Method sample_problem

dwave/cloud/solver.py:1355–1402

Sample from the specified problem. Args: problem: A 3-tuple with linear/quadratic terms of the model and the offset. problem_type: Problem type, one of the handled problem types by the solver. undirected_biases:

(self,
                       problem: tuple[list | dict[int, float],
                                      dict[tuple[int, int], float],
                                      float],
                       *,
                       problem_type: Literal['ising', 'qubo'] = 'ising',
                       undirected_biases: bool = False,
                       label: str | None = None,
                       upload_params: dict | None = None,
                       **sample_params: Any,
                       )

        return problem, params

    def sample_problem(self,
                       problem: tuple[list | dict[int, float],
                                      dict[tuple[int, int], float],
                                      float],
                       *,
                       problem_type: Literal['ising', 'qubo'] = 'ising',
                       undirected_biases: bool = False,
                       label: str | None = None,
                       upload_params: dict | None = None,
                       **sample_params: Any,
                       ) -> Future:
        """Sample from the specified problem.

        Args:
            problem:
                A 3-tuple with linear/quadratic terms of the model and the offset.

            problem_type:
                Problem type, one of the handled problem types by the solver.

            undirected_biases:
                Are (quadratic) biases specified on undirected edges? For
                triangular or symmetric matrix of quadratic biases set it to
                ``True``.

            label:
                Problem label you can optionally tag submissions with for ease
                of identification.

            upload_params:
                Optional upload/encode parameters, not used by structured solvers.

            **sample_params:
                Sampling parameters, solver-specific.

        Returns:
            Response in a future.

        Note:
            :meth:`.sample_problem` accepts the native problem formulation for a
            solver, and for structured QPU solvers that's typically the Ising
            form. Calling ``sample_problem()`` with the default arguments is
            equivallent to calling :meth:`.sample_ising`.
        """
        linear, quadratic, offset = problem
        return self._sample(type_=problem_type, linear=linear, quadratic=quadratic,
                            offset=offset, undirected_biases=undirected_biases,
                            label=label, params=sample_params)

    @dispatches_events('sample')
    def _sample(self, type_, linear, quadratic, offset, params,