Support all structured samplers in SubproblemCliqueEmbedder

hybrid/samplers.py

@@ -26,12 +26,11 @@
 import dimod
 from dwave.system.samplers import DWaveSampler
 from dwave.system.composites import AutoEmbeddingComposite, FixedEmbeddingComposite
-from dwave.embedding.chimera import find_clique_embedding as find_chimera_clique_embedding
-from dwave.embedding.pegasus import find_clique_embedding as find_pegasus_clique_embedding
 
 from tabu import TabuSampler
 from neal import SimulatedAnnealingSampler
 from greedy import SteepestDescentSolver
+from minorminer.busclique import busgraph_cache
 
 from hybrid.core import Runnable, SampleSet
 from hybrid.flow import Loop
@@ -114,8 +113,7 @@ class SubproblemCliqueEmbedder(traits.SubproblemIntaking,
     Args:
         sampler (:class:`dimod.Structured`):
             Structured :class:`dimod.Sampler` such as a
-            :class:`~dwave.system.samplers.DWaveSampler`. The sampler has to
-            have a Chimera or Pegasus topology.
+            :class:`~dwave.system.samplers.DWaveSampler`.
 
     Example:
         To replace :class:`.QPUSubproblemAutoEmbeddingSampler` with a sampler
@@ -141,29 +139,17 @@ def __repr__(self):
 
     @staticmethod
     def find_clique_embedding(variables, sampler):
-        """Given a Chimera- or Pegasus-based ``sampler``, and a list of
+        """Given a :class:`dimod.Structured` ``sampler``, and a list of
         variable labels, return a clique embedding.
 
         Returns:
             dict:
                 Clique embedding map with source variables from ``variables``
-                and target edges taken from ``sampler``.
+                and target graph taken from ``sampler``.
 
         """
-        topology_type = sampler.properties['topology']['type']
-        topology_shape = sampler.properties['topology']['shape']
-
-        clique_embedders = dict(chimera=find_chimera_clique_embedding,
-                                pegasus=find_pegasus_clique_embedding)
-        try:
-            find_clique_embedding = clique_embedders[topology_type]
-        except KeyError:
-            raise ValueError('unknown sampler topology')
-
-        embedding = find_clique_embedding(
-            variables, m=topology_shape[0], target_edges=sampler.edgelist)
-
-        return embedding
+        g = sampler.to_networkx_graph()
+        return busgraph_cache(g).find_clique_embedding(variables)
 
     def next(self, state, **runopts):
         embedding = self.find_clique_embedding(

tests/test_samplers.py

@@ -17,17 +17,20 @@
 from operator import attrgetter
 
 import numpy as np
-from parameterized import parameterized_class
+from parameterized import parameterized, parameterized_class
 
 import dimod
 from neal import SimulatedAnnealingSampler
+from dwave.system import DWaveSampler
 from dwave.system.testing import MockDWaveSampler
 
 from hybrid.samplers import *
 from hybrid.core import State
 from hybrid.testing import mock
 from hybrid.utils import random_sample
 
+MockDWaveSampler.to_networkx_graph = DWaveSampler.to_networkx_graph
+
 
 class MockDWaveReverseAnnealingSampler(MockDWaveSampler):
     """Extend the `dwave.system.testing.MockDWaveSampler` with mock support for
@@ -109,12 +112,12 @@ def test_external_embedding_sampler(self):
         # verify mock sampler received custom kwargs
         self.assertEqual(res.subsamples.first.energy, -1)
 
-    def test_clique_embedder(self):
+    @parameterized.expand([['chimera', 2], ['pegasus', 1]])
+    def test_clique_embedder(self, topology_type, expected_chain_length):
         bqm = dimod.BinaryQuadraticModel.from_ising({}, {'ab': 1, 'bc': 1, 'ca': 1})
         init = State.from_subproblem(bqm)
 
-        sampler = MockDWaveSampler()
-
+        sampler = MockDWaveSampler(topology_type=topology_type)
         workflow = SubproblemCliqueEmbedder(sampler=sampler)
 
         # run embedding
@@ -123,8 +126,10 @@ def test_clique_embedder(self):
         # verify mock sampler received custom kwargs
         self.assertIn('embedding', res)
         self.assertEqual(len(res.embedding.keys()), 3)
-        # embedding a triangle onto a chimera produces 3 x 2-qubit chains
-        self.assertTrue(all(len(e) == 2 for e in res.embedding.values()))
+
+        # embedding a triangle onto a chimera produces 3 x 2-qubit chains;
+        # if embedding onto pegasus the chains have length 1.
+        self.assertTrue(all(len(e) == expected_chain_length for e in res.embedding.values()))
 
     def test_reverse_annealing_sampler(self):
         sampler = MockDWaveReverseAnnealingSampler()