dwave-hybrid 0.0.3

Hybrid Asynchronous Decomposition Solver Framework

A general, minimal Python framework for building hybrid asynchronous decomposition samplers for quadratic unconstrained binary optimization (QUBO) problems. It facilitates experimentation with structures and parameters for tailoring a decomposition solver to a problem.

The framework enables rapid development and insight into expected performance of productized versions of its experimental prototypes. It does not provide real-time performance.

Installation or Building

Package not yet available on PyPI. Install in developer (edit) mode:

pip install -e git+https://github.com/dwavesystems/dwave-hybrid.git#egg=dwave-hybrid

or from source:

git clone https://github.com/dwavesystems/dwave-hybrid.git
cd dwave-hybrid
pip install -r requirements.txt
python setup.py install

Example

import dimod
from hybrid.samplers import (
    QPUSubproblemAutoEmbeddingSampler, InterruptableTabuSampler)
from hybrid.decomposers import EnergyImpactDecomposer
from hybrid.composers import SplatComposer
from hybrid.core import State
from hybrid.flow import RacingBranches, ArgMinFold, SimpleIterator
from hybrid.utils import min_sample

# Construct a problem
bqm = dimod.BinaryQuadraticModel({}, {'ab': 1, 'bc': -1, 'ca': 1}, 0, dimod.SPIN)

# Define the solver
iteration = RacingBranches(
    InterruptableTabuSampler(),
    EnergyImpactDecomposer(max_size=2)
    | QPUSubproblemAutoEmbeddingSampler()
    | SplatComposer()
) | ArgMinFold()
main = SimpleIterator(iteration, max_iter=10, convergence=3)

# Solve the problem
init_state = State.from_sample(min_sample(bqm), bqm)
solution = main.run(init_state).result()

# Print results
print("Solution: sample={s.samples.first}".format(s=solution))