Version 1.31.1

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Changelog

1.31.1 (2023-08-24)

• fix: LLM - De-hardcoded the max_output_tokens default value for the CodeGenerationModel (f5a20eb)

1.31.0 (2023-08-21)

Features

• Add disable_retries option to custom jobs. (db518b0)

• LLM - Added support for stop_sequences in inference (6f7ea84)

• LLM - Exposed the TextGenerationResponse.raw_prediction_response (f8f2b9c)

• LLM - Made tuning asynchronous when tuning becomes GA (226ab8b)

• LLM - release model evaluation for TextGenerationModel to public preview (8df5185)

• LLM - Released TextGenerationModel tuning to GA (62ff30d)

• LLM - Support streaming prediction for chat models (ce60cf7)

• LLM - Support streaming prediction for code chat models (0359f1d)

• LLM - Support streaming prediction for code generation models (3a8348b)

• LLM - Support streaming prediction for text generation models (fb527f3)

• LLM - TextEmbeddingModel - Added support for structural inputs (TextEmbeddingInput), auto_truncate parameter and result statistics (cbf9b6e)

• LVM - Added support for Image Generation models (b3729c1)

• LVM - Released ImageCaptioningModel to GA (7575046)

• LVM - Released ImageQnAModel to GA (fd5cb02)

• LVM - Released MultiModalEmbeddingModel to GA (e99f366)

• LVM - Removed the width and height parameters from ImageGenerationModel.generate_images since the service has dropped support for image sizes and aspect ratios (52897e6)

• Scheduled pipelines client GA. (62b8b23)

Documentation

• Generate documentation for tune_model and related class (705e1ea)

• LVM - Added autogenerated documentation for visual models (18e8bb2)

1.30.1 (2023-08-11)

Features

• LLM - Added tuning support for chat-bison models (3a97c52)

• LLM - Added tuning support for codechat-bison models (af6e455)

Bug Fixes

• LLM - Fixed the TextGenerationModel.predict parameters (f3b25ab)

Miscellaneous Chores

• Release 1.30.1 (d1c79c4)

1.30.0 (2023-08-10)

Features

• Add model.evaluate() method to Model class (51df86e)

• Add support for providing only text to MultiModalEmbeddingModel.get_embeddings() (38ec40a)

Bug Fixes

• LLM - Fixed filter in list_tuned_model_names (57806fb)

1.29.0 (2023-08-02)

Features

• Add preview CustomJob which can be run on persistent resource (56906b0)

• LLM - Support for Batch Prediction for the textembedding models (preview) (a368538)

• LLM - Support tuning for the code-bison model (preview) (e4b23a2)

• LVM - Large Vision Models SDK (preview release). Support for image captioning and image QnA (imagetext model) and multi modal embedding (multimodelembedding model) (preview) (9bbf1ea)

Bug Fixes

• LLM - Fixed get_tuned_model for the future models that are not text-bison (1adf72b)

Documentation

• Fix auto-generated pydoc for language_models (7d72bd1)

• LLM - Made it possible to provide message history to CodeChatModel when starting chat. (cf46145)

1.28.1 (2023-07-18)

Features

• LLM - Released the BatchPrediction to GA for TextGenerationModel (701c3a2)

• LLM - Support tuning in the “us-central1” location (4aa7745)

Bug Fixes

• Fix artifact registry link not showing in ui when creating schedules with SDK. (203cb47)

• Fixed the installation error caused by a PyYAML issue (4b86ce1)

• Require model name in ModelEvaluation.list() (aed8c76)

Documentation

• Fixed a docstring for train_steps (1f55b05)

Miscellaneous Chores

• Release 1.28.1 (8ebf22e)

1.28.0 (2023-07-08)

Features

• LLM - Released the Chat models to GA (22aa26d)

1.27.1 (2023-07-06)

Features

• Add sdk support for xai example-based explanations (f9ca1d5)

Miscellaneous Chores

• Release 1.27.1 (2159f29)

1.27.0 (2023-06-30)

Features

• Add submit for CustomTrainingJob and CustomContainerTrainingJob which won’t block until complete. (d6476d0)

• LLM - Added support for learning_rate in tuning (c6cdd10)

• LLM - Released the Codey models to GA (89609c9)

Bug Fixes

• Fix aiplatform.init bug by replacing experiment_name with experiment (c60773a)

• Fix error when calling update_state() after ExperimentRun.list() (cb255ec)

• LLM - Exported the ChatMessage class (7bf7634)

• LLM - Fixed the chat models failing due to safetyAttributes format (459ba86)

• Vizier - Fixed pyvizier client study creation errors (16299d1)

Documentation

• Fixed a docstring for _Dataset (b68a941)

• Fixed a docstring for TimeSeriesDataset (a7dfce2)

• Populate GA LLM SDK Pydocs (e248285)

• Update scheduled pipelines client max_run_count docstring with allowed values. (750e161)

1.26.1 (2023-06-21)

Features

• Add additional scheduled pipelines client getters and unit tests. (9371b4f)

• Add PipelineJobSchedule update method and unit tests. (69c5f60)

• Add tunable parameters for Model Garden model training to the “AutoMLImageTrainingJob” in SDK. (50646be)

• LLM - Added batch prediction (2235305)

• LLM - Exposed the chat history (bf0e20b)

• LLM - Exposed the safety attributes (01ba3ca)

Bug Fixes

• Change scheduled pipelines client dashboard uri to view created schedules. Note: uri will not work until scheduler UI is GA. (d4d8613)

