Changelog

1.24.1 (2023-04-21)

Features

  • Add preview capability to deploy models with shared resources. (29d4e45)

  • Add support for create public index endpoint in matching engine (7e6022b)

  • Add support for return public endpoint dns name in matching engine (1b5ae44)

  • Add the new model types to “AutoMLImageTrainingJob” in SDK. (4d032d5)

  • Adds the Time series Dense Encoder (TiDE) forecasting job. (d8e6744)

  • Remove google internal annotation when export to github. (fd5ff99)

Bug Fixes

  • Support timestamp in Vertex SDK write_feature_values() (4b0722c)

Documentation

  • Add Time series Dense Encoder (TiDE) model code sample. (8e91a58)

  • Fix docstring formatting for exceptions (d75322c)

Miscellaneous Chores

1.24.0 (2023-04-12)

Features

  • Add ExperimentRun.get_logged_custom_jobs method (c116b07)

  • Add get method for Experiment and ExperimentRun (41cd943)

  • Add incremental training to AutoMLImageTrainingJob. (bb92380)

  • Add preview capability to manage DeploymentResourcePools. (5df5da0)

  • Add start_time support for BatchReadFeatureValues wrapper methods. (91d8459)

  • Add TensorBoard log uploader (3fad7bb)

  • Enable deployment of models that do not support deployment (25f3f21)

  • Enable experiment tracking in CustomJob (94a63b8)

  • Update the v1 service definition to add the embedding_id field in MatchRequest. (5a1146e)

Bug Fixes

  • Adding previously created PrivateEndpoint network parameter in Model deploy helper method (3e1b206)

Documentation

  • Adds note to delete endpoint sample (#2060) (9922eb2)

  • Fix create tensorboard sample (2c45123)

  • samples: Add sample for experiment run state update. (111a747)

  • Update docstring for 3 model uploading methods (a71e4a3)

  • Update Vertex Forecasting weight column description. (e0ee183)

1.23.0 (2023-03-15)

Features

  • Implement Model.copy functionality. (94dd82f)

  • Update the v1 service definition to add the fraction_leaf_nodes_to_search_override field which replaces leaf_nodes_to_search_percent_override. (badd386)

Documentation

  • Added missing comma in README (8cb4377)

1.22.1 (2023-02-28)

Features

  • Add support for enable_dashboard_access field for Training jobs in SDK (3500eab)

  • Add the recently added new model type “cloud_1” to the “AutoMLImageTrainingJob” in SDK. (581939b)

Documentation

  • Add temporal fusion transformer (TFT) model code sample. (8ddc062)

  • samples: Add samples for autologging (f8052b8)

Miscellaneous Chores

1.22.0 (2023-02-16)

Features

  • Add a return value (ClassificationMetrics) for the log_classification_metrics() (8ebcdbd)

  • Add metric and parameter autologging to experiments (96e9e12)

  • Add update_version to Model Registry (8621e24)

  • Support a list of GCS URIs in CustomPythonPackageTrainingJob (05bb71f)

  • Support Model Serialization in Vertex Experiments(tensorflow) (f38ddc2)

Bug Fixes

  • Added missing instances_format parameter to batch_prediction_job_samples (82a2afc)

  • Address broken unit tests in certain environments (d06b22d)

  • List method for MLMD schema classes (2401a1d)

  • Unbreak additional timeout for _deploy_call() (076308f)

  • Unbreak additional timeout for MatchingEngine update_embeddings (5d0bc1e)

  • Unbreak timeouts for Dataset create. (328ebac)

  • Use Client.list_blobs instead of Bucket.list_blobs in CPR artifact downloader, to make sure that CPR works with custom service accounts on Vertex Prediction. (bb27619)

Documentation

  • Add a hint to auth Docker to the LocalModel push_image docstring. (e97a6fb)

  • Fix Create and Import Tabular BQ dataset sample (4415c10)

  • Fix LocalModel push_image docstring. (5fdb7fc)

  • Fixed a typo in docstring. (4ee6232)

  • New samples for model serialization (83457ca)

  • Samples for model serialization (7997094)

1.21.0 (2023-01-13)

