# Copyright 2023 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
from dimod import SPIN, BINARY, Vartype
import openjij.cxxjij as cj
from openjij.model.model import make_BinaryQuadraticModel
[docs]
def make_ChimeraModel(linear, quadratic):
"""ChimeraModel factory.
Returns:
generated ChimeraModel class
"""
class ChimeraModel(make_BinaryQuadraticModel(linear, quadratic,sparse=True)):
"""Binary quadnratic model dealing with chimera graph This model deal
with chimera graph. ChimeraModel provide methods to verify whether a
given interaction graph matches a Chimera graph and to convert it to
cxxjij.graph.Chimera.
Examples::
# This interactions satisfy chimera topology.
>>> Q={(0, 4): -1, (4, 12): -1}
>>> chimera_model = ChimeraModel(Q, unit_num_L=2) # make
>>> chimera_self.validate_chimera()
"""
def __init__(
self,
linear: dict = {},
quadratic: dict = {},
offset: float = 0.0,
vartype: Vartype = SPIN,
unit_num_L: int = 2,
model = None,
):
if model:
super().__init__(
model.linear, model.quadratic, model.offset, model.vartype
)
else:
super().__init__(linear, quadratic, offset, vartype)
if not unit_num_L:
raise ValueError(
"Input unit_num_L which is the length of the side of the two-dimensional grid where chimera unit cells are arranged."
)
self.unit_num_L = unit_num_L
# check the type of indices is valid.
self.coordinate = self._validate_indices(self.indices)
# _chimera_index: 1-D index i,L -> chimera coordinate x,y,z
# _to_index: chimera coordinate x,y,z,L -> 1-D index i
if self.coordinate == "index":
self._chimera_index = lambda i, L: self.chimera_coordinate(i, L)
self._to_index = lambda x, y, z, L: self.to_index(x, y, z, L)
elif self.coordinate == "chimera coordinate":
self._chimera_index = lambda i, L: i
self._to_index = lambda x, y, z, L: self.to_index(x, y, z, L)
def _validate_indices(self, indices):
"""Check if the type of indices is valid.
Args:
indices (list(int) or list(tuple))
Return:
the type of indices ('chimera coordinate or index')
"""
if isinstance(indices[0], int):
return "index"
elif isinstance(indices[0], (tuple, list)):
if len(indices[0]) == len(indices[-1]) == 3:
return "chimera coordinate"
raise ValueError(
"In the chimera graph, index should be int or tuple or list."
)
def validate_chimera(self):
"""Check if the Chimera connectivity is valid.
Chimera coordinate: r, c, z
One dimension coordinate: i
Relation: i = 8Lr + 8c + z
Chimera unit cell (column reprezentation)
0 - 4
1 - 5
2 - 6
3 - 7
"""
# check chimera interaction
for (i, j) in self.quadratic.keys():
r_i, c_i, z_i = self._chimera_index(i, self.unit_num_L)
# list up indices which can connect i
adj_list = []
if z_i >= 4:
# part of right side of a Chimera unit cell (in the column representation).
if c_i > 0:
adj_list.append(
self._to_index(r_i, c_i - 1, z_i, self.unit_num_L)
)
if c_i < self.unit_num_L - 1:
adj_list.append(
self._to_index(r_i, c_i + 1, z_i, self.unit_num_L)
)
adj_list += [
self._to_index(r_i, c_i, z, self.unit_num_L)
for z in range(0, 4)
]
else:
# part of left side of a Chimera unit cell (in the column representation).
if r_i > 0:
adj_list.append(
self._to_index(r_i - 1, c_i, z_i, self.unit_num_L)
)
if r_i < self.unit_num_L - 1:
adj_list.append(
self._to_index(r_i + 1, c_i, z_i, self.unit_num_L)
)
adj_list += [
self._to_index(r_i, c_i, z, self.unit_num_L)
for z in range(4, 8)
]
connect_i = (
j if isinstance(j, int) else self._to_index(*j, self.unit_num_L)
)
if connect_i not in adj_list:
incomp_part = "The connectable nodes of {} are {}, not {}.".format(
i, adj_list, j
)
raise ValueError(
"Problem graph incompatible with chimera graph.\n" + incomp_part
)
return False
return True
def to_index(self, r, c, i, unit_num_L):
"""
Chimera coordinate: r, c, i
One dimension coordinate: i
Relation: i = 8*L*r + 8*c + i
Args:
r (int): Row index of 2-D Chimera grid.
c (int): Column index of 2-D Chimera grid.
i (int): index in Chimera unit cell.
unit_num_L (int): Row and Column length of 2-D Chimera grid.
"""
return 8 * unit_num_L * r + 8 * c + i
def chimera_coordinate(self, i, unit_num_L):
"""Convert 1-d index to chimera corrdinate
Args:
i (int): 1-D index 0~L*L*8-1
unit_num_L (int): number of chimera grid size
Returns:
(int, int, int): chimera corrdinate
"""
z_i = i % 8
c_i = (i % (8 * unit_num_L) - z_i) / 8
r_i = (i - 8 * c_i - z_i) / (8 * unit_num_L)
return int(r_i), int(c_i), int(z_i)
def get_cxxjij_ising_graph(self):
"""Get cxxjij.graph.Chimera type instance
Args:
i (int): 1-D index 0~L*L*8-1
unit_num_L (int): number of chimera grid size
Returns:
object (cxxjij.graph.Chimera)
"""
chimera_L = self.unit_num_L
if not self.validate_chimera():
raise ValueError("Problem graph incompatible with chimera graph.")