• Fix bug where scheduled pipeline jobs were not running. (4e7d11a)

• Remove Schedule read mask because ListSchedules does not support it. (1fda417)

Miscellaneous Chores

• Release 1.26.1 (42567d2)

Documentation

• Update scheduled pipelines client wait() docstring. (a7d92e5)

1.26.0 (2023-06-07)

Features

• Add additional scheduled pipelines client create method unit tests. (0463678)

• Add pipelineJob create_schedule() method and unit test. (635ae9c)

• Add scheduled pipelines client create/get methods and unit tests. (4755fc7)

• Add scheduled pipelines client list/pause/resume methods and unit tests. (ce5dee4)

• Adding enable_access_logging parameter to Endpoint.deploy() method, minor edit to batch_predict() docstring (794cedd)

• LLM - Added support for CMEK in tuning (aebf74a)

• LLM - Released the LLM SDK to GA (76465e2)

• Support publisher models in BatchPredictionJob.create (13b11c6)

Bug Fixes

• CustomJob.from_local_script does not pass args to script for custom container images (6ead69d)

• Fix bug when checking PipelineJob failure status (a154859)

• Fix the bug that start_upload_tb_log() doesn’t continuously upload (66e6eae)

• LLM - Fixed parameters set in ChatModel.start_chat being ignored (a0d815d)

• LLM - Fixed the DataFrame staging on Windows (056b0bd)

• Resource created by _construct_sdk_resource_from_gapic should use the project from the resource name instead of the default project. (162b2f2)

• Retry for etag errors on context update. (d3d5f9a)

• Unbreak additional timeout for MatchingEngineIndexEndpoint deploy_index (af199c0)

Documentation

• Correct text embedding model ID docstring (8824629)

• LLM - Fixed the rendering of the example usage code blocks. (eaaee28)

1.25.0 (2023-05-09)

Features

• Add support for Large Language Models (866c6aa)

• Add default TensorBoard support. (fa7d3a0)

• Add support for find_neighbors/read_index_datapoints in matching engine public endpoint (e3a87f0)

• Added the new root vertexai package (fbd03b1)

Bug Fixes

• EntityType RPC update returns the updated EntityType - not an LRO. (8f9c714)

• Fix default AutoML Forecasting transformations list. (77b89c0)

• Fix type hints for Prediction.predictions. (56518f1)

• Removed parameter Resume, due to causing confusion and errors. (c82e0b5)

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

• Release 1.24.1 (cf633a2)

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

• Release 1.22.1 (ed4c0b1)

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

• Release 1.19.1 (f01867f)

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

• deps: Allow protobuf 3.19.5 (#1720) (83e3b7c)

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

• Fix typos (#1709) (5fe515c)

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

• Release 1.17.1 (#1668) (b54d659)

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

• ExperimentRun docstring and end_run kwarg (#1649) (075a6c2)

• Remove TODOs from docs (#1513) (406ed84)

• samples: Add AutoML image classification sample (#923) (677b311)

• samples: Add Model Registry samples to Vertex AI Python SDK (#1602) (72fd36d)

• samples: Added seq2seq sample (#1595) (4e7175f)

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

• Correct docstring in Dataset classes (#1553) (caebb47)

Miscellaneous Chores

• release 1.16.1 (#1568) (4437cdd)

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

• release 1.15.1 (#1510) (e500ff3)

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

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

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)

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

• 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)

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

• 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)

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

• 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)

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

• release 1.6.2 (#809) (e50b049)

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

• release 1.6.1 (#789) (4520d35)

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

• #677 (#728) (7f548e4)

• PipelineJob: use name as output only field (#719) (1c84464)

• use the project id from BQ dataset instead of the default project id (#717) (e87a255)

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

• release 1.4.3 (#715) (b610486)

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

• Add code sample for Pipelines (#684) (4f0c18e)

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

• fix spelling (#565) (fe5c702)

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

• omit mention of Python 2.7 in ‘CONTRIBUTING.rst’ (#1127) (#489) (cbc47f8)

Miscellaneous Chores

• release 1.1.1 (1a38ce2)

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

• release 1.0.0 (#407) (a2d7b68)

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

• deps: add packaging requirement (#392) (47c1530)

• enable aiplatform unit tests (dcc459d)

• rollback six to 1.15 (#391) (066624b)

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

• add Vizier service (#266) (e5c1b1a)

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

• update index.rst to include v1 (#246) (82193ef)

0.5.0 (2021-02-17)

Features

• exposes v1 enhanced types and adds tests (#226) (42b587d)

• LRO metadata (#204) (2863dc0)

• moves manual enhanced lib edits outside of generated files (#198) (a04a561)

• updates python-aiplatform to v1 (#212) (efc00ed)

Bug Fixes

• correct text sentiment analysis sample (#222) (0befde3)

• deps: remove optional dependencies (#187) (6589383)

• Fix sample test (#215) (cdeb0ec)

• reduces image size for test image (#213) (3ed0e09)

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

• blacken on library, test files (#135) (53cdbab)

• predict image samples params (#150) (7983b44)

Documentation

• update readme (#81) (19dc31a)

0.3.1 (2020-11-13)

Features

• add samples (#56) (53cc5f5)

0.3.0 (2020-11-05)

Features

• generate v1beta1 (e80a4fc)

• python-aiplatform beta library (#39) (81366dc)

• regenerate v1beta1 (#4) (4ddc426)

Bug Fixes

• re-add py sessions to noxfile (#22) (3c713d5)