feat: add model_monitoring_stats_anomalies,model_monitoring_status to…

… BatchPredictionJob in aiplatform v1beta1 batch_prediction_job.proto (#1621) * feat: add model_monitoring_stats_anomalies,model_monitoring_status to BatchPredictionJob in aiplatform v1beta1 batch_prediction_job.proto PiperOrigin-RevId: 470845818 Source-Link: googleapis/googleapis@284389e Source-Link: googleapis/googleapis-gen@29deb79 Copy-Tag: eyJwIjoiLmdpdGh1Yi8uT3dsQm90LnlhbWwiLCJoIjoiMjlkZWI3OWIwNGFlYTE2OWE1NjhlN2M1NDQ4NjgyNDNkNTE2MWRkZSJ9 * 🦉 Updates from OwlBot post-processor See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md Co-authored-by: Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com> Co-authored-by: Yu-Han Liu <yuhanliu@google.com>
googleapis · Aug 31, 2022 · 0a1f4e9 · 0a1f4e9
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diff --git a/google/cloud/aiplatform_v1beta1/types/batch_prediction_job.py b/google/cloud/aiplatform_v1beta1/types/batch_prediction_job.py
@@ -26,6 +26,7 @@
 from google.cloud.aiplatform_v1beta1.types import (
     manual_batch_tuning_parameters as gca_manual_batch_tuning_parameters,
 )
+from google.cloud.aiplatform_v1beta1.types import model_deployment_monitoring_job
 from google.cloud.aiplatform_v1beta1.types import model_monitoring
 from google.cloud.aiplatform_v1beta1.types import (
     unmanaged_container_model as gca_unmanaged_container_model,
@@ -220,6 +221,12 @@ class BatchPredictionJob(proto.Message):
             analysis model behaviors, based on the input and
             output to the batch prediction job, as well as
             the provided training dataset.
+        model_monitoring_stats_anomalies (Sequence[google.cloud.aiplatform_v1beta1.types.ModelMonitoringStatsAnomalies]):
+            Get batch prediction job monitoring
+            statistics.
+        model_monitoring_status (google.rpc.status_pb2.Status):
+            Output only. The running status of the model
+            monitoring pipeline.
     """
 
     class InputConfig(proto.Message):
@@ -539,6 +546,16 @@ class OutputInfo(proto.Message):
         number=26,
         message=model_monitoring.ModelMonitoringConfig,
     )
+    model_monitoring_stats_anomalies = proto.RepeatedField(
+        proto.MESSAGE,
+        number=31,
+        message=model_deployment_monitoring_job.ModelMonitoringStatsAnomalies,
+    )
+    model_monitoring_status = proto.Field(
+        proto.MESSAGE,
+        number=32,
+        message=status_pb2.Status,
+    )
 
 
 __all__ = tuple(sorted(__protobuf__.manifest))
diff --git a/tests/unit/gapic/aiplatform_v1beta1/test_job_service.py b/tests/unit/gapic/aiplatform_v1beta1/test_job_service.py
@@ -61,6 +61,7 @@
 from google.cloud.aiplatform_v1beta1.types import env_var
 from google.cloud.aiplatform_v1beta1.types import explanation
 from google.cloud.aiplatform_v1beta1.types import explanation_metadata
+from google.cloud.aiplatform_v1beta1.types import feature_monitoring_stats
 from google.cloud.aiplatform_v1beta1.types import hyperparameter_tuning_job
 from google.cloud.aiplatform_v1beta1.types import (
     hyperparameter_tuning_job as gca_hyperparameter_tuning_job,