C贸digo fuente para qiskit.compiler.transpiler

# This code is part of Qiskit.
#
# (C) Copyright IBM 2017, 2019.
#
# 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.

# pylint: disable=invalid-sequence-index

"""Circuit transpile function"""
import copy
import logging
from time import time
from typing import List, Union, Dict, Callable, Any, Optional, TypeVar
import warnings

from qiskit import user_config
from qiskit.circuit.quantumcircuit import QuantumCircuit
from qiskit.circuit.quantumregister import Qubit
from qiskit.dagcircuit import DAGCircuit
from qiskit.providers.backend import Backend
from qiskit.providers.models import BackendProperties
from qiskit.pulse import Schedule, InstructionScheduleMap
from qiskit.transpiler import Layout, CouplingMap, PropertySet
from qiskit.transpiler.basepasses import BasePass
from qiskit.transpiler.exceptions import TranspilerError
from qiskit.transpiler.instruction_durations import InstructionDurations, InstructionDurationsType
from qiskit.transpiler.passes.synthesis.high_level_synthesis import HLSConfig
from qiskit.transpiler.preset_passmanagers import generate_preset_pass_manager
from qiskit.transpiler.timing_constraints import TimingConstraints
from qiskit.transpiler.target import Target, target_to_backend_properties

logger = logging.getLogger(__name__)

_CircuitT = TypeVar("_CircuitT", bound=Union[QuantumCircuit, List[QuantumCircuit]])


[documentos]def transpile( # pylint: disable=too-many-return-statements circuits: _CircuitT, backend: Optional[Backend] = None, basis_gates: Optional[List[str]] = None, inst_map: Optional[List[InstructionScheduleMap]] = None, coupling_map: Optional[Union[CouplingMap, List[List[int]]]] = None, backend_properties: Optional[BackendProperties] = None, initial_layout: Optional[Union[Layout, Dict, List]] = None, layout_method: Optional[str] = None, routing_method: Optional[str] = None, translation_method: Optional[str] = None, scheduling_method: Optional[str] = None, instruction_durations: Optional[InstructionDurationsType] = None, dt: Optional[float] = None, approximation_degree: Optional[float] = 1.0, timing_constraints: Optional[Dict[str, int]] = None, seed_transpiler: Optional[int] = None, optimization_level: Optional[int] = None, callback: Optional[Callable[[BasePass, DAGCircuit, float, PropertySet, int], Any]] = None, output_name: Optional[Union[str, List[str]]] = None, unitary_synthesis_method: str = "default", unitary_synthesis_plugin_config: Optional[dict] = None, target: Optional[Target] = None, hls_config: Optional[HLSConfig] = None, init_method: Optional[str] = None, optimization_method: Optional[str] = None, ignore_backend_supplied_default_methods: bool = False, ) -> _CircuitT: """Transpile one or more circuits, according to some desired transpilation targets. Transpilation is potentially done in parallel using multiprocessing when ``circuits`` is a list with > 1 :class:`~.QuantumCircuit` object depending on the local environment and configuration. Args: circuits: Circuit(s) to transpile backend: If set, the transpiler will compile the input circuit to this target device. If any other option is explicitly set (e.g., ``coupling_map``), it will override the backend's. basis_gates: List of basis gate names to unroll to (e.g: ``['u1', 'u2', 'u3', 'cx']``). If ``None``, do not unroll. inst_map: Mapping of unrolled gates to pulse schedules. If this is not provided, transpiler tries to get from the backend. If any user defined calibration is found in the map and this is used in a circuit, transpiler attaches the custom gate definition to the circuit. This enables one to flexibly override the low-level instruction implementation. This feature is available iff the backend supports the pulse gate experiment. coupling_map: Directed coupling map (perhaps custom) to target in mapping. If the coupling map is symmetric, both directions need to be specified. Multiple formats are supported: #. ``CouplingMap`` instance #. List, must be given as an adjacency matrix, where each entry specifies all directed two-qubit interactions supported by backend, e.g: ``[[0, 1], [0, 3], [1, 2], [1, 5], [2, 5], [4, 1], [5, 3]]`` backend_properties: properties returned by a backend, including information on gate errors, readout errors, qubit coherence times, etc. Find a backend that provides this information with: ``backend.properties()`` initial_layout: Initial position of virtual qubits on physical qubits. If this layout makes the circuit compatible with the coupling_map constraints, it will be used. The final layout is not guaranteed to be the same, as the transpiler may permute qubits through swaps or