# This code is part of Qiskit.
#
# (C) Copyright IBM 2017, 2020.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.
"""Layout selection using the SABRE bidirectional search approach from Li et al.
"""
import copy
import logging
import numpy as np
import rustworkx as rx
from qiskit.converters import dag_to_circuit
from qiskit.transpiler.passes.layout.set_layout import SetLayout
from qiskit.transpiler.passes.layout.full_ancilla_allocation import FullAncillaAllocation
from qiskit.transpiler.passes.layout.enlarge_with_ancilla import EnlargeWithAncilla
from qiskit.transpiler.passes.layout.apply_layout import ApplyLayout
from qiskit.transpiler.passes.layout import disjoint_utils
from qiskit.transpiler.passmanager import PassManager
from qiskit.transpiler.layout import Layout
from qiskit.transpiler.basepasses import TransformationPass
from qiskit.transpiler.exceptions import TranspilerError
from qiskit._accelerate.nlayout import NLayout
from qiskit._accelerate.sabre_layout import sabre_layout_and_routing
from qiskit._accelerate.sabre_swap import (
Heuristic,
NeighborTable,
)
from qiskit.transpiler.passes.routing.sabre_swap import _build_sabre_dag, _apply_sabre_result
from qiskit.transpiler.target import Target
from qiskit.transpiler.coupling import CouplingMap
from qiskit.tools.parallel import CPU_COUNT
logger = logging.getLogger(__name__)
[docs]class SabreLayout(TransformationPass):
"""Choose a Layout via iterative bidirectional routing of the input circuit.
Starting with a random initial `Layout`, the algorithm does a full routing
of the circuit (via the `routing_pass` method) to end up with a
`final_layout`. This final_layout is then used as the initial_layout for
routing the reverse circuit. The algorithm iterates a number of times until
it finds an initial_layout that reduces full routing cost.
This method exploits the reversibility of quantum circuits, and tries to
include global circuit information in the choice of initial_layout.
By default this pass will run both layout and routing and will transform the
circuit so that the layout is applied to the input dag (meaning that the output
circuit will have ancilla qubits allocated for unused qubits on the coupling map
and the qubits will be reordered to match the mapped physical qubits) and then
routing will be applied (inserting :class:`~.SwapGate`s to account for limited
connectivity). This is unlike most other layout passes which are :class:`~.AnalysisPass`
objects and just find an initial layout and set that on the property set. This is
done because by default the pass will run parallel seed trials with different random
seeds for selecting the random initial layout and then selecting the routed output
which results in the least number of swap gates needed.
You can use the ``routing_pass`` argument to have this pass operate as a typical
layout pass. When specified this will use the specified routing pass to select an
initial layout only and will not run multiple seed trials.
**References:**
[1] Li, Gushu, Yufei Ding, and Yuan Xie. "Tackling the qubit mapping problem
for NISQ-era quantum devices." ASPLOS 2019.
`arXiv:1809.02573 <https://arxiv.org/pdf/1809.02573.pdf>`_
"""
def __init__(
self,
coupling_map,
routing_pass=None,
seed=None,
max_iterations=3,
swap_trials=None,
layout_trials=None,
skip_routing=False,
):
"""SabreLayout initializer.
Args:
coupling_map (Union[CouplingMap, Target]): directed graph representing a coupling map.
routing_pass (BasePass): the routing pass to use while iterating.
If specified this pass operates as an :class:`~.AnalysisPass` and
will only populate the ``layout`` field in the property set and
the input dag is returned unmodified. This argument is mutually
exclusive with the ``swap_trials`` and the ``layout_trials``
arguments and if this is specified at the same time as either
argument an error will be raised.
seed (int): seed for setting a random first trial layout.
max_iterations (int): number of forward-backward iterations.
swap_trials (int): The number of trials to run of
:class:`~.SabreSwap` for each iteration. This is equivalent to
the ``trials`` argument on :class:`~.SabreSwap`. If this is not
specified (and ``routing_pass`` isn't set) by default the number
of physical CPUs on your local system will be used. For
reproducibility between environments it is best to set this
to an explicit number because the output will potentially depend
on the number of trials run. This option is mutually exclusive
with the ``routing_pass`` argument and an error will be raised
if both are used.
layout_trials (int): The number of random seed trials to run
layout with. When > 1 the trial that resuls in the output with
the fewest swap gates will be selected. If this is not specified
(and ``routing_pass`` is not set) then the number of local
physical CPUs will be used as the default value. This option is
mutually exclusive with the ``routing_pass`` argument and an error
will be raised if both are used.
skip_routing (bool): If this is set ``True`` and ``routing_pass`` is not used
then routing will not be applied to the output circuit. Only the layout
will be returned in the property set. This is a tradeoff to run custom
routing with multiple layout trials, as using this option will cause
SabreLayout to run the routing stage internally but not use that result.
