1.39.0 (2024-01-05)
- Add
fraction_leaf_nodes_to_search_override
. Add support for private endpoint infind_neighbors
. (cd31c13) - Add notification_channels field to model monitoring alert config. (bb228ce)
- Add support of newly added fields of ExportData API to SDK (ec3ea30)
- Allow reuse of deleted experiment run id. (5f6ad8d)
- GenAI - Added support for "models/<model ID>" model name format (ab21feb)
- Support "reservedIpRanges" parameter in PipelineJob run() and submit() methods. (ab99e00)
- Support custom target y column name for Bigframes Tensorflow (1634940)
- Verify client and cluster Ray versions match in create_ray_cluster (17dc9b7)
- Missing request parameter for v1beta explain. (443fa9d)
- Pin google-cloud-aiplatform[tensorboard] dependency on tensorflow < 2.15.0 due to breaking change introduced in tensorboard 2.15.1 (4e891f7)
- GenAI - Added GenAI to docs (92fd7f0)
- Update docstring for start_upload_tb_log() (c033c59)
- Update tensorboard continuous uploader sample (1220746)
1.38.1 (2023-12-13)
- Adding
serving_container_grpc_ports
parameter to Model.upload() method (6a00ed7) - LLM - Added support for model distillation (28925e9)
- Support CMEK for scheduled pipeline jobs. (406595d)
- Release 1.38.1 (537d00e)
1.38.0 (2023-12-11)
- Release GenerativeModel support for Gemini (cd233ef)
- Add explicit constraints for update_ray_cluster (979a4f3)
- Check if dataset exists before creation for Ray on Vertex BigQuery Write (544d6fe)
- LLM - Added support for the
logprobs
,presence_penalty
,frequency_penalty
, andlogit_bias
generation parameters (1449344) - Support
read_index_datapoints
for private network. (c9f7119) - Support custom batch size for Bigframes Tensorflow (7dc8771)
- Update the v1 service definition to add numeric_restricts. (d0c2ffa)
- Verify client and cluster Ray versions match (10c6ad2)
read_index_endpoint
private endpoint support. (3d8835e)- Fix exception message to use vertexai when project is not provided. (0cb1a7b)
- Update test assumption for streaming endpoint of chat-bison@001 (f9a5b69)
- When user is not logged in, throw more intuitive message (a8b24ad)
- Add default value to optional field parameter_values (0a4d772)
1.37.0 (2023-12-05)
- Add additional parameters to Model.upload(). (7b7d7d2)
- Adding support for concurrent explanations (8e2ad75)
- Allow configuring container logging settings on models when deploying. (beae48f)
- Support user provided api endpoint. (92f2b4e)
- Add grpc_ports to UploadModel ModelContainerSpec, add DirectPredict, DirectRawPredict, StreamingPredict, StreamingRawPredict to PredictionService. (6dfbad7)
- Clarify wording when Ray on Vertex cluster is missing head node ip (4a71c8c)
- Fix error when allowed_plugins is set to None. (6f2860a)
- Fixed INTEGER and BOOL parameters casting issue. Fix conversion bug where
INTEGER
andBOOL
parameters are not cast to the correct type. (9a204c4) - Make PipelineJobSchedule propagate labels to created PipelineJobs (a34533f)
- Add upload Tensorboard profile log to Experiment sample. (5780513)
- Update the documentation for the
image_dataset
class (8562368)
1.36.4 (2023-11-16)
- Add
numeric_restricts
to MatchingEngineIndexfind_neighbors()
for querying (6c1f2cc) - Add
remove_datapoints()
toMatchingEngineIndex
. (b86a404) - Add
upsert_datapoints()
toMatchingEngineIndex
to support streaming update index. (7ca484d) - LLM - include error code into blocked response from TextGenerationModel, ChatModel, CodeChatMode, and CodeGenerationModel. (1f81cf2)
- Populate Ray Cluster dashboard_address from proto field (dd4b852)
- add CountTokens API, ComputeTokens API, and ModelContainerSpec features (ba2fb39)
- Add check for empty
encryption_spec_key_name
for MatchingEngineIndexEndpointcreate
. (7740132) - Fix server error due to no
encryption_spec_key_name
in MatchingEngineIndexcreate_tree_ah_index
andcreate_brute_force_index
(595b580)
- Release 1.36.4 (1fd7b4e)
1.36.3 (2023-11-14)
- Add option to not use default tensorboard (a25c669)
- Add preview HyperparameterTuningJob which can be run on persistent resource (0da8c53)
- Add Featurestore Bigtable Serving, Feature Registry v1, November bulk GAPIC release (9f46f7c)
