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qbsolv-like-alt.py
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qbsolv-like-alt.py
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#!/usr/bin/env python
# Copyright 2018 D-Wave Systems Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import print_function
import sys
import dimod
import hybrid
# load a problem
problem = sys.argv[1]
with open(problem) as fp:
bqm = dimod.BinaryQuadraticModel.from_coo(fp)
# define a qbsolv-like workflow
def merge_substates(_, substates):
a, b = substates
return a.updated(subsamples=hybrid.hstack_samplesets(a.subsamples, b.subsamples))
subproblems = hybrid.Unwind(
hybrid.EnergyImpactDecomposer(size=50, rolling_history=0.15)
)
qpu = hybrid.Map(
hybrid.QPUSubproblemAutoEmbeddingSampler()
) | hybrid.Reduce(
hybrid.Lambda(merge_substates)
) | hybrid.SplatComposer()
random = hybrid.Map(
hybrid.RandomSubproblemSampler()
) | hybrid.Reduce(
hybrid.Lambda(merge_substates)
) | hybrid.SplatComposer()
subsampler = hybrid.Parallel(qpu, random, endomorphic=False) | hybrid.ArgMin()
iteration = hybrid.Race(
hybrid.InterruptableTabuSampler(),
subproblems | subsampler
) | hybrid.ArgMin()
main = hybrid.Loop(iteration, max_iter=10, convergence=3)
# run the workflow
init_state = hybrid.State.from_sample(hybrid.min_sample(bqm), bqm)
solution = main.run(init_state).result()
# show execution profile
hybrid.profiling.print_counters(main)
# show results
print("Solution: sample={.samples.first}".format(solution))