other means. Multiple formats are supported: #. ``Layout`` instance #. Dict * virtual to physical:: {qr[0]: 0, qr[1]: 3, qr[2]: 5} * physical to virtual:: {0: qr[0], 3: qr[1], 5: qr[2]} #. List * virtual to physical:: [0, 3, 5] # virtual qubits are ordered (in addition to named) * physical to virtual:: [qr[0], None, None, qr[1], None, qr[2]] layout_method: Name of layout selection pass ('trivial', 'dense', 'noise_adaptive', 'sabre'). This can also be the external plugin name to use for the ``layout`` stage. You can see a list of installed plugins by using :func:`~.list_stage_plugins` with ``"layout"`` for the ``stage_name`` argument. routing_method: Name of routing pass ('basic', 'lookahead', 'stochastic', 'sabre', 'none'). Note This can also be the external plugin name to use for the ``routing`` stage. You can see a list of installed plugins by using :func:`~.list_stage_plugins` with ``"routing"`` for the ``stage_name`` argument. translation_method: Name of translation pass ('unroller', 'translator', 'synthesis') This can also be the external plugin name to use for the ``translation`` stage. You can see a list of installed plugins by using :func:`~.list_stage_plugins` with ``"translation"`` for the ``stage_name`` argument. scheduling_method: Name of scheduling pass. * ``'as_soon_as_possible'``: Schedule instructions greedily, as early as possible on a qubit resource. (alias: ``'asap'``) * ``'as_late_as_possible'``: Schedule instructions late, i.e. keeping qubits in the ground state when possible. (alias: ``'alap'``) If ``None``, no scheduling will be done. This can also be the external plugin name to use for the ``scheduling`` stage. You can see a list of installed plugins by using :func:`~.list_stage_plugins` with ``"scheduling"`` for the ``stage_name`` argument. instruction_durations: Durations of instructions. Applicable only if scheduling_method is specified. The gate lengths defined in ``backend.properties`` are used as default. They are overwritten if this ``instruction_durations`` is specified. The format of ``instruction_durations`` must be as follows. The `instruction_durations` must be given as a list of tuples [(instruction_name, qubits, duration, unit), ...]. | [('cx', [0, 1], 12.3, 'ns'), ('u3', [0], 4.56, 'ns')] | [('cx', [0, 1], 1000), ('u3', [0], 300)] If unit is omitted, the default is 'dt', which is a sample time depending on backend. If the time unit is 'dt', the duration must be an integer. dt: Backend sample time (resolution) in seconds. If ``None`` (default), ``backend.configuration().dt`` is used. approximation_degree (float): heuristic dial used for circuit approximation (1.0=no approximation, 0.0=maximal approximation) timing_constraints: An optional control hardware restriction on instruction time resolution. A quantum computer backend may report a set of restrictions, namely: - granularity: An integer value representing minimum pulse gate resolution in units of ``dt``. A user-defined pulse gate should have duration of a multiple of this granularity value. - min_length: An integer value representing minimum pulse gate length in units of ``dt``. A user-defined pulse gate should be longer than this length. - pulse_alignment: An integer value representing a time resolution of gate instruction starting time. Gate instruction should start at time which is a multiple of the alignment value. - acquire_alignment: An integer value representing a time resolution of measure instruction starting time. Measure instruction should start at time which is a multiple of the alignment value. This information will be provided by the backend configuration. If the backend doesn't have any restriction on the instruction time allocation, then ``timing_constraints`` is None and no adjustment will be performed. seed_transpiler: Sets random seed for the stochastic parts of the transpiler optimization_level: How much optimization to perform on the circuits. Higher levels generate more optimized circuits, at the expense of longer transpilation time. * 0: no optimization * 1: light optimization * 2: heavy optimization * 3: even heavier optimization If ``None``, level 1 will be chosen as default. callback: A callback function that will be called after each pass execution. The function will be called with 5 keyword arguments, | ``pass_``: the pass being run. | ``dag``: the dag output of the pass. | ``time``: the time to execute the pass. | ``property_set``: the property set. | ``count``: the index for the pass execution. The exact arguments passed expose the internals of the pass manager, and are subject to change as the pass manager internals change. If you intend