_h, _J, _offset = self.to_ising()
chimera = cj.graph.Chimera(chimera_L, chimera_L)
for i, hi in _h.items():
r_i, c_i, zi = self._chimera_index(i, L = chimera_L)
if not self._index_validate(i, chimera_L):
raise ValueError(
"Problem graph incompatible with chimera graph. Node {}.".format(
i
)
)
chimera[r_i, c_i, zi] = hi
for (i, j), Jij in _J.items():
r_i, c_i, zi = self._chimera_index(i, L = chimera_L)
r_j, c_j, zj = self._chimera_index(j, L = chimera_L)
# validate connection
error_msg = f"In the {chimera_L}*{chimera_L} Chimera grid, "
error_msg += f"there is no connection between node {i} and node {j}."
linear_vldt = self._index_validate(
i, chimera_L
) and self._index_validate(j, chimera_L)
if not (
linear_vldt
and self._validate((r_i, c_i, zi), (r_j, c_j, zj), chimera_L)
):
raise ValueError(
"Problem graph incompatible with chimera graph.\n" + error_msg
)
if r_i == r_j and c_i == c_j:
# connection in Chimera unit cell
if zj in [0, 4]:
chimera[r_i, c_i, zi, cj.graph.ChimeraDir.IN_0or4] = Jij
elif zj in [1, 5]:
chimera[r_i, c_i, zi, cj.graph.ChimeraDir.IN_1or5] = Jij
elif zj in [2, 6]:
chimera[r_i, c_i, zi, cj.graph.ChimeraDir.IN_2or6] = Jij
else:
chimera[r_i, c_i, zi, cj.graph.ChimeraDir.IN_3or7] = Jij
# connection between Chimera unit cells
elif r_i - r_j == -1:
chimera[r_i, c_i, zi, cj.graph.ChimeraDir.PLUS_R] = Jij
elif r_i - r_j == 1:
chimera[r_i, c_i, zi, cj.graph.ChimeraDir.MINUS_R] = Jij
elif c_i - c_j == -1:
chimera[r_i, c_i, zi, cj.graph.ChimeraDir.PLUS_C] = Jij
elif c_i - c_j == 1:
chimera[r_i, c_i, zi, cj.graph.ChimeraDir.MINUS_C] = Jij
return chimera
def energy(self, sample, convert_sample=False):
"""Calc energy of the BinaryQuadraticModel.
Args:
sample: samples
convert_sample: if true, the type of sample is automatically converted to self.vartype.
"""
return super().energy(sample, sparse=True, convert_sample=convert_sample)
def energies(self, samples_like, convert_sample=False):
return super().energies(
samples_like, sparse = True, convert_sample = convert_sample
)
def _validate(self, rcz1, rcz2, L):
"""Check if the connectivity is valid.
Args:
rcz1 (int), rcz2(int), L(int)
Returns:
result (bool)
"""
r1, c1, z1 = rcz1
r2, c2, z2 = rcz2
left_side = [0, 1, 2, 3]
right_side = [4, 5, 6, 7]
if r1 == r2 and c1 == c2:
if (z1 in left_side) and (z2 in right_side):
return True
elif (z2 in left_side) and (z1 in right_side):
return True
elif (c1 == c2 and abs(r1 - r2) == 1) or (r1 == r2 and abs(c1 - c2) == 1):
return True
return False
def _index_validate(self, i, L):
"""Check if the index is valid.
Args:
i(int), L(int)
Returns:
result (bool)
"""
if isinstance(i, tuple):
two_d_bool = (i[0] < self.unit_num_L) and (i[1] < self.unit_num_L)
return two_d_bool and (i[2] < 8)
max_index = 8 * L * L
return 0 <= i < max_index
return ChimeraModel
[docs]
def make_ChimeraModel_from_JSON(obj):
"""Make ChimeraModel from JSON.
Returns:
corresponding ChimeraModel type
"""
label = obj["variable_labels"][0]
if isinstance(label, list):
# convert to tuple
label = tuple(label)
mock_linear = {label: 1.0}
return make_ChimeraModel(mock_linear, {})
[docs]
def ChimeraModel(
linear: dict = {},
quadratic: dict = {},
offset: float = 0.0,
vartype = SPIN,
unit_num_L: int = 2,
model = None,
):
"""Generate ChimeraModel object
This model deal with chimera graph.
ChimeraModel provide methods to verify whether a given interaction graph
matches a Chimera graph and to convert it to cxxjij.graph.Chimera.
Args:
linear (dict): linear biases
quadratic (dict): quadratic biases
offset (float): offset
vartype: vartype ('SPIN' or 'BINARY')
unit_num_L (int): unit_num_L
model (BinaryQuadraticModel): if model is not None, the object is initialized by model.
Returns:
generated ChimeraModel
Examples:
Example shows how to initialize ChimeraModel.::
# This interactions satisfy chimera topology.
>>> Q={(0, 4): -1, (4, 12): -1}
>>> chimera_model = ChimeraModel(Q, unit_num_L=2) # make
>>> chimera_self.validate_chimera()
"""
Model = make_ChimeraModel(linear, quadratic)
return Model(linear, quadratic, offset, vartype, unit_num_L, model)
# classmethods
ChimeraModel.from_qubo = lambda Q, offset=0.0, **kwargs: make_ChimeraModel(
{}, Q
).from_qubo(Q, offset, **kwargs)
ChimeraModel.from_ising = (
lambda linear, quadratic, offset=0.0, **kwargs: make_ChimeraModel(
linear, quadratic
).from_ising(linear, quadratic, offset, **kwargs)
)
ChimeraModel.from_serializable = lambda obj: make_ChimeraModel_from_JSON(
obj
).from_serializable(obj)
