def build_algorithm_from_dict(params, algo_input=None, backend=None):
"""
Construct algorithm as named in params, using params and algo_input as input data
and returning a QuantumAlgorithm and QuantumInstance instance
Args:
params (dict): Dictionary of params for algo and dependent objects
algo_input (AlgorithmInput): Main input data for algorithm. Optional, an algo may run entirely from params
backend (BaseBackend): Backend object to be used in place of backend name
Returns:
Ready-to-run QuantumAlgorithm and QuantumInstance as specified in input parameters. Note that
no QuantumInstance will be returned if none is specified - None will be returned instead.
"""
_discover_on_demand()
inputparser = InputParser(params)
inputparser.parse()
# before merging defaults attempts to find a provider for the backend in case no
# provider was passed
if backend is None and inputparser.get_section_property(
JSONSchema.BACKEND, JSONSchema.PROVIDER) is None:
backend_name = inputparser.get_section_property(
JSONSchema.BACKEND, JSONSchema.NAME)
if backend_name is not None:
inputparser.set_section_property(
JSONSchema.BACKEND, JSONSchema.PROVIDER,
get_provider_from_backend(backend_name))
inputparser.validate_merge_defaults()
logger.debug('Algorithm Input: {}'.format(
json.dumps(inputparser.get_sections(), sort_keys=True, indent=4)))
algo_name = inputparser.get_section_property(PluggableType.ALGORITHM.value,
JSONSchema.NAME)
if algo_name is None:
raise AquaError('Missing algorithm name')
if algo_name not in local_pluggables(PluggableType.ALGORITHM):
raise AquaError(
'Algorithm "{0}" missing in local algorithms'.format(algo_name))
if algo_input is None:
input_name = inputparser.get_section_property('input', JSONSchema.NAME)
if input_name is not None:
input_params = copy.deepcopy(
inputparser.get_section_properties('input'))
del input_params[JSONSchema.NAME]
convert_json_to_dict(input_params)
algo_input = get_pluggable_class(
PluggableType.INPUT, input_name).from_params(input_params)
algo_params = copy.deepcopy(inputparser.get_sections())
algorithm = get_pluggable_class(PluggableType.ALGORITHM,
algo_name).init_params(
algo_params, algo_input)
random_seed = inputparser.get_section_property(JSONSchema.PROBLEM,
'random_seed')
algorithm.random_seed = random_seed
quantum_instance = None
# setup backend
backend_provider = inputparser.get_section_property(
JSONSchema.BACKEND, JSONSchema.PROVIDER)
backend_name = inputparser.get_section_property(JSONSchema.BACKEND,
JSONSchema.NAME)
if backend_provider is not None and backend_name is not None: # quantum algorithm
backend_cfg = {
k: v
for k, v in inputparser.get_section(JSONSchema.BACKEND).items()
if k not in [JSONSchema.PROVIDER, JSONSchema.NAME]
}
# TODO, how to build the noise model from a dictionary?
backend_cfg['seed_mapper'] = random_seed
pass_manager = PassManager() if backend_cfg.pop(
'skip_transpiler', False) else None
if pass_manager is not None:
backend_cfg['pass_manager'] = pass_manager
if backend is None or not isinstance(backend, BaseBackend):
backend = get_backend_from_provider(backend_provider, backend_name)
backend_cfg['backend'] = backend
# overwrite the basis_gates and coupling_map
basis_gates = backend_cfg.pop('basis_gates', None)
coupling_map = backend_cfg.pop('coupling_map', None)
if backend.configuration().simulator:
if basis_gates is not None:
backend.configuration().basis_gates = basis_gates
if coupling_map is not None:
backend.configuration().coupling_map = coupling_map
else:
logger.warning(
"Change basis_gates and coupling_map on a real device is disallowed."
)
shots = backend_cfg.pop('shots', 1024)
seed = random_seed
max_credits = backend_cfg.pop('max_credits', 10)
memory = backend_cfg.pop('memory', False)
run_config = RunConfig(shots=shots,
max_credits=max_credits,
memory=memory)
if seed is not None:
run_config.seed = seed
backend_cfg['run_config'] = run_config
backend_cfg['skip_qobj_validation'] = inputparser.get_section_property(
JSONSchema.PROBLEM, 'skip_qobj_validation')
use_caching = inputparser.get_section_property(JSONSchema.PROBLEM,
'circuit_caching')
if use_caching:
deepcopy_qobj = inputparser.get_section_property(
JSONSchema.PROBLEM, 'skip_qobj_deepcopy')
cache_file = inputparser.get_section_property(
JSONSchema.PROBLEM, 'circuit_cache_file')
backend_cfg['circuit_cache'] = CircuitCache(
skip_qobj_deepcopy=deepcopy_qobj, cache_file=cache_file)
quantum_instance = QuantumInstance(**backend_cfg)
# Note that quantum_instance can be None if none is specified
return algorithm, quantum_instance
def __init__(self,
backend,
shots=1024,
seed=None,
max_credits=10,
basis_gates=None,
coupling_map=None,
initial_layout=None,
pass_manager=None,
seed_mapper=None,
backend_options=None,
noise_model=None,
timeout=None,
wait=5,
circuit_cache=None,
skip_qobj_validation=False):
"""Constructor.