Features

  • Add default skew threshold to be an optional input at _SkewDetectionConfig and also mark the target_field and data_source of skew config to optional. (7da4164)

  • Add filter to Model Registry list_versions API. (c1cb33f)

  • Add MLMD schema class ExperimentModel (94b2f29)

  • Add Service Account support to BatchPredictionJob (deba06b)

  • Add support for Predict Request Response Logging in Endpoint SDK (372ab8d)

  • Adding Feature Store: Streaming ingestion to GA (6bc4c84)

  • Enable passing experiment_tensorboard to init without experiment (369a0cc)

  • Support Model Serialization in Vertex Experiments(sklearn) (d4deed3)

  • Support Model Serialization in Vertex Experiments(xgboost) (fe75eba)

Bug Fixes

  • Endpoint.undeploy_all() doesn’t undeploy all models (9fb24d7)

  • Fix bug in associating tensorboard to an experiment (6def0b8)

  • Pin shapely version to <2.0.0 (1efd816)

  • Unbreak timeouts for Dataset create, FeatureStore ingest, and MatchingEngine Index create. (3096d1c)

  • Updated proto message formatting logic for batch predict model monitoring (f87fef0)

1.20.0 (2022-12-15)

Features

  • Adds the temporal fusion transformer (TFT) forecasting job (99313e0)

  • Reraise exceptions from API calls (d72bc83)

Documentation

  • samples: Feature Store: Streaming ingestion code sample and test (bc9e2cf)

1.19.1 (2022-12-08)

Features

  • Add explanationSpec to TrainingPipeline-based custom jobs (957703f)

Bug Fixes

  • Add pre-built container(tf2-gpu-2-1) to the container URI list (cdd557e)

  • Fix bug that broke profiler with ‘0-rc2’ tensorflow versions. (8779df5)

  • Fixed argument name in UnmanagedContainerModel (d876b3a)

Documentation

  • Add a sample for create_tensorboard. (52656ca)

  • Fix Experiment resource name format docstring. (f8e5842)

  • Fix get Experiment data frame sample (24e1465)

  • Update docstrings for “data_item_labels” in dataset (b2f8c42)

  • Update README fix product doc link (43a2679)

Miscellaneous Chores

1.19.0 (2022-11-17)

Features

  • Add Feature Store: Streaming Ingestion (write_feature_values()) and introduce Preview namespace to Vertex SDK (bae0315)

  • Add bq_dataset_id parameter to batch_serve_to_df (bb72562)

  • Add annotation_labels to ImportDataConfig in aiplatform v1 dataset.proto (43e2805)

  • Add support for ordery_by in Metadata SDK list methods for Artifact, Execution and Context. (2377606)

  • Support global network parameter. (c7f57ad)

Bug Fixes

  • Correct data file gcs path for import_data_text_sentiment_analysis_sample test (86df4b5)

  • Print error for schema classes (13e2165)

Documentation

  • Update README with new link for AI Platform API (35b83d9)

1.18.3 (2022-11-01)

Documentation

  • Add a sample for get_experiment_run_artifacts (7266352)

1.18.3 (2022-10-31)

Documentation

  • Add a sample for get_experiment_run_artifacts (7266352)

1.18.2 (2022-10-20)

Bug Fixes

  • Added proto message conversion to MDMJob.update fields (#1718) (9e77c61)

  • Log_classification_metrics (#1742) (3588526)

  • PipelineJob should only pass bearer tokens for AR URIs (b43851c)

Documentation

  • Fix create experiment sample (#1716) (cba7fbf)

  • Resurface googleapis.dev and prediction docs (#1724) (24f0c6f)

  • samples: Improve docstring of Vertex AI Python SDK Model Registry samples (#1705) (f97e90f)

1.18.1 (2022-10-10)

Bug Fixes

1.18.0 (2022-10-03)

Features

  • Add deleteFeatureValues in aiplatform v1beta1 featurestore_service.proto (#1670) (9a506ee)

  • Add model_source_info to Model in aiplatform v1beta1 model.proto (#1691) (876fb2a)

  • Add support for HTTPS URI pipeline templates (#1683) (926d0b6)

