class BaseChannel(ABC):
def __init__(self,
params,
graph_type="chimera",
n_nodes=None,
n_edges=None):
self.params = params
self.graph_type = graph_type
device_name = {
'chimera': 'DW_2000Q_6',
'pegasus': 'Advantage_system1.1',
'simulator': None
}
if graph_type == 'simulator':
self.sampler = DWaveSampler(solver={'qpu': False})
else:
self.sampler = DWaveSampler(solver={
'qpu': True,
'name': device_name[graph_type]
})
self.list_edges = np.array(self.sampler.edgelist)
self.list_nodes = np.array(self.sampler.nodelist)
nodes_file = "data/pegasus/list_nodes.npy"
edges_file = "data/pegasus/list_edges.npy"
if graph_type == 'pegasus':
if n_nodes is not None:
if os.path.exists(nodes_file):
print("Loading list nodes...")
self.list_nodes = np.load(nodes_file)
else:
print("Taking subgraph...")
self.list_nodes = take_subgraph(self.sampler, n_nodes)
np.save(nodes_file, self.list_nodes)
self.graph = self.sampler.to_networkx_graph().subgraph(
self.list_nodes)
self.list_edges = np.array(self.graph.edges)
if n_edges is not None:
if os.path.exists(edges_file):
print("Loading list edges...")
self.list_edges = np.load(edges_file)
else:
print("Removing edges...")
edges_idx = np.sort(
np.random.choice(len(self.list_edges),
n_edges,
replace=False))
self.list_edges = self.list_edges[edges_idx]
np.save(edges_file, self.list_edges)
print("Number of qubits", len(self.list_nodes))
print("Number of edges", len(self.list_edges))
super().__init__()
@abstractmethod
def send(self, J_in, h_in):
pass
@abstractmethod
def get_nishimori_temperature(self):
pass
@abstractmethod
def conditional_density(self, y_out, y_in):
pass
def encode(self, x_in):
x_dict = {node: x_in[i] for i, node in enumerate(self.list_nodes)}
J = defaultdict(int)
for (u, v) in self.list_edges:
J[(u, v)] = -x_dict[u] * x_dict[v]
h = {node: -x_dict[node] for node in x_dict.keys()}
return J, h
def decode(self, J_out, h_out, num_reads=1, num_spin_reversals=1):
result = self.sampler.sample_ising(
h_out,
J_out,
num_reads=num_reads,
num_spin_reversal_transforms=num_spin_reversals)
x_dec = np.array(list(list(result.data())[0].sample.values()))
return x_dec
def get_ber(self, x_in, x_dec):
N = len(x_in)
return np.sum(np.abs(x_in - x_dec)) / (2 * N)
def plot_working_graph(sampler: DWaveSampler, out_path: None or os.PathLike=None,
figsize:tuple=(8, 8), ng_color:str="red", ok_color:str="blue",
draw_rectangle:bool=False) -> None:
"""
QPUのworking graphをプロットする。
working graph については https://docs.dwavesys.com/docs/latest/c_gs_4.html?highlight=working%20graph を参考。
Parameters
----------
sampler : DWaveSampler
プロット対象のQPUを保持するDWaveSamplerオブジェクト。
out_path : None or os.PathLike, optional
出力パス, by default None
figsize : tuple, optional
figsize, by default (8, 8)
ng_color : str, optional
無効なqbit, couplerの描画色, by default "red"
ok_color : str, optional
有効なqbit, couplerの描画色, by default "blue"
draw_rectangle : bool, optional
無効なqbit, couplerが存在しない領域を示すか, by default False
DWaveSampler.properties["chip_id"] が "DW_2000Q_6" である時のみ使える。
それ以外のSamplerに対しTrueを設定するとValueErrorが発生する。
矩形のサイズは手動で調整した。ハードコーディング。
"""
# topologyに応じ関数を設定
topology_type = sampler.properties["topology"]["type"]
if topology_type == "chimera":
graph_func = dnx.chimera_graph
draw_func = dnx.draw_chimera
elif topology_type == "pegasus":
graph_func = dnx.pegasus_graph
draw_func = dnx.draw_pegasus
else:
raise ValueError(f"support chimera or pegasus, unsupported {topology_type}.")
# working_graph の 無効なqbit, coupler を求め、colorリストを作成
G = sampler.to_networkx_graph()
T = graph_func(*sampler.properties["topology"]["shape"])
error_node = set(T.nodes() - G.nodes())
node_color = [ng_color if v in error_node else ok_color for v in T.nodes()]
error_edge = set(T.edges() - G.edges())
edge_color = [ng_color if e in error_edge else ok_color for e in T.edges()]
# プロット
plt.figure(figsize=figsize)
ax = plt.axes()
draw_func(T, node_color=node_color, edge_color=edge_color, node_size=1, ax=ax)
if draw_rectangle:
chip_id = sampler.properties["chip_id"]
if chip_id != "DW_2000Q_6":
raise ValueError(f"support DW_2000Q_6, unsupported {chip_id}.")
# ハードコーディング。手動で調整した。
rectangle = patches.Rectangle(xy=(0.37, -0.82), width=0.64, height=0.83,
ec='green', fill=False, ls="--", lw="2")
ax.add_patch(rectangle)
if out_path is None:
plt.show()
else:
os.makedirs(Path(out_path).parent, exist_ok=True)
plt.savefig(out_path)
plt.clf()