def sample(self, bqm, initial_sample=None):
"""Sample from a binary quadratic model using composed runnable sampler.
Args:
bqm (:obj:`~dimod.BinaryQuadraticModel`):
Binary quadratic model to be sampled from.
initial_sample (dict, default=None):
`bqm`-compatible sample used for initial state construction.
Defaults to `hybrid.utils.min_sample(bqm)`.
Returns:
:obj:`~dimod.Response`: A `dimod` :obj:`.~dimod.Response` object.
"""
if not isinstance(bqm, dimod.BinaryQuadraticModel):
raise TypeError("'bqm' should be BinaryQuadraticModel")
if initial_sample is None:
initial_sample = min_sample(bqm)
else:
initial_sample = sample_as_dict(initial_sample)
if len(initial_sample) != len(bqm):
raise ValueError(
"size of 'initial_sample' incompatible with 'bqm'")
initial_state = State.from_sample(initial_sample, bqm)
final_state = self._runnable_solver.run(initial_state)
return dimod.Response.from_future(
final_state, result_hook=lambda f: f.result().samples)
def sample(self, bqm, initial_sample=None, return_state=False, **params):
"""Sample from a binary quadratic model using composed runnable sampler.
Args:
bqm (:obj:`~dimod.BinaryQuadraticModel`):
Binary quadratic model to be sampled from.
initial_sample (dict, default=None):
`bqm`-compatible sample used for initial state construction.
Defaults to `hybrid.utils.min_sample(bqm)`.
return_state (bool, optional, default=False):
If True, the final state is added to :attr:`dimod.SampleSet.info`
of the returned sample set. Note that if a `state` key
already exists in the sample set then it is overwritten.
**params (dict):
Sampling parameters passed down to the underlying workflow as
run-time parameters.
Note:
Sampling via hybrid workflow is run asynchronously, and a sample set
is returned as soon as workflow starts running. A blocking result
resolve occurres on the first attribute access to the returned
sample set.
Returns:
:class:`~dimod.SampleSet`:
Possibly yet unresolved sample set.
"""
if not isinstance(bqm, dimod.BinaryQuadraticModel):
raise TypeError("'bqm' should be BinaryQuadraticModel")
if initial_sample is None:
initial_sample = min_sample(bqm)
else:
initial_sample = sample_as_dict(initial_sample)
if len(initial_sample) != len(bqm):
raise ValueError(
"size of 'initial_sample' incompatible with 'bqm'")
initial_state = State.from_sample(initial_sample, bqm)
final_state = self._workflow.run(initial_state, **params)
def result_hook(state):
resolved = state.result()
ss = resolved.samples
if return_state:
# note: this creates a cyclic reference to `samples` from the
# sample set via `info['state']`, but that shouldn't be a
# problem for GC
ss.info.update(state=resolved)
return ss
return dimod.SampleSet.from_future(final_state,
result_hook=result_hook)
def test_from_samples(self):
s1 = [0, 1]
s2 = {0: 1, 1: 0}
bqm = dimod.BinaryQuadraticModel({0: 1, 1: 2}, {}, 0.0, 'BINARY')
self.assertEqual(State.from_sample(s1, bqm).samples.first.energy, 2.0)
self.assertEqual(State.from_sample(s2, bqm).samples.first.energy, 1.0)
self.assertEqual(State.from_samples([s1, s1], bqm).samples.first.energy, 2.0)
self.assertEqual(State.from_samples([s2, s2], bqm).samples.first.energy, 1.0)
self.assertEqual(State.from_samples([sample_as_dict(s1), s2], bqm).samples.first.energy, 1.0)
