v1.15.1

1.15.1 (2022-07-18)

Features

• add get_associated_experiment method to pipeline_jobs (#1476) (e9f2c3c)
• Add sample for create artifact and execution using the Metadata SDK. (#1462) (1fc7dd9)
• Add support for start_execution in MLMD SDK. (#1465) (298958f)
• Add support for Vertex Tables Q2 regions (#1498) (1b16f90)
• Added the PipelineJob.from_pipeline_func method (#1415) (6ef05de)

Bug Fixes

• deps: require google-api-core>=1.32.0,>=2.8.0 (#1512) (6d09dee)
• Unbreak aiplatform.Experiment.create (#1509) (558c141)

Miscellaneous Chores

• release 1.15.1 (#1510) (e500ff3)

v1.15.0

1.15.0 (2022-06-29)

Features

• add default_skew_threshold to TrainingPredictionSkewDetectionConfig in aiplatform v1beta1, v1 model_monitoring.proto (#1411) (7a8e3be)
• add model_monitoring_config to BatchPredictionJob in aiplatform v1beta1 batch_prediction_job.proto (#1450) (d35df58)
• add model_version_id to BatchPredictionJob in aiplatform v1 batch_prediction_job.proto (#1453) (9ef057a)
• add model_version_id to UploadModelResponse in aiplatform v1 model_service.proto (#1442) (1c198f1)
• Add PrivateEndpoint class and HTTP methods (#1033) (425a32f)
• add support for accepting an Artifact Registry URL in pipeline_job (#1405) (e138cfd)
• add support for failure_policy in PipelineJob (#1452) (d0968ea)
• Improved metadata artifact and execution creation using python / SDK (#1430) (6c4374f)
• support dataset update (#1416) (e3eb82f)
• Support for Model Versioning (#1438) (d890685)
• Vertex AI Experiments GA (#1410) (24d1bb6)

Bug Fixes

• Fixed docstrings for wildcards and matching engine type (#1220) (d778dee)
• Removed dirs_exist_ok parameter as it's not backwards compatible (#1170) (50d4129)

v1.14.0

1.14.0 (2022-06-08)

Features

• add a way to easily clone a PipelineJob (#1239) (efaf6ed)
• add display_name and metadata to ModelEvaluation in aiplatform model_evaluation.proto (b6bf6dc)
• add Examples to Explanation related messages in aiplatform v1beta1 explanation.proto (b6bf6dc)
• Add hierarchy and window configs to Vertex Forecasting training job (#1255) (8560fa8)
• add holiday regions for vertex forecasting (#1253) (0036ab0)
• add IAM policy to aiplatform_v1beta1.yaml (b6bf6dc)
• add latent_space_source to ExplanationMetadata in aiplatform v1 explanation_metadata.proto (b6bf6dc)
• add latent_space_source to ExplanationMetadata in aiplatform v1beta1 explanation_metadata.proto (b6bf6dc)
• add preset configuration for example-based explanations in aiplatform v1beta1 explanation.proto (b6bf6dc)
• add scaling to OnlineServingConfig in aiplatform v1 featurestore.proto (b6bf6dc)
• add seq2seq forecasting training job (#1196) (643d335)
• add successful_forecast_point_count to CompletionStats in completion_stats.proto (b6bf6dc)
• add template_metadata to PipelineJob in aiplatform v1 pipeline_job.proto (b6bf6dc)
• Add Vertex Forecasting E2E test. (#1248) (e82c179)
• Added forecasting snippets and fixed bugs with existing snippets (#1210) (4e4bff5)

Bug Fixes

• change endpoint update method to return resource (#1409) (44e279b)
• Changed system test to use list_models() correctly (#1397) (a3da19a)
• Pinned protobuf to prevent issues with pb files. (#1398) (7a54637)

Documentation

• fix changelog header to consistent size (#1404) (f6a7e6f)

v1.13.1

1.13.1 (2022-05-26)

Features

• add batch_size kwarg for batch prediction jobs (#1194) (50bdb01)
• add update endpoint (#1162) (0ecfe1e)
• support autoscaling metrics when deploying models (#1197) (095717c)

Bug Fixes

• check in service proto file (#1174) (5fdf151)
• regenerate pb2 files using grpcio-tools (#1394) (406c868)

Documentation

• update aiplatform SDK arrangement for Sphinx (#1163) (e9510ea)

Miscellaneous Chores

• release 1.13.1 (#1395) (df78407)

v1.13.0

1.13.0 (2022-05-09)

