def transpile(dag,
basis_gates='u1,u2,u3,cx,id',
coupling_map=None,
initial_layout=None,
get_layout=False,
format='dag',
seed=None,
pass_manager=None):
"""Transform a dag circuit into another dag circuit (transpile), through
consecutive passes on the dag.
Args:
dag (DAGCircuit): dag circuit to transform via transpilation
basis_gates (str): a comma separated string for the target basis gates
coupling_map (list): A graph of coupling::
[
[control0(int), target0(int)],
[control1(int), target1(int)],
]
eg. [[0, 2], [1, 2], [1, 3], [3, 4]}
initial_layout (dict): A mapping of qubit to qubit::
{
("q", start(int)): ("q", final(int)),
...
}
eg.
{
("q", 0): ("q", 0),
("q", 1): ("q", 1),
("q", 2): ("q", 2),
("q", 3): ("q", 3)
}
get_layout (bool): flag for returning the final layout after mapping
format (str): The target format of the compilation:
{'dag', 'json', 'qasm'}
seed (int): random seed for the swap mapper
pass_manager (PassManager): pass manager instance for the transpilation process
If None, a default set of passes are run.
Otherwise, the passes defined in it will run.
If contains no passes in it, no dag transformations occur.
Returns:
DAGCircuit: transformed dag
DAGCircuit, dict: transformed dag along with the final layout on backend qubits
Raises:
TranspilerError: if the format is not valid.
"""
# TODO: `basis_gates` will be removed after we have the unroller pass.
# TODO: `coupling_map`, `initial_layout`, `get_layout`, `seed` removed after mapper pass.
# TODO: move this to the mapper pass
num_qubits = sum(dag.qregs.values())
if num_qubits == 1 or coupling_map == "all-to-all":
coupling_map = None
final_layout = None
if pass_manager:
# run the passes specified by the pass manager
# TODO return the property set too. See #1086
dag = pass_manager.run_passes(dag)
else:
# default set of passes
# TODO: move each step here to a pass, and use a default passmanager below
basis = basis_gates.split(',') if basis_gates else []
dag_unroller = DagUnroller(dag, DAGBackend(basis))
dag = dag_unroller.expand_gates()
# if a coupling map is given compile to the map
if coupling_map:
logger.info("pre-mapping properties: %s", dag.property_summary())
# Insert swap gates
coupling = Coupling(coupling_list2dict(coupling_map))
removed_meas = remove_last_measurements(dag)
logger.info("measurements moved: %s", removed_meas)
logger.info("initial layout: %s", initial_layout)
dag, final_layout, last_layout = swap_mapper(dag,
coupling,
initial_layout,
trials=20,
seed=seed)
logger.info("final layout: %s", final_layout)
# Expand swaps
dag_unroller = DagUnroller(dag, DAGBackend(basis))
dag = dag_unroller.expand_gates()
# Change cx directions
dag = direction_mapper(dag, coupling)
# Simplify cx gates
cx_cancellation(dag)
# Simplify single qubit gates
dag = optimize_1q_gates(dag)
return_last_measurements(dag, removed_meas, last_layout)
logger.info("post-mapping properties: %s", dag.property_summary())
# choose output format
# TODO: do we need all of these formats, or just the dag?
if format == 'dag':
compiled_circuit = dag
elif format == 'json':
# FIXME: JsonBackend is wrongly taking an ordered dict as basis, not list
dag_unroller = DagUnroller(dag, JsonBackend(dag.basis))
compiled_circuit = dag_unroller.execute()
elif format == 'qasm':
compiled_circuit = dag.qasm()
else:
raise TranspilerError('unrecognized circuit format')
if get_layout:
return compiled_circuit, final_layout
return compiled_circuit
def compile(circuits,
backend,
config=None,
basis_gates=None,
coupling_map=None,
initial_layout=None,
shots=1024,
max_credits=10,
seed=None,
qobj_id=None,
hpc=None,
skip_transpiler=False):
"""Compile a list of circuits into a qobj.