- Fix documentation for obsolete link to GCS formatting (95184de)
- Release 1.36.3 (fdee5cb)
1.36.2 (2023-11-10)
- Add
encryption_spec_key_name
toMatchingEngineIndex
create_tree_ah_index
and (1a9e36f) - Add
encryption_spec_key_name
,enable_private_service_connect
,project_allowlist
to MatchingEngineIndexEndpointcreate
. (750e17b) - Add
index_update_method
to MatchingEngineIndexcreate()
(dcb6205) - Expose max_retry_cnt parameter for Ray on Vertex BigQuery write (568907c)
- LLM - Grounding - Added support for the
disable_attribution
grounding parameter (91e985a) - LLM - Support model evaluation when tuning chat models (
ChatModel
,CodeChatModel
) (755c3f9) - LVM - Added multi-language support for
ImageGenerationModel
(791eff5)
- Async call bug in CodeChatModel.send_message_async method (fcf05cb)
- Add Bigframes remote training example to vertexai README (8b993b3)
- Update the documentation for the
tabular_dataset
class (6f40f1b)
- Release 1.36.2 (01be0c9)
1.36.1 (2023-11-07)
- Add
per_crowding_attribute_neighbor_count
,approx_num_neighbors
,fraction_leaf_nodes_to_search_override
, andreturn_full_datapoint
to MatchingEngineIndexEndpointfind_neighbors
(33c551e) - Add profiler support to tensorboard uploader sdk (be1df7f)
- Add support for
per_crowding_attribute_num_neighbors
approx_num_neighbors
to MatchingEngineIndexEndpointmatch()
(e5c20c3) - Add support for
per_crowding_attribute_num_neighbors
approx_num_neighbors
to MatchingEngineIndexEndpointmatch()
(53d31b5) - Add support for
per_crowding_attribute_num_neighbors
approx_num_neighbors
to MatchingEngineIndexEndpointmatch()
(4e357d5) - Enable grounding to ChatModel send_message and send_message_async methods (d4667f2)
- Enable grounding to TextGenerationModel predict and predict_async methods (b0b4e6b)
- LLM - Added support for the
enable_checkpoint_selection
tuning evaluation parameter (eaf4420) - LLM - Added tuning support for the
*-bison-32k
models (9eba18f) - LLM - Released
CodeChatModel
tuning to GA (621af52)
- Correct class name in system test (b822b57)
- Clean up RoV create_ray_cluster docstring (1473e19)
- Release 1.36.1 (1cde170)
1.36.0 (2023-10-31)
- Add preview count_tokens method to CodeGenerationModel (96e7f7d)
- Allow the users to use extra serialization arguments for objects. (ffbd872)
- Also support unhashable objects to be serialized with extra args (77a741e)
- LLM - Added
count_tokens
support to ChatModel (preview) (01989b1) - LLM - Added new regions for tuning and tuned model inference (3d43497)
- LLM - Added support for async streaming (760a025)
- LLM - Added support for multiple response candidates in code chat models (598d57d)
- LLM - Added support for multiple response candidates in code generation models (0c371a4)
- LLM - Enable tuning eval TensorBoard without evaluation data (eaf5d81)
- LLM - Released
CodeGenerationModel
tuning to GA (87dfe40) - LLM - Support
accelerator_type
in tuning (98ab2f9) - Support experiment autologging when using persistent cluster as executor (c19b6c3)
- Upgrade BigQuery Datasource to use write() interface (7944348)
- Adding setuptools to dependencies for Python 3.12 and above. (afd540d)
- Fix Bigframes tensorflow serializer dependencies (b4cdb05)
- LLM - Fixed the async streaming (41bfcb6)
- LLM - Make tuning use the global staging bucket if specified (d9ced10)
- LVM - Fixed negative prompt in
ImageGenerationModel
(cbe3a0d) - Made the Endpoint prediction client initialization lazy (eb6071f)
- Make sure PipelineRuntimeConfigBuilder is created with the right arguments (ad19838)
- Make sure the models list is populated before indexing (f1659e8)
- Raise exception for RoV BQ Write for too many rate limit exceeded (7e09529)
- Rollback BigQuery Datasource to use do_write() interface (dc1b82a)
1.35.0 (2023-10-10)
- Add serializer.register_custom_command() (639cf10)
- Install Bigframes sklearn dependencies automatically (7aaffe5)
- Install Bigframes tensorflow dependencies automatically (e58689b)
- Install Bigframes torch dependencies automatically (1d65347)
- LLM - Added support for multiple chat response candidates (587df74)
- LLM - Added support for multiple text generation response candidates (c3ae475)
- Duplicate logs in Colab (9b75259)