Features

• add ConvexAutomatedStoppingSpec to StudySpec in aiplatform v1 study.proto (847ad78)
• add ConvexAutomatedStoppingSpec to StudySpec in aiplatform v1beta1 study.proto (847ad78)
• add JOB_STATE_UPDATING to JobState in aiplatform v1 job_state.proto (847ad78)
• add JOB_STATE_UPDATING to JobState in aiplatform v1beta1 job_state.proto (847ad78)
• add LatestMonitoringPipelineMetadata to ModelDeploymentMonitoringJob in aiplatform v1beta1 model_deployment_monitoring_job.proto (847ad78)
• add ListModelVersion, DeleteModelVersion, and MergeVersionAliases rpcs to aiplatform v1beta1 model_service.proto (847ad78)
• add MfsMount in aiplatform v1 machine_resources.proto (847ad78)
• add MfsMount in aiplatform v1beta1 machine_resources.proto (847ad78)
• add model_id and parent_model to TrainingPipeline in aiplatform v1beta1 training_pipeline.proto (847ad78)
• add model_version_id to DeployedModel in aiplatform v1beta1 endpoint.proto (847ad78)
• add model_version_id to PredictResponse in aiplatform v1beta1 prediction_service.proto (847ad78)
• add model_version_id to UploadModelRequest and UploadModelResponse in aiplatform v1beta1 model_service.proto (847ad78)
• add nfs_mounts to WorkPoolSpec in aiplatform v1 custom_job.proto (847ad78)
• add nfs_mounts to WorkPoolSpec in aiplatform v1beta1 custom_job.proto (847ad78)
• add Pandas DataFrame support to TabularDataset (#1185) (4fe4558)
• add PredictRequestResponseLoggingConfig to aiplatform v1beta1 endpoint.proto (847ad78)
• add reserved_ip_ranges to CustomJobSpec in aiplatform v1 custom_job.proto (#1165) (847ad78)
• add reserved_ip_ranges to CustomJobSpec in aiplatform v1beta1 custom_job.proto (847ad78)
• add template_metadata to PipelineJob in aiplatform v1beta1 pipeline_job.proto (#1186) (99aca4a)
• add version_id to Model in aiplatform v1beta1 model.proto (847ad78)
• allow creating featurestore without online node (#1180) (3224ae3)
• Allow users to specify timestamp split for vertex forecasting (#1187) (ee49e00)
• Make matching engine API public (#1192) (469db6b)
• rename Similarity to Examples, and similarity to examples in ExplanationParameters in aiplatform v1beta1 explanation.proto (847ad78)

Documentation

• fix type in docstring for map fields (847ad78)

v1.12.1

1.12.1 (2022-04-20)

Features

• Add endpoind_id arg to Endpoint#create (#1168) (4c21993)
• add ModelEvaluation support (#1167) (10f95cd)

Bug Fixes

• change default for create_request_timeout arg to None (#1175) (47791f7)

Documentation

• endpoint.create => aiplatform.Endpoint.create (#1153) (1122a26)
• update changelog headers (#1164) (c1e899d)
• update model code snippet order in README (#1154) (404d7f1)

Miscellaneous Chores

• release 1.12.1 (#1176) (f98d92e)

v1.12.0

1.12.0 (2022-04-07)

Features

• add categorical_threshold_config to FeaturestoreMonitoringConfig in aiplatform v1 featurestore_monitoring.proto (38f3711)
• add categorical_threshold_config to FeaturestoreMonitoringConfig in aiplatform v1beta1 featurestore_monitoring.proto (38f3711)
• add disable_monitoring to Feature in aiplatform v1 feature.proto (38f3711)
• add disable_monitoring to Feature in aiplatform v1beta1 feature.proto (38f3711)
• Add done method for pipeline, training, and batch prediction jobs (#1062) (f3338fc)
• add import_features_analysis to FeaturestoreMonitoringConfig in aiplatform v1 featurestore_monitoring.proto (38f3711)
• add import_features_analysis to FeaturestoreMonitoringConfig in aiplatform v1beta1 featurestore_monitoring.proto (38f3711)
• add ImportModelEvaluation in aiplatform v1 model_service.proto (#1105) (ef5930c)
• add monitoring_config to EntityType in aiplatform v1 entity_type.proto (#1077) (38f3711)
• add monitoring_stats_anomalies to Feature in aiplatform v1 feature.proto (38f3711)
• add monitoring_stats_anomalies to Feature in aiplatform v1beta1 feature.proto (38f3711)
• add numerical_threshold_config to FeaturestoreMonitoringConfig in aiplatform v1 featurestore_monitoring.proto (38f3711)
• add numerical_threshold_config to FeaturestoreMonitoringConfig in aiplatform v1beta1 featurestore_monitoring.proto (38f3711)
• add objective to MonitoringStatsSpec in aiplatform v1 featurestore_service.proto (38f3711)
• add objective to MonitoringStatsSpec in aiplatform v1beta1 featurestore_service.proto (38f3711)
• add PredictRequestResponseLoggingConfig to Endpoint in aiplatform v1 endpoint.proto (#1072) (be0ccc4)
• add staleness_days to SnapshotAnalysis in aiplatform v1 featurestore_monitoring.proto (38f3711)
• add staleness_days to SnapshotAnalysis in aiplatform v1beta1 featurestore_monitoring.proto (38f3711)
• Add support for Vertex Tables Q1 regions (#1065) (6383d4f)
• add timeout arg across SDK (#1099) (184f7f3)
• Add timeout arguments to Endpoint.predict and Endpoint.explain (#1094) (cc59e60)
• Made display_name parameter optional for most calls (#882) (400b760)
• sdk: enable loading both JSON and YAML pipelines IR (#1089) (f2e70b1)
• v1beta1: add service_account to BatchPredictionJob in batch_prediction_job.proto (#1084) (b7a5177)