Args:
circuits (QuantumCircuit or list[QuantumCircuit]): circuits to compile
backend (BaseBackend or str): a backend to compile for
config (dict): dictionary of parameters (e.g. noise) used by runner
basis_gates (str): comma-separated basis gate set to compile to
coupling_map (list): coupling map (perhaps custom) to target in mapping
initial_layout (list): initial layout of qubits in mapping
shots (int): number of repetitions of each circuit, for sampling
max_credits (int): maximum credits to use
seed (int): random seed for simulators
qobj_id (int): identifier for the generated qobj
hpc (dict): HPC simulator parameters
skip_transpiler (bool): If True, bypass most of the compilation process and
creates a qobj with minimal check nor translation
Returns:
Qobj: the qobj to be run on the backends
Raises:
TranspilerError: in case of bad compile options, e.g. the hpc options.
"""
# pylint: disable=redefined-builtin
# Check for valid parameters for the experiments.
if hpc is not None and \
not all(key in hpc for key in ('multi_shot_optimization', 'omp_num_threads')):
raise TranspilerError('Unknown HPC parameter format!')
if isinstance(circuits, QuantumCircuit):
circuits = [circuits]
if isinstance(backend, str):
try:
backend = Aer.get_backend(backend)
except KeyError:
backend = IBMQ.get_backend(backend)
pass_manager = None # default pass manager which executes predetermined passes
if skip_transpiler: # empty pass manager which does nothing
pass_manager = PassManager()
backend_conf = backend.configuration()
backend_name = backend_conf['name']
basis_gates = basis_gates or backend_conf['basis_gates']
coupling_map = coupling_map or backend_conf['coupling_map']
qobj_config = deepcopy(config or {})
qobj_config.update({
'shots': shots,
'max_credits': max_credits,
'memory_slots': 0
})
qobj = Qobj(qobj_id=qobj_id or str(uuid.uuid4()),
config=QobjConfig(**qobj_config),
experiments=[],
header=QobjHeader(backend_name=backend_name))
if seed:
qobj.config.seed = seed
qobj.experiments = parallel_map(_build_exp_parallel,
list(range(len(circuits))),
task_args=(circuits, backend),
task_kwargs={
'initial_layout': initial_layout,
'basis_gates': basis_gates,
'config': config,
'coupling_map': coupling_map,
'seed': seed,
'pass_manager': pass_manager
})
qobj.config.memory_slots = max(experiment.config.memory_slots
for experiment in qobj.experiments)
qobj.config.n_qubits = max(experiment.config.n_qubits
for experiment in qobj.experiments)
return qobj
def transpile(circuits,
backend,
basis_gates=None,
coupling_map=None,
initial_layout=None,
seed_mapper=None,
hpc=None,
pass_manager=None):
"""transpile a list of circuits into a dags.
Args:
circuits (QuantumCircuit or list[QuantumCircuit]): circuits to compile
backend (BaseBackend): a backend to compile for
basis_gates (str): comma-separated basis gate set to compile to
coupling_map (list): coupling map (perhaps custom) to target in mapping
initial_layout (list): initial layout of qubits in mapping
seed_mapper (int): random seed for the swap_mapper
hpc (dict): HPC simulator parameters
pass_manager (PassManager): a pass_manager for the transpiler stage
Returns:
dags: a list of dags.
Raises:
TranspilerError: in case of bad compile options, e.g. the hpc options.