  • Add support for V1 and V2 classification models for the V1Beta2 API (#1680) (1cda4b4)

  • Support complex metrics in Vertex Experiments (#1698) (ed0492e)

Bug Fixes

  • deps: Require protobuf >= 3.20.2 (#1699) (c5c77ad)

  • Fix endpoint parsing in ModelDeploymentMonitoringJob.update (#1671) (186872d)

  • Project/location parsing for nested resources (#1700) (9e1d796)

  • Show inherited SDK methods in pydoc (#1707) (2b7583b)

Documentation

1.17.1 (2022-09-15)

Features

  • Add enable_simple_view to PipelineJob.list() (#1614) (627fdf9)

  • Add eval metrics types to get_experiment_df (#1648) (944b03f)

  • Adding Python 3.10 support + updating google-vizier version (#1644) (f4766dc)

Miscellaneous Chores

1.17.0 (2022-09-07)

Features

  • Add input artifact when creating a pipeline (#1593) (2cf9fe6)

  • Add model_monitoring_stats_anomalies,model_monitoring_status to BatchPredictionJob in aiplatform v1beta1 batch_prediction_job.proto (#1621) (0a1f4e9)

  • Add read_mask to ListPipelineJobsRequest in aiplatform v1 pipeline_service (#1589) (9e19a40)

  • Add samples for get execution input and output artifacts (#1585) (eb5a4b6)

  • Add support for SDK Method metrics tracking via _USER_AGENT_SDK… (#1591) (28e56ef)

  • Support filters in matching engine vector matching (#1608) (d591d3e)

  • Support model monitoring for batch prediction in Vertex SDK (#1570) (bbec998)

  • Support raw_predict for Endpoint (#1620) (cc7c968)

  • Support ResourceName with Version. (#1609) (737dc2b)

  • Update the samples of hyperparameter tuning in the public doc (#1600) (653b759)

Bug Fixes

  • deps: Allow protobuf < 5.0.0 (#1587) (3d3e0aa)

  • deps: require proto-plus >= 1.22.0 (3d3e0aa)

  • Log_metrics docstring error (#1588) (0385c4c)

  • Study.list() method (#1594) (47eb0ae)

  • Update Model.list_model_evaluations and get_model_evaluation to use the provided version (#1616) (8fb836b)

Documentation

1.16.1 (2022-08-02)

Features

  • Add google.ClassificationMetrics, google.RegressionMetrics, and google.Forecasting Metrics (#1549) (3526b3e)

  • added support for conditional parameters in hyperparameter tuning (#1544) (744cc38)

  • SDK support for model monitoring (#1249) (18c88d1)

  • support case insensitive match on search facets (#1523) (cb4d405)

  • Vertex Vizier support in SDK. (#1434) (b63b3ba)

Bug Fixes

Miscellaneous Chores

1.16.0 (2022-07-27)

Features

  • Add metadata SDK sample for delete method. (#1530) (46aa9b5)

  • Add metadata SDK samples for list artifact and list execution (#1514) (c0d01f1)

  • Add Metadata SDK support and samples for get method (#1516) (d442248)

  • Add samples for Metadata context list, get, and create (#1525) (d913e1d)

  • Change the Metadata SDK _Context class to an external class (#1519) (95b107c)

  • Refactor schema classes to subclass from _Resource (#1536) (93002e8)

  • Support custom containers in CustomJob.from_local_script (#1483) (be0b7e1)

  • Vertex AI Prediction Custom Prediction Routine (34bbd0a)

Bug Fixes

  • Fixed getting the output GCS bucket in PipelineJob.submit (#1542) (69d6c7d)

  • Pass the PipelineJob credentials to create_gcs_bucket_for_pipeline_artifacts_if_it_does_not_exist (#1537) (b53e2b5)

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

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)

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

1.13.1 (2022-05-26)

Features

Bug Fixes

Documentation

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

Miscellaneous Chores

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)

1.12.1 (2022-04-20)

Features

Bug Fixes

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

Documentation

Miscellaneous Chores

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)

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)

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

Documentation

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

1.9.0 (2021-12-29)

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)

