def setUp(self):
qasm_filename = self._get_resource_path('qasm/example.qasm')
qasm_ast = Qasm(filename=qasm_filename).parse()
qasm_dag = Unroller(qasm_ast, DAGBackend()).execute()
qasm_json = DagUnroller(qasm_dag,
JsonBackend(qasm_dag.basis)).execute()
qr = QuantumRegister(2, 'q')
cr = ClassicalRegister(2, 'c')
qc = QuantumCircuit(qr, cr)
qc.h(qr[0])
qc.measure(qr[0], cr[0])
qc_dag = DAGCircuit.fromQuantumCircuit(qc)
qc_json = DagUnroller(qc_dag, JsonBackend(qc_dag.basis)).execute()
# create qobj
compiled_circuit1 = QobjExperiment.from_dict(qc_json)
compiled_circuit2 = QobjExperiment.from_dict(qasm_json)
self.qobj = Qobj(qobj_id='test_qobj',
config=QobjConfig(shots=2000,
memory_slots=1,
max_credits=3,
seed=1111),
experiments=[compiled_circuit1, compiled_circuit2],
header=QobjHeader(backend_name='qasm_simulator'))
self.qobj.experiments[0].header.name = 'test_circuit1'
self.qobj.experiments[1].header.name = 'test_circuit2'
self.backend = QasmSimulator()
def setUp(self):
self.seed = 88
self.qasm_filename = self._get_resource_path('qasm/example.qasm')
self.qasm_circ = QuantumCircuit.from_qasm_file(self.qasm_filename)
qr = QuantumRegister(2, 'q')
cr = ClassicalRegister(2, 'c')
qc = QuantumCircuit(qr, cr)
qc.h(qr[0])
qc.measure(qr[0], cr[0])
self.qc = qc
# create qobj
dag = DAGCircuit.fromQuantumCircuit(self.qc)
json_circuit = DagUnroller(dag, JsonBackend(dag.basis)).execute()
compiled_circuit1 = QobjExperiment.from_dict(json_circuit)
dag = DAGCircuit.fromQuantumCircuit(self.qasm_circ)
json_circuit = DagUnroller(dag, JsonBackend(dag.basis)).execute()
compiled_circuit2 = QobjExperiment.from_dict(json_circuit)
self.qobj = Qobj(qobj_id='test_qobj',
config=QobjConfig(shots=2000,
memory_slots=1,
max_credits=3,
seed=1111),
experiments=[compiled_circuit1, compiled_circuit2],
header=QobjHeader(backend_name='qasm_simulator'))
self.qobj.experiments[0].header.name = 'test_circuit1'
self.qobj.experiments[0].config = QobjItem(
basis_gates='u1,u2,u3,cx,id')
self.qobj.experiments[1].header.name = 'test_circuit2'
self.qobj.experiments[1].config = QobjItem(
basis_gates='u1,u2,u3,cx,id')
self.backend = QasmSimulator()
def test_from_dag_to_json_with_basis(self):
ast = qasm.Qasm(
filename=self._get_resource_path('qasm/example.qasm')).parse()
dag_circuit = Unroller(ast, DAGBackend(["cx", "u1", "u2",
"u3"])).execute()
dag_unroller = DagUnroller(dag_circuit,
JsonBackend(["cx", "u1", "u2", "u3"]))
json_circuit = dag_unroller.execute()
expected_result = \
{'operations':
[{'qubits': [5], 'texparams': ['0', '\\pi'], 'params': [0.0, 3.141592653589793],
'name': 'u2'},
{'qubits': [5, 2], 'texparams': [], 'params': [], 'name': 'cx'},
{'qubits': [2], 'clbits': [2], 'name': 'measure'},
{'qubits': [4], 'texparams': ['0', '\\pi'], 'params': [0.0, 3.141592653589793],
'name': 'u2'},
{'qubits': [4, 1], 'texparams': [], 'params': [], 'name': 'cx'},
{'qubits': [1], 'clbits': [1], 'name': 'measure'},
{'qubits': [3], 'texparams': ['0', '\\pi'], 'params': [0.0, 3.141592653589793],
'name': 'u2'},
{'qubits': [3, 0], 'texparams': [], 'params': [], 'name': 'cx'},
{'qubits': [3, 4, 5], 'name': 'barrier'},
{'qubits': [5], 'clbits': [5], 'name': 'measure'},
{'qubits': [4], 'clbits': [4], 'name': 'measure'},
{'qubits': [3], 'clbits': [3], 'name': 'measure'},
{'qubits': [0], 'clbits': [0], 'name': 'measure'}],
'header':
{'clbit_labels': [['d', 3], ['c', 3]],
'number_of_qubits': 6,
'qubit_labels': [['r', 0], ['r', 1], ['r', 2], ['q', 0], ['q', 1], ['q', 2]],
'number_of_clbits': 6
}
}
self.assertEqual(json_circuit, expected_result)
def test_dag_to_json(self):
"""Test DagUnroller with JSON backend."""