"""
if isinstance(circuits, QuantumCircuit):
circuits = [circuits]
# FIXME: THIS NEEDS TO BE CLEANED UP -- some things to decide for list of circuits:
# 1. do all circuits have same coupling map?
# 2. do all circuit have the same basis set?
# 3. do they all have same registers etc?
backend_conf = backend.configuration()
# Check for valid parameters for the experiments.
if hpc is not None and \
not all(key in hpc for key in ('multi_shot_optimization', 'omp_num_threads')):
raise TranspilerError('Unknown HPC parameter format!')
basis_gates = basis_gates or backend_conf['basis_gates']
coupling_map = coupling_map or backend_conf['coupling_map']
# step 1: Making the list of dag circuits
dags = _circuits_2_dags(circuits)
# step 2: Transpile all the dags
# FIXME: Work-around for transpiling multiple circuits with different qreg names.
# Make compile take a list of initial_layouts.
_initial_layout = initial_layout
# Pick a good initial layout if coupling_map is not already satisfied
# otherwise keep it as q[i]->q[i].
# TODO: move this inside mapper pass.
initial_layouts = []
for dag in dags:
if (initial_layout is None and not backend.configuration()['simulator']
and not _matches_coupling_map(dag, coupling_map)):
_initial_layout = _pick_best_layout(dag, backend)
initial_layouts.append(_initial_layout)
dags = _dags_2_dags(dags,
basis_gates=basis_gates,
coupling_map=coupling_map,
initial_layouts=initial_layouts,
seed_mapper=seed_mapper,
pass_manager=pass_manager)
# TODO: change it to circuits
# TODO: make it parallel
return dags
def compile(circuits,
backend,
config=None,
basis_gates=None,
coupling_map=None,
initial_layout=None,
shots=1024,
max_credits=10,
seed=None,
qobj_id=None,
hpc=None,
pass_manager=None):
"""Compile a list of circuits into a qobj.
Args:
circuits (QuantumCircuit or list[QuantumCircuit]): circuits to compile
backend (BaseBackend): a backend to compile for
config (dict): dictionary of parameters (e.g. noise) used by runner
basis_gates (str): comma-separated basis gate set to compile to
coupling_map (list): coupling map (perhaps custom) to target in mapping
initial_layout (list): initial layout of qubits in mapping
shots (int): number of repetitions of each circuit, for sampling
max_credits (int): maximum credits to use
seed (int): random seed for simulators
qobj_id (int): identifier for the generated qobj
hpc (dict): HPC simulator parameters
pass_manager (PassManager): a pass_manager for the transpiler stage
Returns:
QobjExperiment: Experiment to be wrapped in a Qobj.
Raises:
TranspilerError: in case of bad compile options, e.g. the hpc options.
"""
if isinstance(circuits, QuantumCircuit):
circuits = [circuits]
# FIXME: THIS NEEDS TO BE CLEANED UP -- some things to decide for list of circuits:
# 1. do all circuits have same coupling map?
# 2. do all circuit have the same basis set?
# 3. do they all have same registers etc?
backend_conf = backend.configuration()
backend_name = backend_conf['name']
# Check for valid parameters for the experiments.
if hpc is not None and \
not all(key in hpc for key in ('multi_shot_optimization', 'omp_num_threads')):
raise TranspilerError('Unknown HPC parameter format!')
basis_gates = basis_gates or backend_conf['basis_gates']
coupling_map = coupling_map or backend_conf['coupling_map']
# step 1: Making the list of dag circuits
dags = _circuits_2_dags(circuits)