to reuse a callback function over multiple releases, be sure to check that the arguments being passed are the same. To use the callback feature, define a function that will take in kwargs dict and access the variables. For example:: def callback_func(**kwargs): pass_ = kwargs['pass_'] dag = kwargs['dag'] time = kwargs['time'] property_set = kwargs['property_set'] count = kwargs['count'] ... transpile(circ, callback=callback_func) output_name: A list with strings to identify the output circuits. The length of the list should be exactly the length of the ``circuits`` parameter. unitary_synthesis_method (str): The name of the unitary synthesis method to use. By default ``'default'`` is used. You can see a list of installed plugins with :func:`.unitary_synthesis_plugin_names`. unitary_synthesis_plugin_config: An optional configuration dictionary that will be passed directly to the unitary synthesis plugin. By default this setting will have no effect as the default unitary synthesis method does not take custom configuration. This should only be necessary when a unitary synthesis plugin is specified with the ``unitary_synthesis`` argument. As this is custom for each unitary synthesis plugin refer to the plugin documentation for how to use this option. target: A backend transpiler target. Normally this is specified as part of the ``backend`` argument, but if you have manually constructed a :class:`~qiskit.transpiler.Target` object you can specify it manually here. This will override the target from ``backend``. hls_config: An optional configuration class :class:`~qiskit.transpiler.passes.synthesis.HLSConfig` that will be passed directly to :class:`~qiskit.transpiler.passes.synthesis.HighLevelSynthesis` transformation pass. This configuration class allows to specify for various high-level objects the lists of synthesis algorithms and their parameters. init_method: The plugin name to use for the ``init`` stage. By default an external plugin is not used. You can see a list of installed plugins by using :func:`~.list_stage_plugins` with ``"init"`` for the stage name argument. optimization_method: The plugin name to use for the ``optimization`` stage. By default an external plugin is not used. You can see a list of installed plugins by using :func:`~.list_stage_plugins` with ``"optimization"`` for the ``stage_name`` argument. ignore_backend_supplied_default_methods: If set to ``True`` any default methods specified by a backend will be ignored. Some backends specify alternative default methods to support custom compilation target-specific passes/plugins which support backend-specific compilation techniques. If you'd prefer that these defaults were not used this option is used to disable those backend-specific defaults. Returns: The transpiled circuit(s). Raises: TranspilerError: in case of bad inputs to transpiler (like conflicting parameters) or errors in passes """ arg_circuits_list = isinstance(circuits, list) circuits = circuits if arg_circuits_list else [circuits] if not circuits: return [] # transpiling schedules is not supported yet. start_time = time() if all(isinstance(c, Schedule) for c in circuits): warnings.warn("Transpiling schedules is not supported yet.", UserWarning) end_time = time() _log_transpile_time(start_time, end_time) if arg_circuits_list: return circuits else: return circuits[0] if optimization_level is None: # Take optimization level from the configuration or 1 as default. config = user_config.get_config() optimization_level = config.get("transpile_optimization_level", 1) if ( scheduling_method is not None and backend is None and target is None and not instruction_durations ): warnings.warn( "When scheduling circuits without backend," " 'instruction_durations' should be usually provided.", UserWarning, ) _skip_target = False _given_inst_map = bool(inst_map) # check before inst_map is overwritten # If a target is specified have it override any implicit selections from a backend if target is not None: if coupling_map is None: coupling_map = target.build_coupling_map() if basis_gates is None: basis_gates = list(target.operation_names) if instruction_durations is None: instruction_durations = target.durations() if inst_map is None: inst_map = target.instruction_schedule_map() if dt is None: dt = target.dt if timing_constraints is None: timing_constraints = target.timing_constraints() if backend_properties is None: backend_properties = target_to_backend_properties(target) # If target is not specified and any hardware constraint object is # manually specified then do not use the target from the backend as # it is invalidated by a custom basis gate list or