# Copyright 2021 Jij 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 annotations
import openjij
import openjij as oj
import openjij.cxxjij as cxxjij
from openjij.sampler.chimera_gpu.base_gpu_chimera import BaseGPUChimeraSampler
from openjij.sampler.sqa_sampler import SQASampler
[docs]class GPUChimeraSQASampler(SQASampler, BaseGPUChimeraSampler):
"""Sampler with Simulated Quantum Annealing (SQA) on GPU.
Inherits from :class:`openjij.sampler.sqa_sampler.SQASampler`.
Args:
beta (float): Inverse temperature.
gamma (float): Amplitude of quantum fluctuation.
trotter (int): Trotter number.
num_sweeps (int): number of sweeps
schedule_info (dict): Information about a annealing schedule.
num_reads (int): Number of iterations.
unit_num_L (int): Length of one side of two-dimensional lattice in which chimera unit cells are arranged.
Raises:
ValueError: If variables violate as below.
- trotter number is odd.
- no input "unit_num_L" to an argument or this constructor.
- given problem graph is incompatible with chimera graph.
AttributeError: If GPU doesn't work.
"""
def __init__(
self,
beta=10.0,
gamma=1.0,
trotter=4,
num_sweeps=100,
schedule=None,
num_reads=1,
unit_num_L=None,
):
# GPU Sampler allows only even trotter number
if trotter % 2 != 0:
raise ValueError("GPU Sampler allows only even trotter number")
self.trotter = trotter
self.unit_num_L = unit_num_L
super().__init__(
beta=beta,
gamma=gamma,
trotter=trotter,
num_reads=num_reads,
num_sweeps=num_sweeps,
schedule=schedule,
)
self._make_system = {
"singlespinflip": cxxjij.system.make_chimera_transverse_gpu
}
self._algorithm = {"singlespinflip": cxxjij.algorithm.Algorithm_GPU_run}
def _get_result(self, system, model):
result = cxxjij.result.get_solution(system)
sys_info = {}
return result, sys_info
[docs] def sample_ising(
self,
h,
J,
beta=None,
gamma=None,
num_sweeps=None,
schedule=None,
num_reads=None,
unit_num_L=None,
initial_state=None,
updater=None,
reinitialize_state=True,
seed=None,
):
"""Sampling from the Ising model.
Args:
h (dict): Linear term of the target Ising model.
J (dict): Quadratic term of the target Ising model.
beta (float, optional): inverse tempareture.
gamma (float, optional): strangth of transverse field. Defaults to None.
num_sweeps (int, optional): number of sweeps. Defaults to None.
schedule (list[list[float, int]], optional): List of annealing parameter. Defaults to None.
num_reads (int, optional): number of sampling. Defaults to 1.
initial_state (list[int], optional): Initial state. Defaults to None.
updater (str, optional): update method. Defaults to 'single spin flip'.
reinitialize_state (bool, optional): Re-initilization at each sampling. Defaults to True.
seed (int, optional): Sampling seed. Defaults to None.
Returns:
:class:`openjij.sampler.response.Response`: results
Examples::
>>> sampler = openjij.sampler.chimera_gpu.gpu_sqa_sampler.GPUChimeraSQASampler(unit_num_L=2)
>>> h = {0: -1, 1: -1, 2: 1, 3: 1},
>>> J = {(0, 4): -1, (2, 5): -1}
>>> res = sampler.sample_ising(h, J)
"""
# Set default updater
if updater is None:
updater = "single spin flip"
if num_reads is None:
num_reads = 1
self.unit_num_L = unit_num_L if unit_num_L else self.unit_num_L
model = oj.model.chimera_model.ChimeraModel(
linear=h, quadratic=J, vartype="SPIN", unit_num_L=self.unit_num_L, gpu=True
)
# define Chimera structure
structure = {}
structure["size"] = 8 * self.unit_num_L * self.unit_num_L
structure["dict"] = {}
if isinstance(model.indices[0], int):
# identity dict
for ind in model.indices:
structure["dict"][ind] = ind
elif isinstance(model.indices[0], tuple):
# map chimera coordinate to index
for ind in model.indices:
structure["dict"][ind] = model.to_index(*ind, self.unit_num_L)
return self._sampling(
model,
beta=beta,
gamma=gamma,
num_sweeps=num_sweeps,
schedule=schedule,
num_reads=num_reads,
initial_state=initial_state,
updater=updater,
reinitialize_state=reinitialize_state,
seed=seed,
structure=structure,
)