# step 2: Transpile all the dags
# FIXME: Work-around for transpiling multiple circuits with different qreg names.
# Make compile take a list of initial_layouts.
_initial_layout = initial_layout
# Pick a good initial layout if coupling_map is not already satisfied
# otherwise keep it as q[i]->q[i].
# TODO: move this inside mapper pass.
initial_layouts = []
for dag in dags:
if (initial_layout is None and not backend.configuration()['simulator']
and not _matches_coupling_map(dag, coupling_map)):
_initial_layout = _pick_best_layout(dag, backend)
initial_layouts.append(_initial_layout)
dags = _transpile_dags(dags,
basis_gates=basis_gates,
coupling_map=coupling_map,
initial_layouts=initial_layouts,
seed=seed,
pass_manager=pass_manager)
# step 3: Making a qobj
qobj = _dags_2_qobj(dags,
backend_name=backend_name,
config=config,
shots=shots,
max_credits=max_credits,
qobj_id=qobj_id,
basis_gates=basis_gates,
coupling_map=coupling_map,
seed=seed)
return qobj
def compile(circuits,
backend,
config=None,
basis_gates=None,
coupling_map=None,
initial_layout=None,
shots=1024,
max_credits=10,
seed=None,
qobj_id=None,
hpc=None,
pass_manager=None):
"""Compile a list of circuits into a qobj.
Args:
circuits (QuantumCircuit or list[QuantumCircuit]): circuits to compile
backend (BaseBackend): a backend to compile for
config (dict): dictionary of parameters (e.g. noise) used by runner
basis_gates (str): comma-separated basis gate set to compile to
coupling_map (list): coupling map (perhaps custom) to target in mapping
initial_layout (list): initial layout of qubits in mapping
shots (int): number of repetitions of each circuit, for sampling
max_credits (int): maximum credits to use
seed (int): random seed for simulators
qobj_id (int): identifier for the generated qobj
hpc (dict): HPC simulator parameters
pass_manager (PassManager): a pass_manager for the transpiler stage
Returns:
Qobj: the Qobj to be run on the backends
Raises:
TranspilerError: in case of bad compile options, e.g. the hpc options.
"""
if isinstance(circuits, QuantumCircuit):
circuits = [circuits]
backend_conf = backend.configuration
backend_name = backend_conf['name']
# Step 1: create the Qobj, with empty experiments.
# Copy the configuration: the values in `config` have prefern
qobj_config = deepcopy(config or {})
# TODO: "memory_slots" is required by the qobj schema in the top-level
# qobj.config, and is user-defined. At the moment is set to the maximum
# number of *register* slots for the circuits, in order to have `measure`
# behave properly until the transition is over; and each circuit stores
# its memory_slots in its configuration.
qobj_config.update({
'shots': shots,
'max_credits': max_credits,
'memory_slots': 0
})
qobj = Qobj(id=qobj_id or str(uuid.uuid4()),
config=QobjConfig(**qobj_config),
experiments=[],
header=QobjHeader(backend_name=backend_name))
if seed:
qobj.config.seed = seed
# Check for valid parameters for the experiments.
if hpc is not None and \
not all(key in hpc for key in ('multi_shot_optimization', 'omp_num_threads')):
raise TranspilerError('Unknown HPC parameter format!')
basis_gates = basis_gates or backend_conf['basis_gates']
coupling_map = coupling_map or backend_conf['coupling_map']
# Step 2 and 3: transpile and populate the circuits
for circuit in circuits:
experiment = _compile_single_circuit(circuit, backend, config,
basis_gates, coupling_map,
initial_layout, seed,
pass_manager)
# Step 3c: add the Experiment to the Qobj
qobj.experiments.append(experiment)
# Update the `memory_slots` value.
# TODO: remove when `memory_slots` can be provided by the user.
qobj.config.memory_slots = max(experiment.config.memory_slots
for experiment in qobj.experiments)
return qobj
def transpile(dag_circuit,
basis_gates='u1,u2,u3,cx,id',
coupling_map=None,
initial_layout=None,
get_layout=False,
format='dag',
seed=None,
pass_manager=None):
"""Transform a dag circuit into another dag circuit (transpile), through
consecutive passes on the dag.
Args:
dag_circuit (DAGCircuit): dag circuit to transform via transpilation
basis_gates (str): a comma seperated string for the target basis gates
coupling_map (list): A graph of coupling::
[
[control0(int), target0(int)],
[control1(int), target1(int)],
]
eg. [[0, 2], [1, 2], [1, 3], [3, 4]}
initial_layout (dict): A mapping of qubit to qubit::
{
("q", start(int)): ("q", final(int)),
...