1.8.1 (2021-12-14)

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)

1.8.0 (2021-12-03)

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)

1.7.1 (2021-11-16)

Features

Bug Fixes

  • add parameters_value in PipelineJob for schema > 2.0.0 (#817) (900a449)

  • exclude support for python 3.10 (#831) (0301a1d)

Miscellaneous Chores

1.7.0 (2021-11-06)

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)

1.6.2 (2021-11-01)

Features

  • Add PipelineJob.submit to create PipelineJob without monitoring it’s completion. (#798) (7ab05d5)

  • support new protobuf value param types for Pipeline Job client (#797) (2fc05ca)

Bug Fixes

  • Add retries when polling during monitoring runs (#786) (45401c0)

  • use version.py for versioning (#804) (514031f)

  • Widen system test timeout, handle tearing down failed training pipelines (#791) (78879e2)

Miscellaneous Chores

1.6.1 (2021-10-25)

Features

  • Add debugging terminal support for CustomJob, HyperparameterTun… (#699) (2deb505)

  • add support for python 3.10 (#769) (8344804)

  • Add training_utils folder and environment_variables for training (141c008)

  • enable reduction server (#741) (8ef0ded)

  • enabling AutoML Forecasting training response to include BigQuery location of exported evaluated examples (#657) (c1c2326)

  • PipelineJob: allow PipelineSpec as param (#774) (f90a1bd)

  • pre batch creating TensorboardRuns and TensorboardTimeSeries in one_shot mode to speed up uploading (#772) (c9f68c6)

Bug Fixes

  • cast resource labels to dict type (#783) (255edc9)

  • Remove sync parameter from create_endpoint_sample (#695) (0477f5a)

Miscellaneous Chores

1.6.0 (2021-10-12)

Features

  • add featurestore service to aiplatform v1 (#765) (68c88e4)

  • Add one shot profile uploads to tensorboard uploader. (#704) (a83f253)

  • Added column_specs, training_encryption_spec_key_name, model_encryption_spec_key_name to AutoMLForecastingTrainingJob.init and various split methods to AutoMLForecastingTrainingJob.run (#647) (7cb6976)

  • Lazy load Endpoint class (#655) (c795c6f)

1.5.0 (2021-09-30)

Features

  • Add data plane code snippets for feature store service (#713) (e3ea683)

  • add flaky test diagnostic script (#734) (09e48de)

  • add vizier service to aiplatform v1 BUILD.bazel (#731) (1a580ae)

  • code snippets for feature store control plane (#709) (8e06ced)

  • Updating the Tensorboard uploader to use the new batch write API so it runs more efficiently (#710) (9d1b01a)

Bug Fixes

1.4.3 (2021-09-17)

Features

  • PipelineJob: support dict, list, bool typed input parameters fr… (#693) (243b75c)

Bug Fixes

  • Update milli node_hours for image training (#663) (64768c3)

  • XAI Metadata compatibility with Model.upload (#705) (f0570cb)

Miscellaneous Chores

1.4.2 (2021-09-10)

Features

  • add explanation metadata get_metadata_protobuf for reuse (#672) (efb6d18)

1.4.1 (2021-09-07)

Features

  • add prediction service RPC RawPredict to aiplatform_v1beta1 feat: add tensorboard service RPCs to aiplatform_v1beta1: BatchCreateTensorboardRuns, BatchCreateTensorboardTimeSeries, WriteTensorboardExperimentData feat: add model_deployment_monitori… (#670) (b73cd94)

  • add Vizier service to aiplatform v1 (#671) (179150a)

  • add XAI, model monitoring, and index services to aiplatform v1 (#668) (1fbce55)

  • Update tensorboard uploader to use Dispatcher for handling different event types (#651) (d20b520), closes #519

Documentation

1.4.0 (2021-08-30)

Features

  • add filter and timestamp splits (#627) (1a13577)

  • add labels to all resource creation apis (#601) (4e7666a)

  • add PipelineJob.list (a58ea82)

  • add support for export_evaluated_data_items_config in AutoMLTab… (#583) (2a6b0a3)

  • add util functions to get URLs for Tensorboard web app. (#635) (8d88c00)