a custom coupling map elif basis_gates is not None or coupling_map is not None: _skip_target = True else: target = getattr(backend, "target", None) initial_layout = _parse_initial_layout(initial_layout) coupling_map = _parse_coupling_map(coupling_map, backend) approximation_degree = _parse_approximation_degree(approximation_degree) output_name = _parse_output_name(output_name, circuits) inst_map = _parse_inst_map(inst_map, backend) _check_circuits_coupling_map(circuits, coupling_map, backend) timing_constraints = _parse_timing_constraints(backend, timing_constraints) if _given_inst_map and inst_map.has_custom_gate() and target is not None: # Do not mutate backend target target = copy.deepcopy(target) target.update_from_instruction_schedule_map(inst_map) if not ignore_backend_supplied_default_methods: if scheduling_method is None and hasattr(backend, "get_scheduling_stage_plugin"): scheduling_method = backend.get_scheduling_stage_plugin() if translation_method is None and hasattr(backend, "get_translation_stage_plugin"): translation_method = backend.get_translation_stage_plugin() if instruction_durations or dt: # If durations are provided and there is more than one circuit # we need to serialize the execution because the full durations # is dependent on the circuit calibrations which are per circuit if len(circuits) > 1: out_circuits = [] for circuit in circuits: instruction_durations = _parse_instruction_durations( backend, instruction_durations, dt, circuit ) pm = generate_preset_pass_manager( optimization_level, backend=backend, target=target, basis_gates=basis_gates, inst_map=inst_map, coupling_map=coupling_map, instruction_durations=instruction_durations, backend_properties=backend_properties, timing_constraints=timing_constraints, initial_layout=initial_layout, layout_method=layout_method, routing_method=routing_method, translation_method=translation_method, scheduling_method=scheduling_method, approximation_degree=approximation_degree, seed_transpiler=seed_transpiler, unitary_synthesis_method=unitary_synthesis_method, unitary_synthesis_plugin_config=unitary_synthesis_plugin_config, hls_config=hls_config, init_method=init_method, optimization_method=optimization_method, _skip_target=_skip_target, ) out_circuits.append(pm.run(circuit, callback=callback)) for name, circ in zip(output_name, out_circuits): circ.name = name end_time = time() _log_transpile_time(start_time, end_time) return out_circuits else: instruction_durations = _parse_instruction_durations( backend, instruction_durations, dt, circuits[0] ) pm = generate_preset_pass_manager( optimization_level, backend=backend, target=target, basis_gates=basis_gates, inst_map=inst_map, coupling_map=coupling_map, instruction_durations=instruction_durations, backend_properties=backend_properties, timing_constraints=timing_constraints, initial_layout=initial_layout, layout_method=layout_method, routing_method=routing_method, translation_method=translation_method, scheduling_method=scheduling_method, approximation_degree=approximation_degree, seed_transpiler=seed_transpiler, unitary_synthesis_method=unitary_synthesis_method, unitary_synthesis_plugin_config=unitary_synthesis_plugin_config, hls_config=hls_config, init_method=init_method, optimization_method=optimization_method, _skip_target=_skip_target, ) out_circuits = pm.run(circuits, callback=callback) for name, circ in zip(output_name, out_circuits): circ.name = name end_time = time() _log_transpile_time(start_time, end_time) if arg_circuits_list: return out_circuits else: return out_circuits[0]
def _check_circuits_coupling_map(circuits, cmap, backend): # Check circuit width against number of qubits in coupling_map(s) max_qubits = None if cmap is not None: max_qubits = cmap.size() elif backend is not None: backend_version = getattr(backend, "version", 0) if backend_version <= 1: if not backend.configuration().simulator: max_qubits = backend.configuration().n_qubits else: max_qubits = None else: max_qubits = backend.num_qubits for circuit in circuits: # If coupling_map is not None or num_qubits == 1 num_qubits = len(circuit.qubits) if max_qubits is not None and (num_qubits > max_qubits): raise TranspilerError( f"Number of qubits ({num_qubits}) in {circuit.name} " f"is greater than maximum ({max_qubits}) in the coupling_map" ) def _log_transpile_time(start_time, end_time): log_msg = "Total Transpile Time - %.5f (ms)" % ((end_time - start_time) * 1000) logger.info(log_msg) def _parse_inst_map(inst_map, backend): # try getting inst_map from user, else backend if inst_map is None: backend_version = getattr(backend, "version", 0) if backend_version <= 1: if