def run_sweep(
self,
program: 'cirq.Circuit',
program_id: Optional[str] = None,
job_id: Optional[str] = None,
params: study.Sweepable = None,
repetitions: int = 1,
processor_ids: Sequence[str] = ('xmonsim',),
gate_set: Optional[sgs.SerializableGateSet] = None,
program_description: Optional[str] = None,
program_labels: Optional[Dict[str, str]] = None,
job_description: Optional[str] = None,
job_labels: Optional[Dict[str, str]] = None,
) -> engine_job.EngineJob:
"""Runs the supplied Circuit via Quantum Engine.Creates
In contrast to run, this runs across multiple parameter sweeps, and
does not block until a result is returned.
Args:
program: The Circuit to execute. If a circuit is
provided, a moment by moment schedule will be used.
program_id: A user-provided identifier for the program. This must
be unique within the Google Cloud project being used. If this
parameter is not provided, a random id of the format
'prog-################YYMMDD' will be generated, where # is
alphanumeric and YYMMDD is the current year, month, and day.
job_id: Job identifier to use. If this is not provided, a random id
of the format 'job-################YYMMDD' will be generated,
where # is alphanumeric and YYMMDD is the current year, month,
and day.
params: Parameters to run with the program.
repetitions: The number of circuit repetitions to run.
processor_ids: The engine processors that should be candidates
to run the program. Only one of these will be scheduled for
execution.
gate_set: The gate set used to serialize the circuit. The gate set
must be supported by the selected processor.
program_description: An optional description to set on the program.
program_labels: Optional set of labels to set on the program.
job_description: An optional description to set on the job.
job_labels: Optional set of labels to set on the job.
Returns:
An EngineJob. If this is iterated over it returns a list of
TrialResults, one for each parameter sweep.
"""
if not gate_set:
raise ValueError('No gate set provided')
engine_program = self.create_program(
program, program_id, gate_set, program_description, program_labels
)
return engine_program.run_sweep(
job_id=job_id,
params=params,
repetitions=repetitions,
processor_ids=processor_ids,
description=job_description,
labels=job_labels,
)
def run_sweep(
self,
*, # Force keyword args.
program: 'cirq.Circuit',
program_id: Optional[str] = None,
job_config: Optional[JobConfig] = None,
params: study.Sweepable = None,
repetitions: int = 1,
priority: int = 500,
processor_ids: Sequence[str] = ('xmonsim', ),
gate_set: serializable_gate_set.SerializableGateSet = None
) -> engine_job.EngineJob:
"""Runs the supplied Circuit via Quantum Engine.
In contrast to run, this runs across multiple parameter sweeps, and
does not block until a result is returned.
Args:
program: The Circuit to execute. If a circuit is
provided, a moment by moment schedule will be used.
program_id: A user-provided identifier for the program. This must
be unique within the Google Cloud project being used. If this
parameter is not provided, a random id of the format
'prog-################YYMMDD' will be generated, where # is
alphanumeric and YYMMDD is the current year, month, and day.
job_config: Configures the names and properties of jobs.
params: Parameters to run with the program.
repetitions: The number of circuit repetitions to run.
priority: The priority to run at, 0-100.
processor_ids: The engine processors that should be candidates
to run the program. Only one of these will be scheduled for
execution.
Returns:
An EngineJob. If this is iterated over it returns a list of
TrialResults, one for each parameter sweep.
"""
gate_set = gate_set or gate_sets.XMON
engine_program = self.create_program(program, program_id, gate_set)
return engine_program.run_sweep(job_config=job_config,
params=params,
repetitions=repetitions,
priority=priority,
processor_ids=processor_ids)