  • Add wait_for_resource_creation to BatchPredictionJob and unblock async creation when model is pending creation. (#660) (db580ad)

  • Added the VertexAiResourceNoun.to_dict() method (#588) (b478075)

  • expose base_output_dir for custom job (#586) (2f138d1)

  • expose boot disk type and size for CustomTrainingJob, CustomPythonPackageTrainingJob, and CustomContainerTrainingJob (#602) (355ea24)

  • split GAPIC samples by service (#599) (5f15b4f)

Bug Fixes

  • Fixed bug in TabularDataset.column_names (#590) (0fbcd59)

  • pipeline none values (#649) (2f89343)

  • Populate service_account and network in PipelineJob instead of pipeline_spec (#658) (8fde2ce)

  • re-remove extra TB dependencies introduced due to merge conflict (#593) (433b94a)

  • Update BatchPredictionJob.iter_outputs() and BQ docstrings (#631) (28f32fd)

1.3.0 (2021-07-30)

Features

  • add get method for PipelineJob (#561) (fe5e6e4)

  • add Samples section to CONTRIBUTING.rst (#558) (d35c466)

  • add tensorboard resource management (#539) (6f8d3d1)

  • add tf1 metadata builder (#526) (918998c)

  • add wait for creation and more informative exception when properties are not available (#566) (e346117)

  • Adds a new API method FindMostStableBuild (6a99b12)

  • Adds attribution_score_drift_threshold field (6a99b12)

  • Adds attribution_score_skew_thresholds field (6a99b12)

  • Adds BigQuery output table field to batch prediction job output config (6a99b12)

  • Adds CustomJob.enable_web_access field (6a99b12)

  • Adds CustomJob.web_access_uris field (6a99b12)

  • Adds Endpoint.network, Endpoint.private_endpoints fields and PrivateEndpoints message (6a99b12)

  • Adds Execution.State constants: CACHED and CANCELLED (6a99b12)

  • Adds Feature Store features (6a99b12)

  • Adds fields to Study message (6a99b12)

  • Adds IndexEndpoint.private_ip_ranges field (6a99b12)

  • Adds IndexEndpointService.deployed_index_id field (6a99b12)

  • Adds MetadataService.DeleteArtifact and DeleteExecution methods (6a99b12)

  • Adds ModelMonitoringObjectConfig.explanation_config field (6a99b12)

  • Adds ModelMonitoringObjectConfig.ExplanationConfig message field (6a99b12)

  • column specs for tabular transformation (#466) (71d0bd4)

  • enable_caching in PipelineJob to compile time settings (#557) (c9da662)

  • Removes breaking change from v1 version of AI Platform protos (6a99b12)

Bug Fixes

  • change default replica count to 1 for custom training job classes (#579) (c24251f)

  • create pipeline job with user-specified job id (#567) (df68ec3)

  • deps: pin ‘google-{api,cloud}-core’, ‘google-auth’ to allow 2.x versions (#556) (5d79795)

  • enable self signed jwt for grpc (#570) (6a99b12)

Documentation

1.2.0 (2021-07-14)

Features

  • Add additional_experiments field to AutoMlTablesInputs (#540) (96ee726)

  • add always_use_jwt_access (#498) (6df4866)

  • add explain get_metadata function for tf2. (#507) (f6f9a97)

  • Add structure for XAI explain (from XAI SDK) (#502) (cb9ef11)

  • Add two new ModelType constants for Video Action Recognition training jobs (96ee726)

  • Adds AcceleratorType.NVIDIA_TESLA_A100 constant (f3a3d03)

  • Adds additional_experiments field to AutoMlForecastingInputs (8077b3d)

  • Adds additional_experiments field to AutoMlTablesInputs (#544) (8077b3d)

  • Adds AutoscalingMetricSpec message (f3a3d03)

  • Adds BigQuery output table field to batch prediction job output config (f3a3d03)

  • Adds fields to Study message (f3a3d03)

  • Adds JobState.JOB_STATE_EXPIRED constant (f3a3d03)

  • Adds PipelineService methods for Create, Get, List, Delete, Cancel (f3a3d03)