hasattr(backend, "defaults"): inst_map = getattr(backend.defaults(), "instruction_schedule_map", None) else: inst_map = backend.target.instruction_schedule_map() return inst_map def _parse_coupling_map(coupling_map, backend): # try getting coupling_map from user, else backend if coupling_map is None: backend_version = getattr(backend, "version", 0) if backend_version <= 1: if getattr(backend, "configuration", None): configuration = backend.configuration() if hasattr(configuration, "coupling_map") and configuration.coupling_map: coupling_map = CouplingMap(configuration.coupling_map) else: coupling_map = backend.coupling_map # coupling_map could be None, or a list of lists, e.g. [[0, 1], [2, 1]] if coupling_map is None or isinstance(coupling_map, CouplingMap): return coupling_map if isinstance(coupling_map, list) and all( isinstance(i, list) and len(i) == 2 for i in coupling_map ): return CouplingMap(coupling_map) else: raise TranspilerError( "Only a single input coupling map can be used with transpile() if you need to " "target different coupling maps for different circuits you must call transpile() " "multiple times" ) def _parse_initial_layout(initial_layout): # initial_layout could be None, or a list of ints, e.g. [0, 5, 14] # or a list of tuples/None e.g. [qr[0], None, qr[1]] or a dict e.g. {qr[0]: 0} if initial_layout is None or isinstance(initial_layout, Layout): return initial_layout if isinstance(initial_layout, dict): return Layout(initial_layout) initial_layout = list(initial_layout) if all(phys is None or isinstance(phys, Qubit) for phys in initial_layout): return Layout.from_qubit_list(initial_layout) return initial_layout def _parse_instruction_durations(backend, inst_durations, dt, circuit): """Create a list of ``InstructionDuration``s. If ``inst_durations`` is provided, the backend will be ignored, otherwise, the durations will be populated from the backend. If any circuits have gate calibrations, those calibration durations would take precedence over backend durations, but be superceded by ``inst_duration``s. """ if not inst_durations: backend_version = getattr(backend, "version", 0) if backend_version <= 1: backend_durations = InstructionDurations() try: backend_durations = InstructionDurations.from_backend(backend) except AttributeError: pass else: backend_durations = backend.instruction_durations circ_durations = InstructionDurations() if not inst_durations: circ_durations.update(backend_durations, dt or backend_durations.dt) if circuit.calibrations: cal_durations = [] for gate, gate_cals in circuit.calibrations.items(): for (qubits, parameters), schedule in gate_cals.items(): cal_durations.append((gate, qubits, parameters, schedule.duration)) circ_durations.update(cal_durations, circ_durations.dt) if inst_durations: circ_durations.update(inst_durations, dt or getattr(inst_durations, "dt", None)) return circ_durations def _parse_approximation_degree(approximation_degree): if approximation_degree is None: return None if approximation_degree < 0.0 or approximation_degree > 1.0: raise TranspilerError("Approximation degree must be in [0.0, 1.0]") return approximation_degree def _parse_output_name(output_name, circuits): # naming and returning circuits # output_name could be either a string or a list if output_name is not None: if isinstance(output_name, str): # single circuit if len(circuits) == 1: return [output_name] # multiple circuits else: raise TranspilerError( "Expected a list object of length equal " + "to that of the number of circuits " + "being transpiled" ) elif isinstance(output_name, list): if len(circuits) == len(output_name) and all( isinstance(name, str) for name in output_name ): return output_name else: raise TranspilerError( "The length of output_name list " "must be equal to the number of " "transpiled circuits and the output_name " "list should be strings." ) else: raise TranspilerError( "The parameter output_name should be a string or a" "list of strings: %s was used." % type(output_name) ) else: return [circuit.name for circuit in circuits] def _parse_timing_constraints(backend, timing_constraints): if isinstance(timing_constraints, TimingConstraints): return timing_constraints if backend is None and timing_constraints is None: timing_constraints = TimingConstraints() else: backend_version = getattr(backend, "version", 0) if backend_version <= 1: if timing_constraints is None: # get constraints from backend timing_constraints = getattr(backend.configuration(), "timing_constraints", {}) timing_constraints = TimingConstraints(**timing_constraints) else: timing_constraints = backend.target.timing_constraints() return timing_constraints