def _swap_ops_from_edge(edge, layout):
"""Generate list of ops to implement a SWAP gate along a coupling edge."""
device_qreg = QuantumRegister(len(layout.get_physical_bits()), 'q')
qreg_edge = [device_qreg[i] for i in edge]
# TODO shouldn't be making other nodes not by the DAG!!
return [DAGNode(op=SwapGate(), qargs=qreg_edge, cargs=[], type='op')]
def _swap_ops_from_edge(edge, layout):
"""Generate list of ops to implement a SWAP gate along a coupling edge."""
device_qreg = QuantumRegister(len(layout.get_physical_bits()), 'q')
qreg_edge = [(device_qreg, i) for i in edge]
# TODO shouldn't be making other nodes not by the DAG!!
return [
DAGNode({'op': SwapGate(*qreg_edge), 'qargs': qreg_edge, 'type': 'op'})
]
def test_is_identity(self):
""" The is_identity function determines whether a pair of gates
forms the identity, when ignoring control qubits.
"""
seq = [
DAGNode({
'type': 'op',
'op': XGate().control()
}),
DAGNode({
'type': 'op',
'op': XGate().control(2)
})
]
self.assertTrue(HoareOptimizer()._is_identity(seq))
seq = [
DAGNode({
'type': 'op',
'op': RZGate(-pi / 2).control()
}),
DAGNode({
'type': 'op',
'op': RZGate(pi / 2).control(2)
})
]
self.assertTrue(HoareOptimizer()._is_identity(seq))
seq = [
DAGNode({
'type': 'op',
'op': CSwapGate()
}),
DAGNode({
'type': 'op',
'op': SwapGate()
})
]
self.assertTrue(HoareOptimizer()._is_identity(seq))
seq = [
DAGNode({
'type': 'op',
'op': UnitaryGate([[1, 0], [0, 1j]]).control()
}),
DAGNode({
'type': 'op',
'op': UnitaryGate([[1, 0], [0, -1j]])
})
]
def test_is_identity(self):
"""The is_identity function determines whether a pair of gates
forms the identity, when ignoring control qubits.
"""
seq = [
DAGNode(type="op", op=XGate().control()),
DAGNode(type="op", op=XGate().control(2))
]
self.assertTrue(HoareOptimizer()._is_identity(seq))
seq = [
DAGNode(type="op", op=RZGate(-pi / 2).control()),
DAGNode(type="op", op=RZGate(pi / 2).control(2)),
]
self.assertTrue(HoareOptimizer()._is_identity(seq))
seq = [
DAGNode(type="op", op=CSwapGate()),
DAGNode(type="op", op=SwapGate())
]
self.assertTrue(HoareOptimizer()._is_identity(seq))
def run(self, dag):
"""Run the SabreSwap pass on `dag`.
Args:
dag (DAGCircuit): the directed acyclic graph to be mapped.
Returns:
DAGCircuit: A dag mapped to be compatible with the coupling_map.
Raises:
TranspilerError: if the coupling map or the layout are not
compatible with the DAG
"""
if len(dag.qregs) != 1 or dag.qregs.get('q', None) is None:
raise TranspilerError('Sabre swap runs on physical circuits only.')
if len(dag.qubits) > self.coupling_map.size():
raise TranspilerError('More virtual qubits exist than physical.')
rng = np.random.default_rng(self.seed)
# Preserve input DAG's name, regs, wire_map, etc. but replace the graph.
mapped_dag = dag._copy_circuit_metadata()
# Assume bidirectional couplings, fixing gate direction is easy later.
self.coupling_map.make_symmetric()
canonical_register = dag.qregs['q']
current_layout = Layout.generate_trivial_layout(canonical_register)
# A decay factor for each qubit used to heuristically penalize recently
# used qubits (to encourage parallelism).
self.qubits_decay = {qubit: 1 for qubit in dag.qubits}
# Start algorithm from the front layer and iterate until all gates done.
num_search_steps = 0
front_layer = dag.front_layer()
self.applied_gates = set()
while front_layer:
execute_gate_list = []
# Remove as many immediately applicable gates as possible
for node in front_layer:
if len(node.qargs) == 2:
v0, v1 = node.qargs
physical_qubits = (current_layout[v0], current_layout[v1])
if physical_qubits in self.coupling_map.get_edges():
execute_gate_list.append(node)
else: # Single-qubit gates as well as barriers are free
execute_gate_list.append(node)
if execute_gate_list:
for node in execute_gate_list:
new_node = _transform_gate_for_layout(node, current_layout)
mapped_dag.apply_operation_back(new_node.op,
new_node.qargs,
new_node.cargs,
new_node.condition)
front_layer.remove(node)
self.applied_gates.add(node)
for successor in dag.quantum_successors(node):
if successor.type != 'op':
continue
if self._is_resolved(successor, dag):
front_layer.append(successor)
if node.qargs:
self._reset_qubits_decay()
# Diagnostics
logger.debug('free! %s',
[(n.name, n.qargs) for n in execute_gate_list])
logger.debug('front_layer: %s',
[(n.name, n.qargs) for n in front_layer])
