* fix: unblock builds (#132)

* chore: Update README with Experimental verbiage (#131)

* fix: Fixed comments (#116)

Co-authored-by: Ivan Cheung <[email protected]>

* feat: Implements a wrapped client that instantiates the client at every API invocation (#139)

* feat: Added optional model args for custom training (#129)

* Added optional model args

* fix: Removed etag

* fix: Added predict schemata and fixed type error

* fix: Added description and fixed predict_schemata

* Added _model_serving_container_command, _model_serving_container_args,                 env=self._model_serving_container_environment_variables and _model_serving_container_ports

* fix: Ran linter

* fix: Added tests for model_instance_schema_uri, model_parameters_schema_uri and model_prediction_schema_uri

* fix: Fixed env and ports and added tests

* fix: Removed model_labels

* fix: Moved container spec creation into init function

* fix: Fixed docstrings

* fix: Moved import to be alphabetical

* fix: Moved model creation to init function

* fix: Fixed predict_schemata

* fix: simplified predict schemata

* fix: added linter

* fix: Fixed trailing comma

* fix: Removed CustomTrainingJob private fields

* fix: Fixed model tests

* fix: Set managed_model to None

Co-authored-by: Ivan Cheung <[email protected]>

* Fix: refactor class constructor for retrieving resource (#125)

* Added property and abstract method _getter_method and _resource_noun, implemented method _get_gca_resource to class AiPlatformResourceNoun; Added _resource_noun, _getter_method, to Dataset, Model, Endpoint, subclasses of _Job, _TrainingJob, refactored (_)get_* and utils.full_resource_name in class constructor to self._get_gca_resource to Dataset, Model, Endpoint, _Job

* Added return value in _get_gca_resource, added method _sync_gca_resource in AiPlatformResourceNoun class; removed job_type, updated status method with _sync_gca_resource in _Job class

* fix: added return type and lint issues

* fix: merge conflict issue with models.py

* fix: F401 'abc' imported but unused

* chore: merge main into dev (#154)

* test: Dataset integration tests (#126)

* Add dataset.metadata.text to schemas

* Add first integation tests, Dataset class

* Make teardown work if test fails, update asserts

* Change test folder name, enable system tests

* Hide test_base, test_end_to_end for Kokoro CI bug

* Add GCP Project env var to Kokoro presubmit cfg

* Restore presubmit cfg, drop --quiet in unit tests

* Restore test_base, test_end_to_end to find timeout

* Skip tests depending on persistent resources

* Use auth default creds for system tests

* Drop unused import os

* feat: specialized dataset classes, fix: datasets refactor (#153)

* feat: Refactored Dataset by removing intermediate layers

* Added image_dataset and tabular_dataset subclass

* Moved metadata_schema_uri responsibility to subclass to enable forecasting

* Moved validation logic for tabular into Dataset._create_tabular

* Added validation in image_dataset and fixed bounding_box schema error

* Removed import_config

* Fixed metadata_schema_uri

* Fixed import and subclasses

* Added EmptyNontabularDatasource

* change import_metadata to ioformat

* added datasources.py

* added support of multiple gcs_sources

* fix: default (empty) dataset_metadata need to be set to {}, not None

* 1) imported datasources 2) added _support_metadata_schema_uris and _support_import_schema_classes 3) added getter and setter/validation for resource_metadata_schema_uri, metadata_schema_uri, and import_schema_uri 4) fixed request_metadata, data_item_labels 5) encapsulated dataset_metadata, and import_data_configs 6) added datasource configuration logic

* added image_dataset.py and tabular_dataset.py

* fix: refactor - create datasets modeule

* fix: cleanup __init__.py

* fix: data_item_labels

* fix: docstring

* fix:
- changed NonTabularDatasource.dataset_metadata default to None
- updated NonTabularDatasource docstring
- changed gcs_source type hint with Union
- changed _create_and_import to _create_encapsulated with datasource
- removed subclass.__init__ and irrelevant parameters in create

* fix: import the module instead of the classes for datasources

* fix: removed all validation for import_schema_uri

* fix: set parameter default to immutable

* fix: replaced Datasource / DatasourceImportable abstract class instead of a concrete type