ast = qasm.Qasm(filename=self._get_resource_path('qasm/example.qasm')).parse()
dag_circuit = Unroller(ast, DAGBackend()).execute()
dag_unroller = DagUnroller(dag_circuit, JsonBackend())
json_circuit = dag_unroller.execute()
expected_result = {
'operations':
[
{'qubits': [5], 'texparams': ['0.5 \\pi', '0', '\\pi'],
'name': 'U', 'params': [1.5707963267948966, 0.0, 3.141592653589793]},
{'name': 'CX', 'qubits': [5, 2]},
{'clbits': [2], 'name': 'measure', 'qubits': [2]},
{'qubits': [4], 'texparams': ['0.5 \\pi', '0', '\\pi'], 'name': 'U',
'params': [1.5707963267948966, 0.0, 3.141592653589793]},
{'name': 'CX', 'qubits': [4, 1]},
{'clbits': [1], 'name': 'measure', 'qubits': [1]},
{'qubits': [3], 'texparams': ['0.5 \\pi', '0', '\\pi'], 'name': 'U',
'params': [1.5707963267948966, 0.0, 3.141592653589793]},
{'name': 'CX', 'qubits': [3, 0]},
{'name': 'barrier', 'qubits': [3, 4, 5]},
{'clbits': [5], 'name': 'measure', 'qubits': [5]},
{'clbits': [4], 'name': 'measure', 'qubits': [4]},
{'clbits': [3], 'name': 'measure', 'qubits': [3]},
{'clbits': [0], 'name': 'measure', 'qubits': [0]}
],
'header':
{
'memory_slots': 6,
'qubit_labels': [['r', 0], ['r', 1], ['r', 2], ['q', 0], ['q', 1], ['q', 2]],
'n_qubits': 6, 'clbit_labels': [['d', 3], ['c', 3]]
}
}
self.assertEqual(json_circuit, expected_result)
def _dags_2_qobj_parallel(dag, config=None, basis_gates=None,
coupling_map=None):
"""Helper function for dags to qobj in parallel (if available).
Args:
dag (DAGCircuit): DAG to compile
config (dict): dictionary of parameters (e.g. noise) used by runner
basis_gates (list[str])): basis gates for the experiment
coupling_map (list): coupling map (perhaps custom) to target in mapping
Returns:
Qobj: Qobj to be run on the backends
"""
json_circuit = DagUnroller(dag, JsonBackend(dag.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 = dag.name
# TODO: place in header or config?
experiment_config = deepcopy(config or {})
experiment_config.update({
'coupling_map': coupling_map,
'basis_gates': basis_gates,
'layout': dag.layout,
'memory_slots': sum(dag.cregs.values()),
# TODO: `n_qubits` is not part of the qobj spec, but needed for the simulator.
'n_qubits': sum(dag.qregs.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.qasm(
qeflag=True, eval_symbols=True)
# Step 3c: add the Experiment to the Qobj
return experiment
def test_pass_manager_none(self):
"""Test passing the default (None) pass manager to the transpiler.
It should perform the default qiskit flow:
unroll, swap_mapper, direction_mapper, cx cancellation, optimize_1q_gates
and should be equivalent to using wrapper.compile
"""
q = QuantumRegister(2)
circ = QuantumCircuit(q)
circ.h(q[0])
circ.h(q[0])
circ.cx(q[0], q[1])
circ.cx(q[0], q[1])
circ.cx(q[0], q[1])
circ.cx(q[0], q[1])
coupling_map = [[1, 0]]
basis_gates = 'u1,u2,u3,cx,id'
dag_circuit = DAGCircuit.fromQuantumCircuit(circ)
dag_circuit = transpile(dag_circuit, coupling_map=coupling_map,
basis_gates=basis_gates, pass_manager=None)
transpiler_json = DagUnroller(dag_circuit, JsonBackend(dag_circuit.basis)).execute()
qobj = wrapper.compile(circ, backend='local_qasm_simulator',
coupling_map=coupling_map, basis_gates=basis_gates)
compiler_json = qobj.experiments[0].as_dict()