- LLM - Fixed tuning and evaluation when explicit credentials are specified (188dffe)
- Add probabilistic inference to TiDE and L2L model code samples. (efe88f9)
1.34.0 (2023-10-02)
- Add Model Garden support to vertexai.preview.from_pretrained (f978200)
- Enable vertexai preview persistent cluster executor (0ae969d)
- LLM - Added the
count_tokens
method to the previewTextGenerationModel
andTextEmbeddingModel
classes (6a2f2aa) - LLM - Improved representation for blocked responses (222f222)
- LLM - Released
ChatModel
tuning to GA (7d667f9)
- Create PipelineJobSchedule in same project and location as associated PipelineJob by default (c22220e)
- Add documentation for the preview namespace (69a67f2)
1.33.1 (2023-09-20)
- Lightning trainer fails to be unwrapped in remote training (8271301)
1.33.0 (2023-09-18)
- Add Custom Job support to from_pretrained (8b0add1)
- Added async prediction and explanation support to the
Endpoint
class (e9eb159) - LLM - Added support for async prediction methods (c9c9f10)
- LLM - CodeChat - Added support for
context
(f7feeca) - Release Ray on Vertex SDK Preview (3be36e6)
- Handle Ray image parsing error (41a3a83)
- Vizier - Fixed field existence checks for child params in to_proto(). (d516931)
1.32.0 (2023-09-05)
- LLM - Added
stop_sequences
parameter to streaming methods andCodeChatModel
(d62bb1b) - LLM - Improved the handling of temperature and top_p in streaming (6566529)
- Support bigframes sharded parquet ingestion at remote deserialization (Tensorflow) (a8f85ec)
- Release Vertex SDK Preview (c60b9ca)
- Allow setting default service account (d11b8e6)
- Fix feature update since no LRO is created (468e6e7)
- LLM -
CodeGenerationModel
now supports safety attributes (c2c8a5e) - LLM - Fixed batch prediction on tuned models (2a08535)
- LLM - Fixed the handling of the
TextEmbeddingInput.task_type
parameter. (2e3090b) - Make statistics Optional for TextEmbedding. (7eaa1d4)
1.31.1 (2023-08-24)
- fix: LLM - De-hardcoded the
max_output_tokens
default value for theCodeGenerationModel
(f5a20eb)
1.31.0 (2023-08-21)
- 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 resultstatistics
(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
andheight
parameters fromImageGenerationModel.generate_images
since the service has dropped support for image sizes and aspect ratios (52897e6) - Scheduled pipelines client GA. (62b8b23)
- Generate documentation for tune_model and related class (705e1ea)
- LVM - Added autogenerated documentation for visual models (18e8bb2)
1.30.1 (2023-08-11)
- LLM - Added tuning support for
chat-bison
models (3a97c52) - LLM - Added tuning support for
codechat-bison
models (af6e455)
- LLM - Fixed the
TextGenerationModel.predict
parameters (f3b25ab)
- Release 1.30.1 (d1c79c4)
1.30.0 (2023-08-10)
- Add model.evaluate() method to Model class (51df86e)
- Add support for providing only text to MultiModalEmbeddingModel.get_embeddings() (38ec40a)
- LLM - Fixed filter in
list_tuned_model_names
(57806fb)
1.29.0 (2023-08-02)
- 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)
- LLM - Fixed
get_tuned_model
for the future models that are nottext-bison
(1adf72b)
- 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)
- LLM - Released the BatchPrediction to GA for TextGenerationModel (701c3a2)
- LLM - Support tuning in the "us-central1" location (4aa7745)
- 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)
- Fixed a docstring for train_steps (1f55b05)
- Release 1.28.1 (8ebf22e)
1.28.0 (2023-07-08)
- LLM - Released the Chat models to GA (22aa26d)
1.27.1 (2023-07-06)
- Add sdk support for xai example-based explanations (f9ca1d5)
- Release 1.27.1 (2159f29)
1.27.0 (2023-06-30)
- 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)
- 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)
- 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)
- 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)
- 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)
- Release 1.26.1 (42567d2)
- Update scheduled pipelines client wait() docstring. (a7d92e5)
1.26.0 (2023-06-07)
- 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)
- 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)