continue
# After all free gates are exhausted, heuristically find
# the best swap and insert it. When two or more swaps tie
# for best score, pick one randomly.
extended_set = self._obtain_extended_set(dag, front_layer)
swap_candidates = self._obtain_swaps(front_layer, current_layout)
swap_scores = dict.fromkeys(swap_candidates, 0)
for swap_qubits in swap_scores:
trial_layout = current_layout.copy()
trial_layout.swap(*swap_qubits)
score = self._score_heuristic(self.heuristic, front_layer,
extended_set, trial_layout,
swap_qubits)
swap_scores[swap_qubits] = score
min_score = min(swap_scores.values())
best_swaps = [k for k, v in swap_scores.items() if v == min_score]
best_swaps.sort(key=lambda x: (x[0].index, x[1].index))
best_swap = rng.choice(best_swaps)
swap_node = DAGNode(op=SwapGate(), qargs=best_swap, type='op')
swap_node = _transform_gate_for_layout(swap_node, current_layout)
mapped_dag.apply_operation_back(swap_node.op, swap_node.qargs)
current_layout.swap(*best_swap)
num_search_steps += 1
if num_search_steps % DECAY_RESET_INTERVAL == 0:
self._reset_qubits_decay()
else:
self.qubits_decay[best_swap[0]] += DECAY_RATE
self.qubits_decay[best_swap[1]] += DECAY_RATE
# Diagnostics
logger.debug('SWAP Selection...')
logger.debug('extended_set: %s',
[(n.name, n.qargs) for n in extended_set])
logger.debug('swap scores: %s', swap_scores)
logger.debug('best swap: %s', best_swap)
logger.debug('qubits decay: %s', self.qubits_decay)
self.property_set['final_layout'] = current_layout
return mapped_dag
def run(self, dag):
"""Run the SabreSwap pass on `dag`.
Args:
dag (DAGCircuit): the directed acyclic graph to be mapped.
Returns:
DAGCircuit: A dag mapped to be compatible with the coupling_map.
Raises:
TranspilerError: if the coupling map or the layout are not
compatible with the DAG
"""
if len(dag.qregs) != 1 or dag.qregs.get("q", None) is None:
raise TranspilerError("Sabre swap runs on physical circuits only.")
if len(dag.qubits) > self.coupling_map.size():
raise TranspilerError("More virtual qubits exist than physical.")
rng = np.random.default_rng(self.seed)
# Preserve input DAG's name, regs, wire_map, etc. but replace the graph.
mapped_dag = None
if not self.fake_run:
mapped_dag = dag._copy_circuit_metadata()
canonical_register = dag.qregs["q"]
current_layout = Layout.generate_trivial_layout(canonical_register)
self._bit_indices = {
bit: idx
for idx, bit in enumerate(canonical_register)
}
# A decay factor for each qubit used to heuristically penalize recently
# used qubits (to encourage parallelism).
self.qubits_decay = {qubit: 1 for qubit in dag.qubits}
# Start algorithm from the front layer and iterate until all gates done.
num_search_steps = 0
front_layer = dag.front_layer()
self.applied_predecessors = defaultdict(int)
for _, input_node in dag.input_map.items():
for successor in self._successors(input_node, dag):
self.applied_predecessors[successor] += 1
while front_layer:
execute_gate_list = []
# Remove as many immediately applicable gates as possible
for node in front_layer:
if len(node.qargs) == 2:
v0, v1 = node.qargs
if self.coupling_map.graph.has_edge(
current_layout[v0], current_layout[v1]):
execute_gate_list.append(node)
else: # Single-qubit gates as well as barriers are free
execute_gate_list.append(node)
if execute_gate_list:
for node in execute_gate_list:
self._apply_gate(mapped_dag, node, current_layout,
canonical_register)
front_layer.remove(node)
for successor in self._successors(node, dag):
self.applied_predecessors[successor] += 1
if self._is_resolved(successor):
front_layer.append(successor)
if node.qargs:
self._reset_qubits_decay()
# Diagnostics
logger.debug("free! %s",
[(n.name, n.qargs) for n in execute_gate_list])
logger.debug("front_layer: %s",
[(n.name, n.qargs) for n in front_layer])
continue
# After all free gates are exhausted, heuristically find
# the best swap and insert it. When two or more swaps tie
# for best score, pick one randomly.
extended_set = self._obtain_extended_set(dag, front_layer)
swap_candidates = self._obtain_swaps(front_layer, current_layout)
swap_scores = dict.fromkeys(swap_candidates, 0)
for swap_qubits in swap_scores:
trial_layout = current_layout.copy()
trial_layout.swap(*swap_qubits)
score = self._score_heuristic(self.heuristic, front_layer,
extended_set, trial_layout,
swap_qubits)
swap_scores[swap_qubits] = score
min_score = min(swap_scores.values())
best_swaps = [k for k, v in swap_scores.items() if v == min_score]
best_swaps.sort(key=lambda x:
(self._bit_indices[x[0]], self._bit_indices[x[1]]))
best_swap = rng.choice(best_swaps)
swap_node = DAGNode(op=SwapGate(), qargs=best_swap, type="op")
self._apply_gate(mapped_dag, swap_node, current_layout,
canonical_register)
current_layout.swap(*best_swap)
num_search_steps += 1
if num_search_steps % DECAY_RESET_INTERVAL == 0:
self._reset_qubits_decay()
else:
self.qubits_decay[best_swap[0]] += DECAY_RATE
self.qubits_decay[best_swap[1]] += DECAY_RATE
# Diagnostics
logger.debug("SWAP Selection...")
logger.debug("extended_set: %s",
[(n.name, n.qargs) for n in extended_set])
logger.debug("swap scores: %s", swap_scores)
logger.debug("best swap: %s", best_swap)
logger.debug("qubits decay: %s", self.qubits_decay)
self.property_set["final_layout"] = current_layout
if not self.fake_run:
return mapped_dag
return dag