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Jij CPU SQA Sampler

JijSQASampler

Bases: JijZeptBaseSampler

sample_model(problem, feed_dict, multipliers={}, fixed_variables={}, search=False, num_search=15, algorithm=None, parameters=None, timeout=None, sync=True, queue_name=None, **kwargs)

Sample using JijModeling by means of the simulated annealing.

Parameters:

Name Type Description Default
model Expression

Mathematical expression of JijModeling.

required
feed_dict Dict[str, Union[Number, list, np.ndarray]]

The actual values to be assigned to the placeholders.

required
multipliers Dict[str, Number]

The actual multipliers for penalty terms, derived from constraint conditions.

{}
fixed_variables Dict[str, Dict[Tuple[int, ...], Union[int, float]]]

dictionary of variables to fix.

{}
search bool

If True, the parameter search will be carried out, which tries to find better values of multipliers for penalty terms.

False
num_search int

The number of parameter search iteration. Defaults to set 15. This option works if search is True.

15
algorithm Optional[str]

Algorithm for parameter search. Defaults to None.

None
timeout Optional[int]

The number of timeout [sec] for post request. If None, 3600 (one hour) will be set.

None
sync bool

Synchronous mode.

True
queue_name str

queue_name.

None

Returns:

Name Type Description
JijModelingResponse JijModelingResponse

Stores minimum energy samples and other information.

Examples:

import jijzept as jz
import jijmodeling as jm
n = jm.Placeholder('n')
x = jm.Binary('x', shape=n)
d = jm.Placeholder('d', shape=n)
i = jm.Element("i", n)
problem = jm.Problem('problem')
problem += jm.Sum(i, d[i] * x[i])
sampler = jz.JijSASampler(config='config.toml')
response = sampler.sample_model(problem, feed_dict={'n': 5, 'd': [1,2,3,4,5]})

sample_qubo(qubo, constant=0, parameters=None, timeout=None, sync=True, queue_name=None, **kwargs)

Sample using BinaryQuadraticModel by means of the simulated annealing.

Parameters:

Name Type Description Default
bqm Union[cimod.BinaryQuadraticModel, openjij.BinaryQuadraticModel]

Binary quadratic model.

required
parameters JijSQAParameters | None

(JijSAParameters | None, optional): defaults None.

None
timeout Optional[int]

The number of timeout [sec] for post request. If None, 3600 (one hour) will be set.

None
sync bool

Synchronous mode.

True
queue_name str

queue_name.

None

Returns:

Type Description
JijModelingResponse

dimod.SampleSet: Stores minimum energy samples and other information.

Examples:

For cimod.BinaryQuadraticModel case:

import jijzept as jz
import cimod
bqm = cimod.BinaryQuadraticModel({0: -1, 1: -1}, {(0, 1): -1, (1, 2): -1}, "SPIN")
sampler = jz.JijSASampler(config='config.toml')
response = sampler.sample(bqm)
One can also use sample_ising and sample_qubo methods.

For Ising case:

import jijzept as jz
h = {0: -1, 1: -1, 2: 1, 3: 1}
J = {(0, 1): -1, (3, 4): -1}
sampler = jz.JijSASampler(config='config.toml')
response = sampler.sample_ising(h, J)

For QUBO case:

import jijzept as jz
Q = {(0, 0): -1, (1, 1): -1, (2, 2): 1, (0, 1): -1, (1, 2): 1}
sampler = jz.JijSASampler(config='config.toml')
response = sampler.sample_qubo(Q)


Last update: 2022年12月21日