google-cloud-aiplatform

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

Features

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

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)

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)

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)

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)

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)

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)

Bug Fixes

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

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)

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)

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)

Bug Fixes

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

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)

Features

• add Vizier service (#266) (e5c1b1a)

Bug Fixes

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

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)

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)

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)

Features

• add samples (#56) (53cc5f5)

Features

• generate v1beta1 (e80a4fc)
• python-aiplatform beta library (#39) (81366dc)
• regenerate v1beta1 (#4) (4ddc426)

Bug Fixes

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