Bug Fixes

• add resource manager utils to get project ID from project number (#1068) (f10a1d4)
• add self.wait() in operations after optional_sync supported resource creation (#1083) (79aeec1)
• Don't throw exception when getting representation of unrun GCA objects (#1071) (c9ba060)
• Fix import error string showing wrong pip install path (#1076) (74ffa19)
• Fixed getting project ID when running on Vertex AI; Fixes #852 (#943) (876cb33)
• Give aiplatform logging its own log namespace, let the user configure their own root logger (#1081) (fb78243)
• Honoring the model's supported_deployment_resources_types (#865) (db34b85)
• missing reference to logged_web_access_uris (#1056) (198a1b5)
• system tests failure from test_upload_and_deploy_xgboost_model (#1149) (c8422a9)

Documentation

• fix CustomContainerTrainingJob example in docstring (#1101) (d2fb9db)
• improve bigquery_destination_prefix docstring (#1098) (a46df64)
• Include time dependency in documentation for weight, time, and target columns. (#1102) (52273c2)
• samples: read, import, batch_serve, batch_create features (#1046) (80dd40d)
• Update AutoML Video docstring (#987) (6002d5d)

v1.11.0

1.11.0 (2022-03-03)

Features

• add additional_experiement flag in the tables and forecasting training job (#979) (5fe59a4)
• add TPU_V2 & TPU_V3 values to AcceleratorType in aiplatform v1/v1beta1 accelerator_type.proto (#1010) (09c2e8a)
• Added scheduling to CustomTrainingJob, CustomPythonPackageTrainingJob, CustomContainerTrainingJob (#970) (89078e0)

Bug Fixes

• deps: allow google-cloud-storage < 3.0.0dev (#1008) (1c34154)
• deps: require google-api-core>=1.31.5, >=2.3.2 (#1050) (dfbd68a)
• deps: require proto-plus>=1.15.0 (dfbd68a)
• enforce bq SchemaField field_type and mode using feature value_type (#1019) (095bea2)
• Fix create_lit_model_from_endpoint not accepting models that don't return a dictionary. (#1020) (b9a057d)
• loosen assertions for system test featurestore (#1040) (2ba404f)
• remove empty scripts kwarg in setup.py (#1014) (ef3fcc8)
• show logs when TFX pipelines are submitted (#976) (c10923b)
• update system test_model_upload to use BUILD_SPECIFIC_GCP_PROJECT (#1043) (e7d2719)

Documentation

• samples: add samples to create/delete featurestore (#980) (5ee6354)
• samples: added create feature and create entity type samples and tests (#984) (d221e6b)

v1.10.0

1.10.0 (2022-02-07)

Features

• _TrainingScriptPythonPackager to support folders (#812) (3aec6a7)
• add dedicated_resources to DeployedIndex in aiplatform v1beta1 index_endpoint.proto feat: add Scaling to OnlineServingConfig in aiplatform v1beta1 featurestore.proto chore: sort imports (#991) (7a7f0d4)
• add dedicated_resources to DeployedIndex message in aiplatform v1 index_endpoint.proto chore: sort imports (#990) (a814923)
• Add XAI SDK integration to TensorFlow models with LIT integration (#917) (ea2b5cf)
• Added aiplatform.Model.update method (#952) (44e208a)
• Enable europe-west6 and northamerica-northeast2 regions (0f6b670)
• enable feature store batch serve to BigQuery and GCS for csv and tfrecord (#919) (c840728)
• enable feature store batch serve to Pandas DataFrame; fix: read instances uri for batch serve (#983) (e0fec36)
• enable feature store online serving (#918) (b8f5f82)
• enable ingest from pd.DataFrame (#977) (9289f2d)
• Open LIT with a deployed model (#963) (ea16849)

Bug Fixes

• Fixed BigQuery datasets that have colon in URI (#855) (153578f)
• Fixed integration test for model.upload (#975) (0ca3747)
• rename teardown fixture (#1004) (fcd0096)

Documentation

• samples: replace deprecated fields in create_training_pipeline_tabular_forecasting_sample.py (#981) (9ebc972)

v1.9.0

Features

• add create in Featurestore, EntityType, Feature; add create_entity_type in Featurestore; add create_feature, batch_create_features in EntityType; add ingest_from_* for bq and gcs in EntityType; add and update delete with force delete nested resources (#872) (ba11c3d)
• Add LIT methods for Pandas DataFrame and TensorFlow saved model. (#874) (03cf301)
• Add support to create TensorboardExperiment (#909) (96ce738)
• Add support to create TensorboardRun (#912) (8df74a2)

Bug Fixes

• Fix timestamp proto util to default to timestamp at call time. (#933) (d72a254)
• Improve handling of undeploying model without redistributing remaining traffic (#898) (8a8a4fa)
• issues/192254729 (#914) (3ec620c)
• issues/192254729 (#915) (0f22ff6)
• use open_in_new_tab in the render method. (#926) (04618e0)