  • Adds two new ModelType constants for Video Action Recognition training jobs (8077b3d)

  • Removes AcceleratorType.TPU_V2 and TPU_V3 constants (#543) (f3a3d03)

Bug Fixes

  • Handle nested fields from BigQuery source when getting default column_names (#522) (3fc1d44)

  • log pipeline completion and raise pipeline failures (#523) (2508fe9)

  • making the uploader depend on tensorflow-proper (#499) (b95e040)

  • Set prediction client when listing Endpoints (#512) (95639ee)

1.1.1 (2021-06-22)

Features

  • add cancel method to pipeline client (#488) (3b19fff)

Bug Fixes

  • check if training_task_metadata is populated before logging backingCustomJob (#494) (2e627f8)

Documentation

Miscellaneous Chores

1.1.0 (2021-06-17)

Features

  • add aiplatform API Vizier service (fdc968f)

  • add featurestore, index, metadata, monitoring, pipeline, and tensorboard services to aiplatform v1beta1 (fdc968f)

  • add invalid_row_count to ImportFeatureValuesResponse and ImportFeatureValuesOperationMetadata (fdc968f)

  • add pipeline client init and run to vertex AI (1f1226f)

  • add tensorboard support for CustomTrainingJob, CustomContainerTrainingJob, CustomPythonPackageTrainingJob (#462) (8cfd611)

  • adds enhanced protos for time series forecasting (fdc968f)

  • adds enhanced protos for time series forecasting (#374) (fdc968f)

  • allow the prediction endpoint to be overridden (#461) (c2cf612)

  • AutoMlImageSegmentationInputs.ModelType adds MOBILE_TF_LOW_LATENCY constant (fdc968f)

  • AutoMlVideoClassificationInputs.ModelType adds MOBILE_JETSON_VERSATILE_1 constant (fdc968f)

  • Expose additional attributes into Vertex SDK to close gap with GAPIC (#477) (572a27c)

  • ImageSegmentationPredictionResult.category_mask field changed to string data type (fdc968f)

  • remove unsupported accelerator types (fdc968f)

  • removes forecasting (time_series_forecasting proto) from public v1beta1 protos (fdc968f)

  • removes unused protos from schema/ folders: schema/io_format.proto, schema/saved_query_metadata.proto (fdc968f)

  • support additional_experiments for AutoML Tables and AutoML Forecasting (#428) (b4211f2)

  • support self-signed JWT flow for service accounts (fdc968f)

Bug Fixes

  • add async client to %name_%version/init.py (fdc968f)

  • add target_column docstring (#473) (c0543cd)

  • configuring timeouts for aiplatform v1 methods (fdc968f)

  • Enable MetadataStore to use credentials when aiplatfrom.init passed experiment and credentials. (#460) (e7bf0d8)

  • exclude docs and tests from package (#481) (b209904)

  • pass credentials to BQ and GCS clients (#469) (481d172)

  • remove display_name from FeatureStore (fdc968f)

  • Remove URI attribute from Endpoint sample (#478) (e3cbdd8)

Documentation

  • changes product name to Vertex AI (fdc968f)

  • correct link to fieldmask (fdc968f)

  • removes tinyurl links (fdc968f)

1.0.1 (2021-05-21)

Bug Fixes

  • use resource name location when passed full resource name (#421) (f40f322)

1.0.0 (2021-05-19)

Features

  • add custom and hp tuning (#388) (aab9e58)

  • add tensorboard support to custom job and hyperparameter tuning job (#404) (fa9bc39)

Bug Fixes

  • tb-gcp-uploader to show flags in “–help” correctly (#409) (9f603dd)

Miscellaneous Chores

0.9.0 (2021-05-17)

Features

  • Add AutoML vision, Custom training job, and generic prediction samples (#300) (cc1a708)

  • Add VPC Peering support to CustomTrainingJob classes (#378) (56273f7)

  • AutoML Forecasting, Metadata Experiment Tracking, Tensorboard uploader (e94c9db)

Bug Fixes

0.8.0 (2021-05-11)

Features

  • Add export model (#353) (12c5be4)

