Used to retrieve training metrics from SageMaker.
Parameters:
-
metric_queries
(Optional[MetricQueryList], default:
None
)
–
Queries made to retrieve training metrics from SageMaker.
Raises:
Source code in docs_src/capo_sagemaker_metrics/_services/sage_maker_metrics.py
| def batch_get_metrics(
self,
*,
config_overrides: Optional[SageMakerMetricsClientConfig] = None,
metric_queries: Optional[
"capo_sagemaker_metrics.types.metric_query_list.MetricQueryList"
] = None,
) -> "capo_sagemaker_metrics.types.batch_get_metrics_response.BatchGetMetricsResponse":
"""<p>Used to retrieve training metrics from SageMaker.</p>
Args:
metric_queries: <p>Queries made to retrieve training metrics from SageMaker.</p>
Raises:
capo_sagemaker_metrics.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
def _handler(
req: "OperationRequest[capo_sagemaker_metrics.types.batch_get_metrics_request.BatchGetMetricsRequest]",
) -> OperationResponse[
"capo_sagemaker_metrics.types.batch_get_metrics_response.BatchGetMetricsResponse"
]:
import capo_sagemaker_metrics._operations.sage_maker_metrics_service.batch_get_metrics
output, http_response = (
capo_sagemaker_metrics._operations.sage_maker_metrics_service.batch_get_metrics.batch_get_metrics(
req.options, req.input
)
)
return OperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("BatchGetMetrics")
)
input_: capo_sagemaker_metrics.types.batch_get_metrics_request.BatchGetMetricsRequest = {}
if metric_queries is not None:
input_["metric_queries"] = metric_queries
response = execute_pipeline(
OperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output
|