# Remove extra Qobj header parameters.
compiler_json.pop('config')
compiler_json['header'].pop('name')
compiler_json['header'].pop('compiled_circuit_qasm')
self.assertDictEqual(transpiler_json, compiler_json)
def _create_qobj(self, circuits, circuit_config, backend, seed,
resources, shots, do_compile):
# local and remote backends currently need different
# compilied circuit formats
formatted_circuits = []
if do_compile:
for circuit in circuits:
formatted_circuits.append(None)
else:
if backend in backends.local_backends():
for circuit in self.circuits:
basis = ['u1', 'u2', 'u3', 'cx', 'id']
unroller = Unroller
# TODO: No instanceof here! Refactor this class
if isinstance(circuit, DAGCircuit):
unroller = DagUnroller
elif isinstance(circuit, QuantumCircuit):
# TODO: We should remove this code path (it's redundant and slow)
circuit = Qasm(data=circuit.qasm()).parse()
unroller_instance = unroller(circuit, JsonBackend(basis))
compiled_circuit = unroller_instance.execute()
formatted_circuits.append(compiled_circuit)
else:
for circuit in self.circuits:
formatted_circuits.append(circuit.qasm(qeflag=True))
# create circuit component of qobj
circuit_records = []
if circuit_config is None:
config = {'coupling_map': None,
'basis_gates': 'u1,u2,u3,cx,id',
'layout': None,
'seed': seed}
circuit_config = [config] * len(self.circuits)
for circuit, fcircuit, name, config in zip(self.circuits,
formatted_circuits,
self.names,
circuit_config):
record = {
'name': name,
'compiled_circuit': None if do_compile else fcircuit,
'compiled_circuit_qasm': None if do_compile else fcircuit,
'circuit': circuit,
'config': config
}
circuit_records.append(record)
return {'id': self._generate_job_id(length=10),
'config': {
'max_credits': resources['max_credits'],
'shots': shots,
'backend': backend
},
'circuits': circuit_records}
def dag2json(dag_circuit, basis_gates='u1,u2,u3,cx,id'):
"""Make a Json representation of the circuit.
Takes a circuit dag and returns json circuit obj. This is an internal
function.
Args:
dag_circuit (QuantumCircuit): a dag representation of the circuit.
basis_gates (str): a comma seperated string and are the base gates,
which by default are: u1,u2,u3,cx,id
Returns:
json: the json version of the dag
"""
return DagUnroller(dag_circuit, JsonBackend(basis_gates)).execute()
def setUp(self):
self.seed = 88
self.backend = QasmSimulatorPy()
backend_basis = self.backend.configuration().basis_gates
qasm_filename = self._get_resource_path('qasm/example.qasm')
qasm_ast = Qasm(filename=qasm_filename).parse()
qasm_dag = Unroller(qasm_ast, DAGBackend()).execute()
qasm_dag = DagUnroller(qasm_dag, DAGBackend(backend_basis)).expand_gates()
qasm_json = DagUnroller(qasm_dag, JsonBackend(qasm_dag.basis)).execute()
compiled_circuit = QobjExperiment.from_dict(qasm_json)
compiled_circuit.header.name = 'test'
self.qobj = Qobj(
qobj_id='test_sim_single_shot',
config=QobjConfig(
shots=1024, memory_slots=6,
max_credits=3, seed=self.seed
),
experiments=[compiled_circuit],
header=QobjHeader(backend_name='qasm_simulator_py')
)
def _circuit_to_experiment(circuit,
config=None,
basis_gates=None,
coupling_map=None):
"""Helper function for dags to qobj in parallel (if available).
Args:
circuit (QuantumCircuit): QuantumCircuit to convert into qobj experiment
config (dict): dictionary of parameters (e.g. noise) used by runner
basis_gates (list[str])): basis gates for the experiment
coupling_map (list): coupling map (perhaps custom) to target in mapping
Returns:
Qobj: Qobj to be run on the backends
"""
# pylint: disable=unused-argument
# TODO: if arguments are really unused, consider changing the signature
# TODO: removed the DAG from this function
from qiskit.converters import circuit_to_dag
from qiskit.unroll import DagUnroller, JsonBackend
dag = circuit_to_dag(circuit)
json_circuit = DagUnroller(dag, JsonBackend(dag.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
experiment_config = deepcopy(config or {})
experiment_config.update({
'memory_slots':
sum([creg.size for creg in dag.cregs.values()]),
'n_qubits':
sum([qreg.size for qreg in dag.qregs.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 = circuit.qasm()
# Step 3c: add the Experiment to the Qobj
return experiment
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_single_circuit(circuit,
backend,
config=None,
basis_gates=None,
coupling_map=None,
initial_layout=None,
seed=None,
pass_manager=None):
"""Compile a single circuit into a QobjExperiment.