  • add mbsdk video dataset samples (#307) (24d6920)

  • Add service account support to Custom Training and Model deployment (#342) (b4b1b12)

  • add services to aiplatform_v1beta1 (#367) (beb4032)

  • Added create_training_pipeline_custom_job_sample and create_training_pipeline_custom_training_managed_dataset_sample and fixed create_training_pipeline_image_classification_sample (#343) (1c6b998)

  • Added create_training_pipeline_custom_package_job_sample and create_training_pipeline_custom_container_job_sample and reworked create_training_pipeline_custom_job_sample (#351) (7abf8ef)

  • Added default AutoMLTabularTrainingJob column transformations (#357) (4fce8c4)

  • Added deploy_model_with_dedicated_resources_sample, deploy_model_with_automatic_resources_sample, upload_model and get_model samples (#337) (ef4f6f8)

  • Added explain tabular samples (#348) (c95d1ce)

  • aiplatform: Add support for setting User agent header (#364) (d50d26d)

  • expose env var in cust training class run func args (#366) (7ae28b8)

  • MBSDK Tabular samples (#338) (4241738)

  • update featurestore (#377) (bc17163)

Bug Fixes

  • Add all supported uCAIP GA regions (#350) (5e14c59)

  • aiplatform: Fix doc formatting (#359) (857f63d)

  • Bump google-cloud-storage min version to 1.32.0 (#371) (6fda925)

  • default model_display_name to _CustomTrainingJob.display_name when model_serving_container_image_uri is provided (#324) (a5fa7a2)

  • env formatiing (#379) (6bc4c61)

  • remove Optional type hint on deploy (#345) (79b0ab1)

0.7.1 (2021-04-14)

Bug Fixes

  • fix list failing without order_by and local sorting (#320) (06e99db)

0.7.0 (2021-04-14)

Features

  • Add Custom Container Prediction support, move to single API endpoint (#277) (ca7f6d6)

  • Add initial Model Builder SDK samples (#265) (1230dc6)

  • Add list() method to all resource nouns (#294) (3ec9386)

  • add support for multiple client versions, change aiplatform from compat.V1BETA1 to compat.V1 (#290) (89e3212)

  • Make aiplatform.Dataset private (#296) (1f0d5f3)

  • parse project location when passed full resource name to get apis (#297) (674227d)

Bug Fixes

  • add quotes to logged snippet (0ecd0a8)

  • make logging more informative during training (#310) (9a4d991)

  • remove TPU from accelerator test cases (57f4fcf)

0.6.0 (2021-03-22)

Features

Bug Fixes

  • skip create data labeling job sample tests (#254) (116a29b)

0.5.1 (2021-03-01)

Bug Fixes

  • fix create data labeling job samples tests (#244) (3c440de)

  • fix predict sample tests for proto-plus==1.14.2 (#250) (b1c9d88)

  • fix update export model sample, and add sample test (#239) (20b8859)

Documentation

0.5.0 (2021-02-17)

Features

Bug Fixes

0.4.0 (2021-01-08)

Features

  • add create_batch_prediction_job samples (#67) (96a850f)

  • add create_hyperparameter_tuning_job_python_package sample (#76) (5155dee)

  • add create_training_pipeline_custom_training_managed_dataset sample (#75) (b012283)

  • add custom_job samples (#69) (fb165b3)

  • add data_labeling samples (#78) (7daacd5)

  • add get_custom_job and get_hyperparameter_tuning_job samples (#68) (26da7a7)

  • add schema namespace (#140) (1cbd4a5)

  • add video action recognition samples (#77) (4c60ad6)

  • Added tabular forecasting sample (#156) (a23857b)

  • Added tabular forecasting samples (#128) (69fc7fd)

  • adds function/method enhancements, demo samples (#122) (1a302d2)

  • adds text batch prediction samples (#82) (ad09c29)

  • initial generation of enhanced types (#102) (5ddbf16)

  • update create_training_pipeline samples (#142) (624a08d)

  • xai samples (#83) (5cf3859)

Bug Fixes

Documentation

0.3.1 (2020-11-13)

Features

0.3.0 (2020-11-05)

Features

Bug Fixes