LostTech.TensorFlow : API Documentation

Type LinearOperatorInversion

Namespace tensorflow.linalg

Parent LinearOperator

Interfaces ILinearOperatorInversion

`LinearOperator` representing the inverse of another operator.

This operator represents the inverse of another operator. #### Performance

The performance of `LinearOperatorInversion` depends on the underlying operators performance: `solve` and `matmul` are swapped, and determinant is inverted.

#### Matrix property hints

This `LinearOperator` is initialized with boolean flags of the form `is_X`, for `X = non_singular, self_adjoint, positive_definite, square`. These have the following meaning:

* If `is_X == True`, callers should expect the operator to have the property `X`. This is a promise that should be fulfilled, but is *not* a runtime assert. For example, finite floating point precision may result in these promises being violated. * If `is_X == False`, callers should expect the operator to not have `X`. * If `is_X == None` (the default), callers should have no expectation either way.
Show Example
# Create a 2 x 2 linear operator.
            operator = LinearOperatorFullMatrix([[1., 0.], [0., 2.]])
            operator_inv = LinearOperatorInversion(operator) 

operator_inv.to_dense() ==> [[1., 0.] [0., 0.5]]

operator_inv.shape ==> [2, 2]

operator_inv.log_abs_determinant() ==> - log(2)

x =... Shape [2, 4] Tensor operator_inv.matmul(x) ==> Shape [2, 4] Tensor, equal to operator.solve(x)


Public properties

object batch_shape get;

object batch_shape_dyn get;

Dimension domain_dimension get;

object domain_dimension_dyn get;

object dtype get;

object dtype_dyn get;

IList<object> graph_parents get;

object graph_parents_dyn get;

Nullable<bool> is_non_singular get;

object is_non_singular_dyn get;

object is_positive_definite get;

object is_positive_definite_dyn get;

object is_self_adjoint get;

object is_self_adjoint_dyn get;

Nullable<bool> is_square get;

object is_square_dyn get;

object name get;

object name_dyn get;

object name_scope get;

object name_scope_dyn get;

object operator get;

object operator_dyn get;

The operator before inversion.

object PythonObject get;

Dimension range_dimension get;

object range_dimension_dyn get;

TensorShape shape get;

object shape_dyn get;

ValueTuple<object> submodules get;

object submodules_dyn get;

Nullable<int> tensor_rank get;

object tensor_rank_dyn get;

object trainable_variables get;

object trainable_variables_dyn get;

object variables get;

object variables_dyn get;