- Correct text embedding model ID docstring (8824629)
- LLM - Fixed the rendering of the example usage code blocks. (eaaee28)
1.25.0 (2023-05-09)
- 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)
- 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)
- 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)
- Support timestamp in Vertex SDK write_feature_values() (4b0722c)
- Add Time series Dense Encoder (TiDE) model code sample. (8e91a58)
- Fix docstring formatting for exceptions (d75322c)
- Release 1.24.1 (cf633a2)
1.24.0 (2023-04-12)
- 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)
- Adding previously created PrivateEndpoint network parameter in Model deploy helper method (3e1b206)
- 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)
- 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)
- Added missing comma in README (8cb4377)
1.22.1 (2023-02-28)
- 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)
- Add temporal fusion transformer (TFT) model code sample. (8ddc062)
- samples: Add samples for autologging (f8052b8)
- Release 1.22.1 (ed4c0b1)
1.22.0 (2023-02-16)
- 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)
- 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)
- 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)
- 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)
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)
- Adds the temporal fusion transformer (TFT) forecasting job (99313e0)
- Reraise exceptions from API calls (d72bc83)
- samples: Feature Store: Streaming ingestion code sample and test (bc9e2cf)
1.19.1 (2022-12-08)
- Add explanationSpec to TrainingPipeline-based custom jobs (957703f)
- 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)
- 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)
- Release 1.19.1 (f01867f)
1.19.0 (2022-11-17)
- 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)
- Correct data file gcs path for import_data_text_sentiment_analysis_sample test (86df4b5)
- Print error for schema classes (13e2165)
- Update README with new link for AI Platform API (35b83d9)
1.18.3 (2022-11-01)
- Add a sample for get_experiment_run_artifacts (7266352)
1.18.3 (2022-10-31)
- Add a sample for get_experiment_run_artifacts (7266352)
1.18.2 (2022-10-20)
- 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)
- 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)
1.18.0 (2022-10-03)
- 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)
- 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)
1.17.1 (2022-09-15)
- 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)
1.17.0 (2022-09-07)
- 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)
- 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)
- 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)
- 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)
1.16.0 (2022-07-27)
- 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)
- 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)
- 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)
- deps: require google-api-core>=1.32.0,>=2.8.0 (#1512) (6d09dee)
- Unbreak aiplatform.Experiment.create (#1509) (558c141)
1.15.0 (2022-06-29)
- 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)
- 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)
- 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)
- 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)
1.13.1 (2022-05-26)
- add batch_size kwarg for batch prediction jobs (#1194) (50bdb01)
- add update endpoint (#1162) (0ecfe1e)
- support autoscaling metrics when deploying models (#1197) (095717c)
- check in service proto file (#1174) (5fdf151)
- regenerate pb2 files using grpcio-tools (#1394) (406c868)
1.13.0 (2022-05-09)
- 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)
- fix type in docstring for map fields (847ad78)
1.12.1 (2022-04-20)
- Add endpoind_id arg to Endpoint#create (#1168) (4c21993)
- add ModelEvaluation support (#1167) (10f95cd)
- endpoint.create => aiplatform.Endpoint.create (#1153) (1122a26)
- update changelog headers (#1164) (c1e899d)
- update model code snippet order in README (#1154) (404d7f1)
1.12.0 (2022-04-07)
- 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