Raises:
TranspilerError: If both ``routing_pass`` and ``swap_trials`` or
both ``routing_pass`` and ``layout_trials`` are specified
"""
super().__init__()
if isinstance(coupling_map, Target):
self.target = coupling_map
self.coupling_map = self.target.build_coupling_map()
else:
self.target = None
self.coupling_map = coupling_map
self._neighbor_table = None
if routing_pass is not None and (swap_trials is not None or layout_trials is not None):
raise TranspilerError("Both routing_pass and swap_trials can't be set at the same time")
self.routing_pass = routing_pass
self.seed = seed
self.max_iterations = max_iterations
self.trials = swap_trials
if swap_trials is None:
self.swap_trials = CPU_COUNT
else:
self.swap_trials = swap_trials
if layout_trials is None:
self.layout_trials = CPU_COUNT
else:
self.layout_trials = layout_trials
self.skip_routing = skip_routing
if self.coupling_map is not None:
if not self.coupling_map.is_symmetric:
# deepcopy is needed here if we don't own the coupling map (i.e. we were passed it
# directly) to avoid modifications updating shared references in passes which
# require directional constraints
if isinstance(coupling_map, CouplingMap):
self.coupling_map = copy.deepcopy(self.coupling_map)
self.coupling_map.make_symmetric()
self._neighbor_table = NeighborTable(rx.adjacency_matrix(self.coupling_map.graph))
[docs] def run(self, dag):
"""Run the SabreLayout pass on `dag`.
Args:
dag (DAGCircuit): DAG to find layout for.
Returns:
DAGCircuit: The output dag if swap mapping was run
(otherwise the input dag is returned unmodified).
Raises:
TranspilerError: if dag wider than self.coupling_map
"""
if len(dag.qubits) > self.coupling_map.size():
raise TranspilerError("More virtual qubits exist than physical.")
# Choose a random initial_layout.
if self.routing_pass is not None:
if not self.coupling_map.is_connected():
raise TranspilerError(
"The routing_pass argument cannot be used with disjoint coupling maps."
)
if self.seed is None:
seed = np.random.randint(0, np.iinfo(np.int32).max)
else:
seed = self.seed
rng = np.random.default_rng(seed)
physical_qubits = rng.choice(self.coupling_map.size(), len(dag.qubits), replace=False)
physical_qubits = rng.permutation(physical_qubits)
initial_layout = Layout({q: dag.qubits[i] for i, q in enumerate(physical_qubits)})
self.routing_pass.fake_run = True
# Do forward-backward iterations.
circ = dag_to_circuit(dag)
rev_circ = circ.reverse_ops()
for _ in range(self.max_iterations):
for _ in ("forward", "backward"):
pm = self._layout_and_route_passmanager(initial_layout)
new_circ = pm.run(circ)
# Update initial layout and reverse the unmapped circuit.
pass_final_layout = pm.property_set["final_layout"]
final_layout = self._compose_layouts(
initial_layout, pass_final_layout, new_circ.qregs
)
initial_layout = final_layout
circ, rev_circ = rev_circ, circ
# Diagnostics
logger.info("new initial layout")
logger.info(initial_layout)
for qreg in dag.qregs.values():
initial_layout.add_register(qreg)
self.property_set["layout"] = initial_layout
self.routing_pass.fake_run = False
return dag
# Combined
if self.target is not None:
# This is a special case SABRE only works with a bidirectional coupling graph
# which we explicitly can't create from the target. So do this manually here
# to avoid altering the shared state with the unfiltered indices.
target = self.target.build_coupling_map(filter_idle_qubits=True)
target.make_symmetric()
else:
target = self.coupling_map
layout_components = disjoint_utils.run_pass_over_connected_components(
dag,
target,
self._inner_run,
)
initial_layout_dict = {}
final_layout_dict = {}
for (
layout_dict,
final_dict,
component_map,
_sabre_result,
_circuit_to_dag_dict,
local_dag,
) in layout_components:
initial_layout_dict.update({k: component_map[v] for k, v in layout_dict.items()})
final_layout_dict.update({component_map[k]: component_map[v] for k, v in final_dict})
self.property_set["layout"] = Layout(initial_layout_dict)
