:
graph_parents: Iterable over Tensors.
"""
# TODO(b/143910018) Remove this function in V3.
graph_parents = [] if graph_parents is None else graph_parents
for i, t in enumerate(graph_parents):
if t is None or not (linear_operator_util.is_ref(t) or
tensor_util.is_tensor(t)):
raise ValueError("Graph parent item %d is not a Tensor; %s." % (i, t))
self._graph_parents = graph_parents
def __init__(self,
dtype,
graph_parents=None,
is_non_singular=None,
is_self_adjoint=None,
is_positive_definite=None,
is_square=None,
name=None):
r"""Initialize the `LinearOperator`.
**This is a private method for subclass use.**
**Subclasses should copy-paste this `__init__` documentation.**
Args:
dtype: The type of the this `LinearOperator`. Arguments to `matmul` and
`solve` will have to be this type.
graph_parents: (Deprecated) Python list of graph prerequisites of this
`LinearOperator` Typically tensors that are passed during initialization
is_non_singular: Expect that this operator is non-singular.
is_self_adjoint: Expect that this operator is equal to its hermitian
transpose. If `dtype` is real, this is equivalent to being symmetric.
is_positive_definite: Expect that this operator is positive definite,
meaning the quadratic form `x^H A x` has positive real part for all
nonzero `x`. Note that we do not require the operator to be
self-adjoint to be positive-definite. See:
https://en.wikipedia.org/wiki/Positive-definite_matrix#Extension_for_non-symmetric_matrices
is_square: Expect that this operator acts like square [batch] matrices.
name: A name for this `LinearOperator`.
Raises:
ValueError: If any member of graph_parents is `None` or not a `Tensor`.
ValueError: If hints are set incorrectly.
"""
# Check and auto-set flags.
if is_positive_definite:
if is_non_singular is False:
raise ValueError("A positive definite matrix is always non-singular.")
is_non_singular = True
if is_non_singular:
if is_square is False:
raise ValueError("A non-singular matrix is always square.")
is_square = True
if is_self_adjoint:
if is_square is False:
raise ValueError("A self-adjoint matrix is always square.")
is_square = True
self._is_square_set_or_implied_by_hints = is_square
graph_parents = [] if graph_parents is None else graph_parents
for i, t in enumerate(graph_parents):
if t is None or not (linear_operator_util.is_ref(t) or
tensor_util.is_tensor(t)):
raise ValueError("Graph parent item %d is not a Tensor; %s." % (i, t))
self._dtype = dtypes.as_dtype(dtype).base_dtype if dtype else dtype
self._graph_parents = graph_parents
self._is_non_singular = is_non_singular
self._is_self_adjoint = is_self_adjoint
self._is_positive_definite = is_positive_definite
self._name = name or type(self).__name__