toBatchPredictionJob
inbatch_prediction_job.proto
(#1084) (b7a5177)
- 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)
- 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)
- 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)
- 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)
- 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)
- _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)
- Fixed BigQuery datasets that have colon in URI (#855) (153578f)
- Fixed integration test for model.upload (#975) (0ca3747)
- rename teardown fixture (#1004) (fcd0096)
- samples: replace deprecated fields in create_training_pipeline_tabular_forecasting_sample.py (#981) (9ebc972)
1.9.0 (2021-12-29)
- 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)
- 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)
- 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)
- Update references to containers and notebook samples. (#890) (67fa1f1)
- Updated docstrings with exception error classes (#894) (f9aecd2)
1.8.0 (2021-12-03)
- 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)
- Import error for cloud_profiler (#869) (0f124e9)
- Support multiple instances in custom predict sample (#857) (8cb4839)
- 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)
- add parameters_value in PipelineJob for schema > 2.0.0 (#817) (900a449)
- exclude support for python 3.10 (#831) (0301a1d)
1.7.0 (2021-11-06)
- Adds support for
google.protobuf.Value
pipeline parameters in theparameter_values
field (#807) (c97199d) - Adds support for
google.protobuf.Value
pipeline parameters in theparameter_values
field (#808) (726b620) - PipelineJob switch to v1 API from v1beta1 API (#750) (8db7e0c)
- Correct PipelineJob credentials description (#816) (49aaa87)
- Fixed docstrings for Dataset in AutoMLForecastingTrainingJob (760887b)
- 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)
- 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)
- 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)
1.6.1 (2021-10-25)
- 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)
- cast resource labels to dict type (#783) (255edc9)
- Remove sync parameter from create_endpoint_sample (#695) (0477f5a)
1.6.0 (2021-10-12)
- 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)
- 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)
- #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)
- Update milli node_hours for image training (#663) (64768c3)
- XAI Metadata compatibility with Model.upload (#705) (f0570cb)
1.4.2 (2021-09-10)
1.4.1 (2021-09-07)
- 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
1.4.0 (2021-08-30)
- 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)
- 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)
- 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)
- 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)
1.2.0 (2021-07-14)
- 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)
- 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)
- release 1.1.1 (1a38ce2)
1.1.0 (2021-06-17)
- 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)
- 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)
- changes product name to Vertex AI (fdc968f)
- correct link to fieldmask (fdc968f)
- removes tinyurl links (fdc968f)
1.0.1 (2021-05-21)
1.0.0 (2021-05-19)
- add custom and hp tuning (#388) (aab9e58)
- add tensorboard support to custom job and hyperparameter tuning job (#404) (fa9bc39)
0.9.0 (2021-05-17)
- 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)
- deps: add packaging requirement (#392) (47c1530)
- enable aiplatform unit tests (dcc459d)
- rollback six to 1.15 (#391) (066624b)
0.8.0 (2021-05-11)
- 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)
- 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)
0.7.0 (2021-04-14)
- 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)
- 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)
0.5.1 (2021-03-01)
- 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)
0.5.0 (2021-02-17)
- 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)
- 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)
- 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)