* feat: SDK support for model monitoring (for models deployed to endpoints; batch prediction use case will be implemented separately)"

* fixing syntax errors

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* resolving merge diff

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* removing sync parameter from MDM job

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* fixing runtime errors

* fixing more runtime errors

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* fixing some more linter errors

* added endpoint path resolution logic

* excluding uninitialized optional arguments for as_proto methods in objective config

* fixing typo in class variable

* adding more upstream error handling

* fixing errors with runtime type checks

* fixed runtime errors in update and pause functions

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* removing unused methods

* fixed job delete method

* removing unused parameter

* addressing some PR comments

* docs clarification

* Update google/cloud/aiplatform/jobs.py

Co-authored-by: sasha-gitg <[email protected]>

* Update google/cloud/aiplatform/jobs.py

Co-authored-by: sasha-gitg <[email protected]>

* Update google/cloud/aiplatform/jobs.py

Co-authored-by: sasha-gitg <[email protected]>

* fixing logic for checking explanation_specs

* chore: system test for model monitoring (#1428)

* chore: adding system test for model monitoring

* debugged system test

* removing extra print statements

* added test coverage for pause resume and delete methods

* added test coverage for model monitoring config for two models

* fixing test bug

* added test coverage for XAI error case

* addressed more PR comments

* addressing remaining comments

* adding more error checking in parse_configs helper function

* minor fix for deployed model ID validation logic

* addressing docs commentes

* addressed more PR comments

* removing runtime errors

* added more documentation

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* addressing PR comments

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* addressing more PR comments

* adding more doc strings

* more fixes

* formatting

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* added more test coverage and changed iterator names for parse_configs function

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* making objective config class non-abstract

* renaming configuration classes

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* Added the Vizier client in the aiplatform folder.

* Copied the pyvizier from the open source vizier.

* Added the Trial in the aiplatform folder.

* Forked the pyvizier from the pyVizier.

* imported the objects from the pyvizier.

* Added the Vizier client and types in the aiplatform init file.

* Made the pyvizier converters compatible with the Vertex SDK proto.

* Forked the framework for the Vertex Vizier from the Open Source Vizier.

* Implemented the interfaces for Study and Trial. Added the unit tests and system tests for them.

* Setup the dependencies for the Vizier.

* Fix the lint error by running the nox -s blacken.

* Fixed the lint errors for the Vizier.

* Made the unit test import the google credentials.

* Disable the coverage check for the pyvizier. It will be imported from the open source vizier.

* Remove the converage dependency to avoid the conflicts.

* Fixing the py-3.9 issue in the sample/module-builder

* Convert the lambda function to avoid the import numpy be called in the confest.py test

* Revert the requirements file.

* Fix the lint error by running the nox -s blacken.

* Fixed the syntax issue in the setup.py

* Setup the local package

* scrube the TODO since it's the documentation ticket.

* Addresses the comments.

* Ran blacken on the test_vizier file.

* Import the OSS in the Vertex SDK.

* Already imported the package from open source vizier. Removing the code copied from oss.

* Import the google-vizier and fix the dependencies for Vertex Vizier.

* Configured the dependency of the google-vizier.

* Ran the nox -s blacken.

* Fixed the lint issue.

* Clean the debugging logs.

* Decouple the Study, Trial and the aiplatform to make the sample test pass.

* Fixed the issue in the system test got an unexpected keyword argument 'credentials'

* Ran the nox -s blacken to format the python file.

* Fixed the unit test failure.

* Add the wrapper to give more error information about the vizier import error.

Co-authored-by: Rosie Zou <[email protected]>

… google.Forecasting Metrics (#1549)

* Add google.ClassificationMetrics, google.RegressionMetrics, and google.ForecastingMetrics Artifact types to metadata schema with unit tests.

* fix implicit false

* Fix typo

* Running nox -s blacken and nox -s lint

* fix typo in unit test

Co-authored-by: sina chavoshi <[email protected]>

…ng (#1544)

* feat: added support for conditional parameters in hyperparameter tuning

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* fixing unit tests

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* fixed all failing tests

* addressed PR comments

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* feat: SDK feature store samples (create/delete fs)

* feat: adding to conftest.py

* docs(samples): fixed testing

* docs(samples): fixed testing

* docs(samples): fixed testing

* docs(samples) added changes

* docs(samples): style issues

* Update samples/model-builder/create_featurestore_sample_test.py

Co-authored-by: Morgan Du <[email protected]>

* Update samples/model-builder/test_constants.py

Co-authored-by: Morgan Du <[email protected]>

* Update samples/model-builder/create_featurestore_sample_test.py

Co-authored-by: Morgan Du <[email protected]>

* chore: release 1.16.1

Co-authored-by: Morgan Du <[email protected]>

* feat: add a DeploymentResourcePool API resource_definition
feat: add shared_resources for supported prediction_resources

PiperOrigin-RevId: 461971827

Source-Link: googleapis/googleapis@0b24d03

Source-Link: googleapis/googleapis-gen@d3298e7
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* chore(bazel): update protobuf to v3.21.3

chore(bazel): update gax-java to 2.18.4

PiperOrigin-RevId: 463115700

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Source-Link: googleapis/googleapis-gen@6a4d9d9
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* feat: add DeploymentResourcePool in aiplatform v1beta1 deployment_resource_pool.proto
feat: add DeploymentResourcePoolService in aiplatform v1beta1 deployment_resource_pool_service.proto
feat: add SHARED_RESOURCES to DeploymentResourcesType in aiplatform v1beta1 model.proto

PiperOrigin-RevId: 463147866

Source-Link: googleapis/googleapis@6276461

Source-Link: googleapis/googleapis-gen@57665f4
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* feat: making network arg optional in aiplatform v1beta1 custom_job.proto
feat: DeploymentResourcePool and DeployementResourcePoolService added to aiplatform v1beta1 model.proto (cl/463147866)
docs: doc edits to aiplatform v1beta1 job_service.proto, model_service.proto, pipeline_service.proto, saved_query.proto, study.proto, types.proto

PiperOrigin-RevId: 463932106

Source-Link: googleapis/googleapis@efbe03d

Source-Link: googleapis/googleapis-gen@e012128
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* feat: making network arg optional in aiplatform v1 custom_job.proto
feat: added SHARED_RESOURCES enum to aiplatform v1 model.proto
docs: doc edits to aiplatform v1 dataset_service.proto, job_service.proto, model_service.proto, pipeline_service.proto, saved_query.proto, study.proto, types.proto

PiperOrigin-RevId: 463932566

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* feat: support case insensitive match on search facets
feat: allow disabling spell check in search requests
feat: allow adding labels in search requests
feat: allow returning min/max values on search numeric facets
feat: allow using serving configs as an alias of placements
feat: allow enabling recommendation filtering on custom attributes
feat: return output BigQuery table on product / event export response
docs: keep the API doc up-to-date with recent changes

PiperOrigin-RevId: 463980128

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Source-Link: googleapis/googleapis-gen@e3d1296
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* feat: support case insensitive match on search facets
feat: allow to return min/max values on search numeric facets
feat: allow to use serving configs as an alias of placements
docs: keep the API doc up-to-date with recent changes

PiperOrigin-RevId: 464560246

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This reverts commit 5430319.

Release-As: 1.16.1

#1565)

* chore: fix resource deletion issues with model monitoring system tests

* syntax fix

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* removing GAPIC job name checks

* removing test coverage for pause and resume

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