User-requested configuration of how to execute a given cg.QuantumExecutableGroup
.
cirq_google.workflow.QuantumRuntimeConfiguration(
processor_record: 'cg.ProcessorRecord',
run_id: Optional[str] = None,
random_seed: Optional[int] = None,
qubit_placer: cirq_google.workflow.QubitPlacer
= NaiveQubitPlacer()
,
target_gateset: Optional[cirq.CompilationTargetGateset] = None
)
Args |
processor
|
The cg.AbstractEngineProcessor responsible for running circuits and providing
device information.
|
run_id
|
A unique str identifier for a run. If data already exists for the specified
run_id , an exception will be raised. If not specified, we will generate a UUID4
run identifier.
|
random_seed
|
An initial seed to make the run deterministic. Otherwise, the default numpy
seed will be used.
|
qubit_placer
|
A cg.QubitPlacer implementation to map executable qubits to device qubits.
The placer is only called if a given cg.QuantumExecutable has a problem_topology .
This subroutine's runtime is keyed by "placement" in RuntimeInfo.timings_s .
|
target_gateset
|
If not None , compile all circuits to this target gateset prior to
execution with cirq.optimize_for_target_gateset .
|
Attributes |
processor_record
|
Dataclass field
|
run_id
|
Dataclass field
|
random_seed
|
Dataclass field
|
qubit_placer
|
Dataclass field
|
target_gateset
|
Dataclass field
|
Methods
__eq__
__eq__(
other
)
Return self==value.