}
eg.
{
("q", 0): ("q", 0),
("q", 1): ("q", 1),
("q", 2): ("q", 2),
("q", 3): ("q", 3)
}
get_layout (bool): flag for returning the layout
format (str): The target format of the compilation:
{'dag', 'json', 'qasm'}
seed (int): random seed for simulators
pass_manager (PassManager): pass manager instance for the tranpilation process
If None, a default set of passes are run.
Otherwise, the passes defined in it will run.
If contains no passes in it, no dag transformations occur.
Returns:
object: If get_layout == False, the compiled circuit in the specified
format. If get_layout == True, a tuple is returned, with the
second element being the layout.
Raises:
TranspilerError: if the format is not valid.
"""
final_layout = None
if pass_manager:
# run the passes specified by the pass manager
for pass_ in pass_manager.passes():
pass_.run(dag_circuit)
else:
# default set of passes
# TODO: move each step here to a pass, and use a default passmanager below
basis = basis_gates.split(',') if basis_gates else []
dag_unroller = DagUnroller(dag_circuit, DAGBackend(basis))
dag_circuit = dag_unroller.expand_gates()
# if a coupling map is given compile to the map
if coupling_map:
logger.info("pre-mapping properties: %s",
dag_circuit.property_summary())
# Insert swap gates
coupling = Coupling(coupling_list2dict(coupling_map))
logger.info("initial layout: %s", initial_layout)
dag_circuit, final_layout = swap_mapper(dag_circuit,
coupling,
initial_layout,
trials=20,
seed=seed)
logger.info("final layout: %s", final_layout)
# Expand swaps
dag_unroller = DagUnroller(dag_circuit, DAGBackend(basis))
dag_circuit = dag_unroller.expand_gates()
# Change cx directions
dag_circuit = direction_mapper(dag_circuit, coupling)
# Simplify cx gates
cx_cancellation(dag_circuit)
# Simplify single qubit gates
dag_circuit = optimize_1q_gates(dag_circuit)
logger.info("post-mapping properties: %s",
dag_circuit.property_summary())
# choose output format
# TODO: do we need all of these formats, or just the dag?
if format == 'dag':
compiled_circuit = dag_circuit
elif format == 'json':
# FIXME: JsonBackend is wrongly taking an ordered dict as basis, not list
dag_unroller = DagUnroller(dag_circuit, JsonBackend(dag_circuit.basis))
compiled_circuit = dag_unroller.execute()
elif format == 'qasm':
compiled_circuit = dag_circuit.qasm()
else:
raise TranspilerError('unrecognized circuit format')
if get_layout:
return compiled_circuit, final_layout
return compiled_circuit
def compile(circuits,
backend,
config=None,
basis_gates=None,
coupling_map=None,
initial_layout=None,
shots=1024,
max_credits=10,
seed=None,
qobj_id=None,
hpc=None,
pass_manager=None):
"""Compile a list of circuits into a qobj.
Args:
circuits (QuantumCircuit or list[QuantumCircuit]): circuits to compile
backend (BaseBackend): a backend to compile for
config (dict): dictionary of parameters (e.g. noise) used by runner
basis_gates (str): comma-separated basis gate set to compile to
coupling_map (list): coupling map (perhaps custom) to target in mapping
initial_layout (list): initial layout of qubits in mapping
shots (int): number of repetitions of each circuit, for sampling
max_credits (int): maximum credits to use
seed (int): random seed for simulators
qobj_id (int): identifier for the generated qobj
hpc (dict): HPC simulator parameters
pass_manager (PassManager): a pass_manager for the transpiler stage
Returns:
obj: the qobj to be run on the backends
Raises:
TranspilerError: in case of bad compile options, e.g. the hpc options.
