def run(self, quantum_circuit):
dag_circuit = circuit_to_dag(quantum_circuit)
init_time = time.time()
self.parameters["TIME_START"] = init_time
initial_mapping = []
if self.parameters["initial_map"] == K7MInitialMapping.RANDOM:
# Only the first positions which correspond to the circuit qubits
initial_mapping = numpy.random.permutation(
self.parameters["nisq_qubits"])
initial_mapping = initial_mapping[:dag_circuit.num_qubits()]
elif self.parameters["initial_map"] == K7MInitialMapping.LINEAR:
initial_mapping = list(range(dag_circuit.num_qubits()))
elif self.parameters["initial_map"] == K7MInitialMapping.HEURISTIC:
initial_mapping = cuthill_order(dag_circuit, self.coupling_obj,
self.parameters)
init_time = time.time() - init_time
if initial_mapping is None:
return None, init_time, None
# print(initial_mapping)
#
# return quantum_circuit
print(" .......")
original_pm = PassManager()
optimal_layout = Layout()
for c_idx, p_idx in enumerate(initial_mapping):
optimal_layout.add(quantum_circuit.qregs[0][c_idx], p_idx)
original_pm.append([
SetLayout(optimal_layout),
ApplyLayout(),
StochasticSwap(self.coupling_obj.coupling, seed=0),
Decompose(gate=qiskit.extensions.SwapGate)
])
return original_pm.run(quantum_circuit), init_time, initial_mapping
def run(self, quantum_circuit):
dag_circuit = circuit_to_dag(quantum_circuit)
init_time = time.time()
initial_mapping = []
if self.parameters["initial_map"] == K7MInitialMapping.RANDOM:
# Only the first positions which correspond to the circuit qubits
initial_mapping = numpy.random.permutation(
self.parameters["nisq_qubits"])
initial_mapping = initial_mapping[:dag_circuit.num_qubits()]
elif self.parameters["initial_map"] == K7MInitialMapping.LINEAR:
initial_mapping = list(range(dag_circuit.num_qubits()))
elif self.parameters["initial_map"] == K7MInitialMapping.HEURISTIC:
initial_mapping = cuthill_order(dag_circuit, self.coupling_obj,
self.parameters)
init_time = time.time() - init_time
# print(initial_mapping)
#
# return quantum_circuit
print(" .......")
original_pm = PassManager()
optimal_layout = Layout()
for c_idx, p_idx in enumerate(initial_mapping):
optimal_layout.add(quantum_circuit.qregs[0][c_idx], p_idx)
original_pm.append([
SetLayout(optimal_layout),
ApplyLayout(),
StochasticSwap(self.coupling_obj.coupling),
Decompose(gate=qiskit.extensions.SwapGate)
])
return original_pm.run(quantum_circuit), init_time, initial_mapping
"""
NAIVE ROUTING
"""
# if self.positions_obj == None:
# self.positions_obj = K7MPositions(dag_circuit,
# self.parameters,
# initial_mapping)
# '''
# Start with an initial configuration
# '''
# compiled_dag, back_stack = self.find_solution(dag_circuit, self.parameters["dry_run"])
#
# """
# Returning here stops backtracking -> A full backtrack is not available,
# but the following code, after having iterated through the possible
# configurations (code before here):
# * counts the most common configuration
# * computes for each configuration the cost
# * chooses the configuration of minimum cost
# """
#
# # Clean the positions
# self.positions_obj = None
#
# return dag_to_circuit(compiled_dag)
"""
