- 1.122.0 (latest)
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Changelog
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
vertexaipackage ( 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
-
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 )
-
PipelineJob should only pass bearer tokens for AR URIs ( b43851c )
Documentation
-
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
-
Fix endpoint parsing in ModelDeploymentMonitoringJob.update ( #1671 ) ( 186872d )
-
Project/location parsing for nested resources ( #1700 ) ( 9e1d796 )
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 )
-
Update the samples of hyperparameter tuning in the public doc ( #1600 ) ( 653b759 )
Bug Fixes
-
deps:require proto-plus >= 1.22.0 ( 3d3e0aa )
-
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 )
-
samples:Add AutoML image classification sample ( #923 ) ( 677b311 )
-
samples:Add Model Registry samples to Vertex AI Python SDK ( #1602 ) ( 72fd36d )
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 )
-
support case insensitive match on search facets ( #1523 ) ( cb4d405 )
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
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 )
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 successful_forecast_point_count to CompletionStats in completion_stats.proto ( b6bf6dc )
-
add template_metadata to PipelineJob in aiplatform v1 pipeline_job.proto ( b6bf6dc )
-
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
-
add batch_size kwarg for batch prediction jobs ( #1194 ) ( 50bdb01 )
-
support autoscaling metrics when deploying models ( #1197 ) ( 095717c )
Bug Fixes
Documentation
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 )
-
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
Documentation
-
endpoint.create => aiplatform.Endpoint.create ( #1153 ) ( 1122a26 )
-
update model code snippet order in README ( #1154 ) ( 404d7f1 )
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 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_accounttoBatchPredictionJobinbatch_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 )
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 )
-
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 )
Bug Fixes
-
Fixed BigQuery datasets that have colon in URI ( #855 ) ( 153578f )
-
Fixed integration test for model.upload ( #975 ) ( 0ca3747 )
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 )
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 )
-
use open_in_new_tab in the render method. ( #926 ) ( 04618e0 )
1.8.1 (2021-12-14)
Bug Fixes
-
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 )
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 )
-
updating Tensorboard related code to use v1 ( #851 ) ( b613b26 )
Bug Fixes
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
Miscellaneous Chores
1.7.0 (2021-11-06)
Features
-
Adds support for
google.protobuf.Valuepipeline parameters in theparameter_valuesfield ( #807 ) ( c97199d ) -
Adds support for
google.protobuf.Valuepipeline parameters in theparameter_valuesfield ( #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 )
-
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 training_utils folder and environment_variables for training ( 141c008 )
-
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
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 )
1.5.0 (2021-09-30)
Features
-
Add data plane code snippets for feature store service ( #713 ) ( e3ea683 )
-
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
-
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
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
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 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 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 boot disk type and size for CustomTrainingJob, CustomPythonPackageTrainingJob, and CustomContainerTrainingJob ( #602 ) ( 355ea24 )
Bug Fixes
-
Fixed bug in TabularDataset.column_names ( #590 ) ( 0fbcd59 )
-
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 Samples section to CONTRIBUTING.rst ( #558 ) ( d35c466 )
-
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 )
Documentation
1.2.0 (2021-07-14)
Features
-
Add additional_experiments field to AutoMlTablesInputs ( #540 ) ( 96ee726 )
-
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
Bug Fixes
Documentation
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 )
-
configuring timeouts for aiplatform v1 methods ( fdc968f )
-
Enable MetadataStore to use credentials when aiplatfrom.init passed experiment and credentials. ( #460 ) ( e7bf0d8 )
-
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
1.0.0 (2021-05-19)
Features
Bug Fixes
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
-
enable aiplatform unit tests ( dcc459d )
0.8.0 (2021-05-11)
Features
-
Add service account support to Custom Training and Model deployment ( #342 ) ( b4b1b12 )
-
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 )
-
aiplatform:Add support for setting User agent header ( #364 ) ( d50d26d )
-
expose env var in cust training class run func args ( #366 ) ( 7ae28b8 )
Bug Fixes
-
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 )
0.7.1 (2021-04-14)
Bug Fixes
0.7.0 (2021-04-14)
Features
-
Add Custom Container Prediction support, move to single API endpoint ( #277 ) ( ca7f6d6 )
-
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 )
-
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
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
-
exposes v1 enhanced types and adds tests ( #226 ) ( 42b587d )
-
moves manual enhanced lib edits outside of generated files ( #198 ) ( a04a561 )
Bug Fixes
0.4.0 (2021-01-08)
Features
-
add create_hyperparameter_tuning_job_python_package sample ( #76 ) ( 5155dee )
-
add create_training_pipeline_custom_training_managed_dataset sample ( #75 ) ( b012283 )
-
add get_custom_job and get_hyperparameter_tuning_job samples ( #68 ) ( 26da7a7 )
-
adds function/method enhancements, demo samples ( #122 ) ( 1a302d2 )
-
update create_training_pipeline samples ( #142 ) ( 624a08d )
Bug Fixes
Documentation
0.3.1 (2020-11-13)
Features
0.3.0 (2020-11-05)
Features
-
generate v1beta1 ( e80a4fc )