# If skip_routing is set then return the layout in the property set
# and throwaway the extra work we did to compute the swap map.
# We also skip routing here if there is more than one connected
# component we ran layout on. We can only reliably route the full dag
# in this case if there is any dependency between the components
# (typically shared classical data or barriers).
if self.skip_routing or len(layout_components) > 1:
return dag
# After this point the pass is no longer an analysis pass and the
# output circuit returned is transformed with the layout applied
# and swaps inserted
dag = self._apply_layout_no_pass_manager(dag)
mapped_dag = dag.copy_empty_like()
self.property_set["final_layout"] = Layout(
{dag.qubits[k]: v for (k, v) in final_layout_dict.items()}
)
canonical_register = dag.qregs["q"]
original_layout = NLayout.generate_trivial_layout(self.coupling_map.size())
for (
_layout_dict,
_final_layout_dict,
component_map,
sabre_result,
circuit_to_dag_dict,
local_dag,
) in layout_components:
_apply_sabre_result(
mapped_dag,
local_dag,
initial_layout_dict,
canonical_register,
original_layout,
sabre_result,
circuit_to_dag_dict,
component_map,
)
disjoint_utils.combine_barriers(mapped_dag, retain_uuid=False)
return mapped_dag
def _inner_run(self, dag, coupling_map):
if not coupling_map.is_symmetric:
# deepcopy is needed here to avoid modifications updating
# shared references in passes which require directional
# constraints
coupling_map = copy.deepcopy(coupling_map)
coupling_map.make_symmetric()
neighbor_table = NeighborTable(rx.adjacency_matrix(coupling_map.graph))
dist_matrix = coupling_map.distance_matrix
original_qubit_indices = {bit: index for index, bit in enumerate(dag.qubits)}
sabre_dag, circuit_to_dag_dict = _build_sabre_dag(
dag,
coupling_map.size(),
original_qubit_indices,
)
((initial_layout, final_layout), sabre_result) = sabre_layout_and_routing(
sabre_dag,
neighbor_table,
dist_matrix,
Heuristic.Decay,
self.max_iterations,
self.swap_trials,
self.layout_trials,
self.seed,
)
# Apply initial layout selected.
layout_dict = {}
num_qubits = len(dag.qubits)
for k, v in initial_layout.layout_mapping():
if k < num_qubits:
layout_dict[dag.qubits[k]] = v
final_layout_dict = final_layout.layout_mapping()
component_mapping = {x: coupling_map.graph[x] for x in coupling_map.graph.node_indices()}
return (
layout_dict,
final_layout_dict,
component_mapping,
sabre_result,
circuit_to_dag_dict,
dag,
)
def _apply_layout_no_pass_manager(self, dag):
"""Apply and embed a layout into a dagcircuit without using a ``PassManager`` to
avoid circuit<->dag conversion.
"""
ancilla_pass = FullAncillaAllocation(self.coupling_map)
ancilla_pass.property_set = self.property_set
dag = ancilla_pass.run(dag)
enlarge_pass = EnlargeWithAncilla()
enlarge_pass.property_set = ancilla_pass.property_set
dag = enlarge_pass.run(dag)
apply_pass = ApplyLayout()
apply_pass.property_set = enlarge_pass.property_set
dag = apply_pass.run(dag)
return dag
def _layout_and_route_passmanager(self, initial_layout):
"""Return a passmanager for a full layout and routing.
We use a factory to remove potential statefulness of passes.
"""
layout_and_route = [
SetLayout(initial_layout),
FullAncillaAllocation(self.coupling_map),
EnlargeWithAncilla(),
ApplyLayout(),
self.routing_pass,
]
pm = PassManager(layout_and_route)
return pm
def _compose_layouts(self, initial_layout, pass_final_layout, qregs):
"""Return the real final_layout resulting from the composition
of an initial_layout with the final_layout reported by a pass.
The routing passes internally start with a trivial layout, as the
layout gets applied to the circuit prior to running them. So the
"final_layout" they report must be amended to account for the actual
initial_layout that was selected.
"""
trivial_layout = Layout.generate_trivial_layout(*qregs)
qubit_map = Layout.combine_into_edge_map(initial_layout, trivial_layout)
final_layout = {v: pass_final_layout._v2p[qubit_map[v]] for v in initial_layout._v2p}
return Layout(final_layout)