"""
if isinstance(circuits, QuantumCircuit):
circuits = [circuits]
backend_conf = backend.configuration
backend_name = backend_conf['name']
qobj = {}
# step 1: populate the qobj-level `id`
qobj_id = qobj_id or str(uuid.uuid4())
qobj['id'] = qobj_id
# step 2: populate the qobj-level `config`
qobj['config'] = {
'max_credits': max_credits,
'shots': shots,
'backend_name': backend_name
}
if hpc is not None and \
not all(key in hpc for key in ('multi_shot_optimization', 'omp_num_threads')):
raise TranspilerError('Unknown HPC parameter format!')
# step 3: populate the `circuits` in qobj, after compiling each circuit
qobj['circuits'] = []
if not basis_gates:
basis_gates = backend_conf['basis_gates']
if not coupling_map:
coupling_map = backend_conf['coupling_map']
for circuit in circuits:
job = {}
# step 1: populate the circuit-level `name`
job["name"] = circuit.name
# step 2: populate the circuit-level `config`
if config is None:
config = {}
job["config"] = copy.deepcopy(config)
# TODO: A better solution is to have options to enable/disable optimizations
num_qubits = sum((len(qreg) for qreg in circuit.get_qregs().values()))
if num_qubits == 1 or coupling_map == "all-to-all":
coupling_map = None
job["config"]["coupling_map"] = coupling_map
job["config"]["basis_gates"] = basis_gates
job["config"]["seed"] = seed
# step 3: populate the circuit `instructions` after compilation
# step 3a: circuit -> dag
dag_circuit = DAGCircuit.fromQuantumCircuit(circuit)
# TODO: move this inside the mapper pass
# pick a good initial layout if coupling_map is not already satisfied
# otherwise keep it as q[i]->q[i]
if (initial_layout is None and not backend_conf['simulator']
and not _matches_coupling_map(circuit.data, coupling_map)):
initial_layout = _pick_best_layout(backend, num_qubits,
circuit.get_qregs())
# step 3b: transpile (dag -> dag)
dag_circuit, final_layout = transpile(dag_circuit,
basis_gates=basis_gates,
coupling_map=coupling_map,
initial_layout=initial_layout,
get_layout=True,
seed=seed,
pass_manager=pass_manager)
# step 3c: dag -> json
# TODO: populate the Qobj object when Qobj class exists
# the compiled circuit to be run saved as a dag
# we assume that transpile() has already expanded gates
# to the target basis, so we just need to generate json
list_layout = [[k, v] for k, v in final_layout.items()
] if final_layout else None
job["config"]["layout"] = list_layout
json_circuit = DagUnroller(dag_circuit,
JsonBackend(dag_circuit.basis)).execute()
job["compiled_circuit"] = json_circuit
# set eval_symbols=True to evaluate each symbolic expression
# TODO after transition to qobj, we can drop this
job["compiled_circuit_qasm"] = dag_circuit.qasm(qeflag=True,
eval_symbols=True)
# add job to the qobj
qobj["circuits"].append(job)
return qobj
def compile(circuits,
backend,
config=None,
basis_gates=None,
coupling_map=None,
initial_layout=None,
shots=1024,
max_credits=10,
seed=None,
qobj_id=None,
hpc=None,
pass_manager=None):
"""Compile a list of circuits into a qobj.
Args:
circuits (QuantumCircuit or list[QuantumCircuit]): circuits to compile
backend (BaseBackend): a backend to compile for
config (dict): dictionary of parameters (e.g. noise) used by runner
basis_gates (str): comma-separated basis gate set to compile to
coupling_map (list): coupling map (perhaps custom) to target in mapping
initial_layout (list): initial layout of qubits in mapping
shots (int): number of repetitions of each circuit, for sampling
max_credits (int): maximum credits to use
seed (int): random seed for simulators
qobj_id (int): identifier for the generated qobj
hpc (dict): HPC simulator parameters
pass_manager (PassManager): a pass_manager for the transpiler stage
Returns:
Qobj: the Qobj to be run on the backends
Raises:
TranspilerError: in case of bad compile options, e.g. the hpc options.
