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)

v1.8.1

Bug Fixes

• add clarity to param model_name (#888) (1d81783)
• add clarity to parameters per user feedback (#886) (37ee0a1)
• add param for multi-label per user's feedback (#887) (fda942f)
• add support for API base path overriding (#908) (45c4086)
• Important the correct constants and use v1 for tensorboard experiments (#905) (48c2bf1)
• incorrect uri for IOD yaml (#889) (e108ef8)
• Minor docstring and snippet fixes (#873) (578e06d)

Documentation

• Update references to containers and notebook samples. (#890) (67fa1f1)
• Updated docstrings with exception error classes (#894) (f9aecd2)

v1.8.0

Features

• Add cloud profiler to training_utils (6d5c7c4)
• add enable_private_service_connect field to Endpoint feat: add id field to DeployedModel feat: add service_attachment field to PrivateEndpoints feat: add endpoint_id to CreateEndpointRequest and method signature to CreateEndpoint feat: add method... (#878) (ca813be)
• add enable_private_service_connect field to Endpoint feat: add id field to DeployedModel feat: add service_attachment field to PrivateEndpoints feat: add endpoint_id to CreateEndpointRequest and method signature to CreateEndpoint feat: add method... (#879) (47e93b2)
• add featurestore module including Featurestore, EntityType, and Feature classes; add get, update, delete, list methods in all featurestore classes; add search method in Feature class (#850) (66745a6)
• Add prediction container URI builder method (#805) (91dd3c0)
• default to custom job display name if experiment name looks like a custom job ID (#833) (8b9376e)
• Support uploading local models (#779) (bffbd9d)
• Tensorboard v1 protos release (#847) (e0fc3d9)
• updating Tensorboard related code to use v1 (#851) (b613b26)
• Upgrade Tensorboard from v1beta1 to v1 (#849) (c40ec85)

Bug Fixes

• Import error for cloud_profiler (#869) (0f124e9)
• Support multiple instances in custom predict sample (#857) (8cb4839)

Documentation

• Added comment for evaluation_id to python examples (#860) (004bf5f)
• Reverted IDs in model_service snippets test (#871) (da747b5)
• Update name of BQ source parameter in samples (#859) (f11b598)

v1.7.1

Features

• Add support for new Vertex regions (#811) (8d04138)

Bug Fixes

• add parameters_value in PipelineJob for schema > 2.0.0 (#817) (900a449)
• exclude support for python 3.10 (#831) (0301a1d)

Miscellaneous Chores

• release 1.7.1 (#845) (ca04de6)

v1.7.0

Features

• Adds support for google.protobuf.Value pipeline parameters in the parameter_values field (#807) (c97199d)
• Adds support for google.protobuf.Value pipeline parameters in the parameter_values field (#808) (726b620)
• PipelineJob switch to v1 API from v1beta1 API (#750) (8db7e0c)

Bug Fixes

• Correct PipelineJob credentials description (#816) (49aaa87)
• Fixed docstrings for Dataset in AutoMLForecastingTrainingJob (760887b)

Documentation

• Fix pydocs README to be consistent with repo README (#821) (95dbd60)
• Update sample with feedback from b/191251050 (#818) (6b2d938)