Args:
backend (BaseBackend): instance of selected backend
shots (int, optional): number of repetitions of each circuit, for sampling
seed (int, optional): random seed for simulators
max_credits (int, optional): maximum credits to use
basis_gates (list[str], optional): list of basis gate names supported by the
target. Default: ['u1','u2','u3','cx','id']
coupling_map (list[list]): coupling map (perhaps custom) to target in mapping
initial_layout (dict, optional): initial layout of qubits in mapping
pass_manager (PassManager, optional): pass manager to handle how to compile the circuits
seed_mapper (int, optional): the random seed for circuit mapper
backend_options (dict, optional): all running options for backend, please refer to the provider.
noise_model (qiskit.provider.aer.noise.noise_model.NoiseModel, optional): noise model for simulator
timeout (float, optional): seconds to wait for job. If None, wait indefinitely.
wait (float, optional): seconds between queries to result
circuit_cache (CircuitCache, optional): A CircuitCache to use when calling compile_and_run_circuits
skip_qobj_validation (bool, optional): Bypass Qobj validation to decrease submission time
"""
self._backend = backend
# setup run config
run_config = RunConfig(shots=shots, max_credits=max_credits)
if seed:
run_config.seed = seed
if getattr(run_config, 'shots', None) is not None:
if self.is_statevector and run_config.shots != 1:
logger.info(
"statevector backend only works with shot=1, change "
"shots from {} to 1.".format(run_config.shots))
run_config.shots = 1
self._run_config = run_config
# setup backend config
basis_gates = basis_gates or backend.configuration().basis_gates
coupling_map = coupling_map or getattr(backend.configuration(),
'coupling_map', None)
self._backend_config = {
'basis_gates': basis_gates,
'coupling_map': coupling_map
}
# setup noise config
noise_config = None
if noise_model is not None:
if is_aer_provider(self._backend):
if not self.is_statevector:
noise_config = noise_model
else:
logger.info(
"The noise model can be only used with Aer qasm simulator. "
"Change it to None.")
else:
logger.info(
"The noise model can be only used with Qiskit Aer. "
"Please install it.")
self._noise_config = {} if noise_config is None else {
'noise_model': noise_config
}
# setup compile config
if initial_layout is not None and not isinstance(
initial_layout, Layout):
initial_layout = Layout(initial_layout)
self._compile_config = {
'pass_manager': pass_manager,
'initial_layout': initial_layout,
'seed_mapper': seed_mapper
}
# setup job config
self._qjob_config = {'timeout': timeout} if self.is_local \
else {'timeout': timeout, 'wait': wait}
# setup backend options for run
self._backend_options = {}
if is_ibmq_provider(self._backend):
logger.info(
"backend_options can not used with the backends in IBMQ provider."
