def sample(self, bqm, chain_strength=1.0, chain_break_fraction=True, **parameters):
        """Sample the binary quadratic model.

        Note: At the initial sample(..) call, it will find a suitable embedding and initialize the remaining attributes
        before sampling the bqm. All following sample(..) calls will reuse that initial embedding.

        Args:
            bqm (:obj:`dimod.BinaryQuadraticModel`):
                Binary quadratic model to be sampled from.

            chain_strength (float, optional, default=1.0):
                Magnitude of the quadratic bias (in SPIN-space) applied between variables to create
                chains. Note that the energy penalty of chain breaks is 2 * `chain_strength`.

            chain_break_fraction (bool, optional, default=True):
                If True, a ‘chain_break_fraction’ field is added to the unembedded response which report
                what fraction of the chains were broken before unembedding.

            **parameters:
                Parameters for the sampling method, specified by the child sampler.
        Returns:
            :class:`dimod.SampleSet`
        """
        if self.embedding is None:
            # Find embedding
            child = self.child   # Solve the problem on the child system
            __, target_edgelist, target_adjacency = child.structure
            source_edgelist = list(bqm.quadratic) + [(v, v) for v in bqm.linear]  # Add self-loops for single variables
            embedding = minorminer.find_embedding(source_edgelist, target_edgelist)

            # Initialize properties that need embedding
            super(LazyFixedEmbeddingComposite, self)._set_graph_related_init(embedding=embedding)

        return super(LazyFixedEmbeddingComposite, self).sample(bqm, chain_strength=chain_strength,
                                                               chain_break_fraction=chain_break_fraction, **parameters)
Sample the binary quadratic model.

        Note: At the initial sample(..) call, it will find a suitable embedding and initialize the remaining attributes
        before sampling the bqm. All following sample(..) calls will reuse that initial embedding.

        Args:
            bqm (:obj:`dimod.BinaryQuadraticModel`):
                Binary quadratic model to be sampled from.

            chain_strength (float, optional, default=1.0):
                Magnitude of the quadratic bias (in SPIN-space) applied between variables to create
                chains. Note that the energy penalty of chain breaks is 2 * `chain_strength`.

            chain_break_fraction (bool, optional, default=True):
                If True, a ‘chain_break_fraction’ field is added to the unembedded response which report
                what fraction of the chains were broken before unembedding.

            **parameters:
                Parameters for the sampling method, specified by the child sampler.
        Returns:
            :class:`dimod.SampleSet`