"""
if isinstance(circuits, QuantumCircuit):
circuits = [circuits]
backend_conf = backend.configuration
backend_name = backend_conf['name']
# Step 1: create the Qobj, with empty experiments.
# Copy the configuration: the values in `config` have prefern
qobj_config = deepcopy(config or {})
# TODO: "register_slots" is required by the qobj schema in the top-level
# qobj.config. In this implementation, is overridden by the individual
# experiment.config entries (hence the 0 should never be used).
qobj_config.update({
'shots': shots,
'max_credits': max_credits,
'register_slots': 0
})
qobj = Qobj(id=qobj_id or str(uuid.uuid4()),
config=QobjConfig(**qobj_config),
experiments=[],
header=QobjHeader(backend_name=backend_name))
if seed:
qobj.config.seed = seed
# Check for valid parameters for the experiments.
if hpc is not None and \
not all(key in hpc for key in ('multi_shot_optimization', 'omp_num_threads')):
raise TranspilerError('Unknown HPC parameter format!')
basis_gates = basis_gates or backend_conf['basis_gates']
coupling_map = coupling_map or backend_conf['coupling_map']
# Step 2 and 3: transpile and populate the circuits
for circuit in circuits:
# TODO: A better solution is to have options to enable/disable optimizations
num_qubits = sum((len(qreg) for qreg in circuit.get_qregs().values()))
if num_qubits == 1 or coupling_map == "all-to-all":
coupling_map = None
# Step 2a: circuit -> dag
dag_circuit = DAGCircuit.fromQuantumCircuit(circuit)
# TODO: move this inside the mapper pass
# pick a good initial layout if coupling_map is not already satisfied
# otherwise keep it as q[i]->q[i]
if (initial_layout is None and not backend_conf['simulator']
and not _matches_coupling_map(circuit.data, coupling_map)):
initial_layout = _pick_best_layout(backend, num_qubits,
circuit.get_qregs())
# Step 2b: transpile (dag -> dag)
dag_circuit, final_layout = transpile(dag_circuit,
basis_gates=basis_gates,
coupling_map=coupling_map,
initial_layout=initial_layout,
get_layout=True,
seed=seed,
pass_manager=pass_manager)
# Step 2c: dag -> json
# the compiled circuit to be run saved as a dag
# we assume that transpile() has already expanded gates
# to the target basis, so we just need to generate json
list_layout = [[k, v] for k, v in final_layout.items()
] if final_layout else None
json_circuit = DagUnroller(dag_circuit,
JsonBackend(dag_circuit.basis)).execute()
# Step 3a: create the Experiment based on json_circuit
experiment = QobjExperiment.from_dict(json_circuit)
# Step 3b: populate the Experiment configuration and header
experiment.header.name = circuit.name
# TODO: place in header or config?
experiment_config = deepcopy(config or {})
experiment_config.update({
'coupling_map':
coupling_map,
'basis_gates':
basis_gates,
'layout':
list_layout,
'register_slots':
sum(register.size for register in circuit.get_cregs().values())
})
experiment.config = QobjItem(**experiment_config)
# set eval_symbols=True to evaluate each symbolic expression
# TODO after transition to qobj, we can drop this
experiment.header.compiled_circuit_qasm = dag_circuit.qasm(
qeflag=True, eval_symbols=True)
# Step 3c: add the Experiment to the Qobj
qobj.experiments.append(experiment)
return qobj
def compile(circuits,
backend,
config=None,
basis_gates=None,
coupling_map=None,
initial_layout=None,
shots=1024,
max_credits=10,
seed=None,
qobj_id=None,
hpc=None,
pass_manager=None):
"""Compile a list of circuits into a qobj.