Args:
circuit (QuantumCircuit): circuit 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
seed (int): random seed for simulators
pass_manager (PassManager): a pass_manager for the transpiler stage
Returns:
QobjExperiment: the QobjExperiment to be run on the backends
"""
# 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.configuration['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,
'memory_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)
return experiment
def compile(quantum_circuit, basis_gates='u1,u2,u3,cx,id', coupling_map=None,
initial_layout=None, get_layout=False, format='dag'):
"""Compile the circuit.
This builds the internal "to execute" list which is list of quantum
circuits to run on different backends.
Args:
quantum_circuit (QuantumCircuit): circuit to compile
basis_gates (str): a comma seperated string and are the base gates,
which by default are: u1,u2,u3,cx,id
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'}
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:
QISKitCompilerError: if the format is not valid.
"""
compiled_dag_circuit = DAGCircuit.fromQuantumCircuit(quantum_circuit)
basis = basis_gates.split(',') if basis_gates else []
dag_unroller = DagUnroller(compiled_dag_circuit, DAGBackend(basis))
compiled_dag_circuit = dag_unroller.expand_gates()
final_layout = None
# if a coupling map is given compile to the map
if coupling_map:
logger.info("pre-mapping properties: %s",
compiled_dag_circuit.property_summary())
# Insert swap gates
coupling = mapper.Coupling(mapper.coupling_list2dict(coupling_map))
logger.info("initial layout: %s", initial_layout)
compiled_dag_circuit, final_layout = mapper.swap_mapper(
compiled_dag_circuit, coupling, initial_layout, trials=20, seed=13)
logger.info("final layout: %s", final_layout)
# Expand swaps
dag_unroller = DagUnroller(compiled_dag_circuit, DAGBackend(basis))
compiled_dag_circuit = dag_unroller.expand_gates()
# Change cx directions
compiled_dag_circuit = mapper.direction_mapper(compiled_dag_circuit, coupling)
# Simplify cx gates
mapper.cx_cancellation(compiled_dag_circuit)
# Simplify single qubit gates
compiled_dag_circuit = mapper.optimize_1q_gates(compiled_dag_circuit)
logger.info("post-mapping properties: %s",
compiled_dag_circuit.property_summary())
# choose output format
if format == 'dag':
compiled_circuit = compiled_dag_circuit
elif format == 'json':
dag_unroller = DagUnroller(compiled_dag_circuit,
JsonBackend(list(compiled_dag_circuit.basis.keys())))
compiled_circuit = dag_unroller.execute()
elif format == 'qasm':
compiled_circuit = compiled_dag_circuit.qasm()
else:
raise QISKitCompilerError('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 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 _dags_2_qobj(dags,
backend_name,
config=None,
shots=None,
max_credits=None,
qobj_id=None,
basis_gates=None,
coupling_map=None,
seed=None):
"""Convert a list of dags into a qobj.
Args:
dags (list[DAGCircuit]): dags to compile
backend_name (str): name of runner backend
config (dict): dictionary of parameters (e.g. noise) used by runner
shots (int): number of repetitions of each circuit, for sampling
max_credits (int): maximum credits to use
qobj_id (int): identifier for the generated qobj
basis_gates (list[str])): basis gates for the experiment
coupling_map (list): coupling map (perhaps custom) to target in mapping
seed (int): random seed for simulators
Returns:
Qobj: the Qobj to be run on the backends
"""
# TODO: the following will be removed from qobj and thus removed here:
# `basis_gates`, `coupling_map`
# Step 1: create the Qobj, with empty experiments.
# Copy the configuration: the values in `config` have preference
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(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
for dag in dags:
json_circuit = DagUnroller(dag, JsonBackend(dag.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 = dag.name
# TODO: place in header or config?
experiment_config = deepcopy(config or {})
experiment_config.update({
'coupling_map': coupling_map,
'basis_gates': basis_gates,
'layout': dag.layout,
'memory_slots': sum(dag.cregs.values()),
# TODO: `n_qubits` is not part of the qobj spec, but needed for the simulator.
'n_qubits': sum(dag.qregs.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.qasm(qeflag=True,
eval_symbols=True)
# 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)
# Update the `n_qubits` global value.
# TODO: num_qubits is not part of the qobj specification, but needed
# for the simulator.
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 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