)
else:
self._backend_options = {} if backend_options is None \
else {'backend_options': backend_options}
self._shared_circuits = False
self._circuit_summary = False
self._circuit_cache = circuit_cache
self._skip_qobj_validation = skip_qobj_validation
logger.info(self)
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,
seed_mapper=None,
pass_manager=None,
memory=False):
"""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
seed_mapper (int): random seed for swapper mapper
qobj_id (int): identifier for the generated qobj
pass_manager (PassManager): a pass manger for the transpiler pipeline
memory (bool): if True, per-shot measurement bitstrings are returned as well
Returns:
Qobj: the qobj to be run on the backends
Raises:
QiskitError: if the desired options are not supported by backend
"""
if config:
warnings.warn(
'The `config` argument is deprecated and '
'does not do anything', DeprecationWarning)
circuits = transpiler.transpile(circuits, backend, basis_gates,
coupling_map, initial_layout, seed_mapper,
pass_manager)
# step 4: Making a qobj
run_config = RunConfig()
if seed:
run_config.seed = seed
if shots:
run_config.shots = shots
if max_credits:
run_config.max_credits = max_credits
if memory:
run_config.memory = memory
qobj = circuits_to_qobj(circuits,
user_qobj_header=QobjHeader(),
run_config=run_config,
qobj_id=qobj_id)
return qobj
def _build_algorithm_from_dict(self, quantum_instance):
_discover_on_demand()
self._parser = InputParser(self._params)
self._parser.parse()
# before merging defaults attempts to find a provider for the backend in case no
# provider was passed
if quantum_instance is None and self._parser.get_section_property(
JSONSchema.BACKEND, JSONSchema.PROVIDER) is None:
backend_name = self._parser.get_section_property(
JSONSchema.BACKEND, JSONSchema.NAME)
if backend_name is not None:
self._parser.set_section_property(
JSONSchema.BACKEND, JSONSchema.PROVIDER,
get_provider_from_backend(backend_name))
self._parser.validate_merge_defaults()
logger.debug('Algorithm Input: {}'.format(
json.dumps(self._parser.get_sections(), sort_keys=True, indent=4)))
algo_name = self._parser.get_section_property(
PluggableType.ALGORITHM.value, JSONSchema.NAME)
if algo_name is None:
raise AquaError('Missing algorithm name')
if algo_name not in local_pluggables(PluggableType.ALGORITHM):
raise AquaError(
'Algorithm "{0}" missing in local algorithms'.format(
algo_name))
if self._algorithm_input is None:
input_name = self._parser.get_section_property(
'input', JSONSchema.NAME)
if input_name is not None:
input_params = copy.deepcopy(
self._parser.get_section_properties('input'))
del input_params[JSONSchema.NAME]
convert_json_to_dict(input_params)
self._algorithm_input = get_pluggable_class(
PluggableType.INPUT, input_name).from_params(input_params)
algo_params = copy.deepcopy(self._parser.get_sections())
self._quantum_algorithm = get_pluggable_class(
PluggableType.ALGORITHM,
algo_name).init_params(algo_params, self._algorithm_input)
random_seed = self._parser.get_section_property(
JSONSchema.PROBLEM, 'random_seed')
self._quantum_algorithm.random_seed = random_seed
if isinstance(quantum_instance, QuantumInstance):
self._quantum_instance = quantum_instance
return
backend = None
if isinstance(quantum_instance, BaseBackend):
backend = quantum_instance
elif quantum_instance is not None:
raise AquaError(
'Invalid QuantumInstance or BaseBackend parameter {}.'.format(
quantum_instance))
# setup backend
backend_provider = self._parser.get_section_property(
JSONSchema.BACKEND, JSONSchema.PROVIDER)
backend_name = self._parser.get_section_property(
JSONSchema.BACKEND, JSONSchema.NAME)
if backend_provider is not None and backend_name is not None: # quantum algorithm
backend_cfg = {
k: v
for k, v in self._parser.get_section(
JSONSchema.BACKEND).items()
if k not in [JSONSchema.PROVIDER, JSONSchema.NAME]
}
# TODO, how to build the noise model from a dictionary?
backend_cfg['seed_mapper'] = random_seed
pass_manager = PassManager() if backend_cfg.pop(
'skip_transpiler', False) else None
if pass_manager is not None:
backend_cfg['pass_manager'] = pass_manager
if backend is None:
backend = get_backend_from_provider(backend_provider,
backend_name)
backend_cfg['backend'] = backend
# overwrite the basis_gates and coupling_map
basis_gates = backend_cfg.pop('basis_gates', None)
if isinstance(basis_gates, str):
basis_gates = basis_gates.split(',')
coupling_map = backend_cfg.pop('coupling_map', None)
if backend.configuration().simulator:
if basis_gates is not None:
backend.configuration().basis_gates = basis_gates
if coupling_map is not None:
backend.configuration().coupling_map = coupling_map
else:
logger.warning(
"Change basis_gates and coupling_map on a real device is disallowed."
)
shots = backend_cfg.pop('shots', 1024)
seed = random_seed
max_credits = backend_cfg.pop('max_credits', 10)
memory = backend_cfg.pop('memory', False)
run_config = RunConfig(shots=shots,
max_credits=max_credits,
memory=memory)
if seed is not None:
run_config.seed = seed
backend_cfg['run_config'] = run_config
backend_cfg[
'skip_qobj_validation'] = self._parser.get_section_property(
JSONSchema.PROBLEM, 'skip_qobj_validation')
use_caching = self._parser.get_section_property(
JSONSchema.PROBLEM, 'circuit_caching')
if use_caching:
deepcopy_qobj = self._parser.get_section_property(
JSONSchema.PROBLEM, 'skip_qobj_deepcopy')
cache_file = self._parser.get_section_property(
JSONSchema.PROBLEM, 'circuit_cache_file')
backend_cfg['circuit_cache'] = CircuitCache(
skip_qobj_deepcopy=deepcopy_qobj, cache_file=cache_file)
self._quantum_instance = QuantumInstance(**backend_cfg)