def calibration_results(self):
"""Returns the results of a run_calibration() call.
This function will fail if any other type of results were returned
by the Engine.
"""
import cirq.google.engine.engine as engine_base
if not self._calibration_results:
result = self._wait_for_result()
result_type = result.type_url[len(engine_base.TYPE_PREFIX):]
if result_type != 'cirq.google.api.v2.FocusedCalibrationResult':
raise ValueError(
f'Did not find calibration results, instead found: {result_type}'
)
parsed_val = v2.calibration_pb2.FocusedCalibrationResult.FromString(
result.value)
cal_results = []
for layer in parsed_val.results:
metrics = calibration.Calibration(layer.metrics)
message = layer.error_message or None
token = layer.token or None
if layer.valid_until_ms > 0:
ts = datetime.datetime.fromtimestamp(layer.valid_until_ms /
1000)
else:
ts = None
cal_results.append(
CalibrationResult(layer.code, message, token, ts, metrics))
self._calibration_results = cal_results
return self._calibration_results
def get_calibration(self) -> Optional[calibration.Calibration]:
"""Returns the recorded calibration at the time when the job was run, if
one was captured, else None."""
status = self._inner_job().execution_status
if not status.calibration_name:
return None
ids = self.context.client._ids_from_calibration_name(
status.calibration_name)
response = self.context.client.get_calibration(*ids)
metrics = v2.metrics_pb2.MetricsSnapshot.FromString(response.data.value)
return calibration.Calibration(metrics)
def get_calibration(self, calibration_name: str) -> calibration.Calibration:
"""Retrieve metadata about a specific calibration run.
Params:
calibration_name: A string of the form
`<processor name>/calibrations/<ms since epoch>`
Returns:
A dictionary containing the metadata.
"""
response = self.service.projects().processors().calibrations().get(
name=calibration_name).execute()
return calibration.Calibration(response['data']['data'])
def get_calibration(self, calibration_name: str) -> calibration.Calibration:
"""Retrieve metadata about a specific calibration run.
Params:
calibration_name: A string of the form
`projects/<project_id>/processors/<processor id>`
`/calibrations/<timestamp in seconds since epoch>`
Returns:
A dictionary containing the metadata.
"""
response = self._make_request(
self.service.projects().processors().calibrations().get(
name=calibration_name))
return calibration.Calibration(response['data'])
def get_calibration(self, calibration_name: str) -> calibration.Calibration:
"""Retrieve metadata about a specific calibration run.
Params:
calibration_name: A string of the form
`projects/<project_id>/processors/<processor id>`
`/calibrations/<timestamp in seconds since epoch>`
Returns:
A dictionary containing the metadata.
"""
response = self._make_request(lambda: self.client.
get_quantum_calibration(calibration_name))
metrics = v2.metrics_pb2.MetricsSnapshot()
metrics.ParseFromString(response.data.value)
return calibration.Calibration(metrics)
def get_latest_calibration(
self, processor_id: str) -> Optional[calibration.Calibration]:
"""Returns metadata about the latest known calibration for a processor.
Params:
processor_id: The processor identifier within the resource name,
where name has the format:
`projects/<project_id>/processors/<processor_id>`.
Returns:
A dictionary containing the calibration data or None if there are
no calibrations.
"""
processor_name = 'projects/{}/processors/{}'.format(
self.project_id, processor_id)
response = self.service.projects().processors().calibrations().list(
parent=processor_name).execute()
if (not 'calibrations' in response
or len(response['calibrations']) < 1):
return None
return calibration.Calibration(response['calibrations'][0]['data'])
def _to_calibration(
calibration_any: qtypes.any_pb2.Any) -> calibration.Calibration:
metrics = v2.metrics_pb2.MetricsSnapshot()
metrics.ParseFromString(calibration_any.value)
return calibration.Calibration(metrics)
