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 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 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