Args:
circuits (QuantumCircuit or list[QuantumCircuit]): circuits to compile
backend (BaseBackend): a backend to compile for
config (dict): dictionary of parameters (e.g. noise) used by runner
basis_gates (str): comma-separated basis gate set to compile to
coupling_map (list): coupling map (perhaps custom) to target in mapping
initial_layout (list): initial layout of qubits in mapping
shots (int): number of repetitions of each circuit, for sampling
max_credits (int): maximum credits to use
seed (int): random seed for simulators
qobj_id (int): identifier for the generated qobj
hpc (dict): HPC simulator parameters
pass_manager (PassManager): a pass_manager for the transpiler stage
Returns:
Qobj: the Qobj to be run on the backends
Raises:
TranspilerError: in case of bad compile options, e.g. the hpc options.
"""
if isinstance(circuits, QuantumCircuit):
circuits = [circuits]
backend_conf = backend.configuration
backend_name = backend_conf['name']
# Step 1: create the Qobj, with empty circuits
qobj = Qobj(id=qobj_id or str(uuid.uuid4()),
config=QobjConfig(max_credits=max_credits,
shots=shots,
backend_name=backend_name),
circuits=[])
# Check for valid parameters for the experiments.
if hpc is not None and \
not all(key in hpc for key in ('multi_shot_optimization', 'omp_num_threads')):
raise TranspilerError('Unknown HPC parameter format!')
basis_gates = basis_gates or backend_conf['basis_gates']
coupling_map = coupling_map or backend_conf['coupling_map']
for circuit in circuits:
# Step 1: create the experiment configuration.
config = config or {}
circuit_config = copy.deepcopy(config)
# TODO: A better solution is to have options to enable/disable optimizations
num_qubits = sum((len(qreg) for qreg in circuit.get_qregs().values()))
if num_qubits == 1 or coupling_map == "all-to-all":
coupling_map = None
circuit_config["coupling_map"] = coupling_map
circuit_config["basis_gates"] = basis_gates
circuit_config["seed"] = seed
circuit_config["layout"] = None # set during step 3.
# Step 2: create the QobjExperiment, with empty compiled circuits.
experiment = QobjExperiment(
name=circuit.name,
config=QobjExperimentConfig(**circuit_config),
compiled_circuit=None,
compiled_circuit_qasm=None)
# Step 3: populate the circuit `instructions` after compilation
# Step 3a: circuit -> dag
dag_circuit = DAGCircuit.fromQuantumCircuit(circuit)
# TODO: move this inside the mapper pass
# pick a good initial layout if coupling_map is not already satisfied
# otherwise keep it as q[i]->q[i]
if (initial_layout is None and not backend_conf['simulator']
and not _matches_coupling_map(circuit.data, coupling_map)):
initial_layout = _pick_best_layout(backend, num_qubits,
circuit.get_qregs())
# Step 3b: transpile (dag -> dag)
dag_circuit, final_layout = transpile(dag_circuit,
basis_gates=basis_gates,
coupling_map=coupling_map,
initial_layout=initial_layout,
get_layout=True,
seed=seed,
pass_manager=pass_manager)
# Step 3c: dag -> json
# the compiled circuit to be run saved as a dag
# we assume that transpile() has already expanded gates
# to the target basis, so we just need to generate json
list_layout = [[k, v] for k, v in final_layout.items()
] if final_layout else None
experiment.config.layout = list_layout
json_circuit = DagUnroller(dag_circuit,
JsonBackend(dag_circuit.basis)).execute()
experiment.compiled_circuit = QobjCompiledCircuit.from_dict(
json_circuit)
# set eval_symbols=True to evaluate each symbolic expression
# TODO after transition to qobj, we can drop this
experiment.compiled_circuit_qasm = dag_circuit.qasm(qeflag=True,
eval_symbols=True)
# add job to the qobj
qobj.circuits.append(experiment)
return qobj