* fix: added examples for gcs_source

* fix:
- remove Sequence from utils.py
- refactor datasources.py to _datasources.py
- change docstring format to arg_name (arg_type): convention
- change and include the type signature _supported_metadata_schema_uris
- change _validate_metadata_schema_uri
- refactor _create_encapsulated to _create_and_import
- refactor to module level imports
- add tests for ImageDataset and TabularDataset

* fix: remove all labels

* fix: remove Optional in docstring, add example for bq_source

* test: add import_data raise for tabular dataset test

* fix: refactor datasource creation with create_datasource

* fix: lint

Co-authored-by: Ivan Cheung <[email protected]>

* feat: Add AutoML Image Training Job class (#152)

* Add AutoMLImageTrainingJob, tests, constants

* Address reviewer comments

* feat: Add custom container support (#164)

* chore: merge main into dev (#162)

* fix: suppress no project id warning (#160)

* fix: suppress no project id warning

* fix: temporary suppress logging.WARNING and set credentials as google.auth.default credentials

* fix: move default credentials config to credentials property

* fix: add property setter for credentials to avoid everytime reset

* fix: Fixed wrong key value for multilabel (#168)

Co-authored-by: Ivan Cheung <[email protected]>

* feat: Add delete methods, add list_models and undeploy_all for Endpoint class (#165)

* Endpoint list_models, delete, undeploy_all WIP

* Finish delete + undeploy methods, tests

* Add global pool teardowns for test timeout issue

* Address reviewer comments, add async support

* fix: Fixed bug causing training failure for object detection (#171)

Co-authored-by: Ivan Cheung <[email protected]>

* fix: Support intermediary BQ Table for Custom Training (#166)

* chore: add AutoMLImageTrainingJob to aiplatform namespace (#173)

* fix: Unblock build (#174)

* fix: default credentials config related test failures (#167)

* fix: suppress no project id warning

* fix: temporary suppress logging.WARNING and set credentials as google.auth.default credentials

* fix: move default credentials config to credentials property

* fix: add property setter for credentials to avoid everytime reset

* fix: tests for set credentials to default when default not provided

* fix: change credentials with initializer default when not provided in AiPlatformResourceNoun

* fix: use credential mock in tests

* fix: lint

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

Co-authored-by: Ivan Cheung <[email protected]>
Co-authored-by: Ivan Cheung <[email protected]>
Co-authored-by: Morgan Du <[email protected]>
Co-authored-by: Vinny Senthil <[email protected]>

* fix: unblock builds (#132)

* chore: Update README with Experimental verbiage (#131)

* fix: Fixed comments (#116)

Co-authored-by: Ivan Cheung <[email protected]>

* feat: Implements a wrapped client that instantiates the client at every API invocation (#139)

* feat: Added optional model args for custom training (#129)

* Added optional model args

* fix: Removed etag

* fix: Added predict schemata and fixed type error

* fix: Added description and fixed predict_schemata

* Added _model_serving_container_command, _model_serving_container_args,                 env=self._model_serving_container_environment_variables and _model_serving_container_ports

* fix: Ran linter

* fix: Added tests for model_instance_schema_uri, model_parameters_schema_uri and model_prediction_schema_uri

* fix: Fixed env and ports and added tests

* fix: Removed model_labels

* fix: Moved container spec creation into init function

* fix: Fixed docstrings

* fix: Moved import to be alphabetical

* fix: Moved model creation to init function

* fix: Fixed predict_schemata

* fix: simplified predict schemata

* fix: added linter

* fix: Fixed trailing comma

* fix: Removed CustomTrainingJob private fields

* fix: Fixed model tests

* fix: Set managed_model to None

Co-authored-by: Ivan Cheung <[email protected]>

* Fix: refactor class constructor for retrieving resource (#125)

* Added property and abstract method _getter_method and _resource_noun, implemented method _get_gca_resource to class AiPlatformResourceNoun; Added _resource_noun, _getter_method, to Dataset, Model, Endpoint, subclasses of _Job, _TrainingJob, refactored (_)get_* and utils.full_resource_name in class constructor to self._get_gca_resource to Dataset, Model, Endpoint, _Job

* Added return value in _get_gca_resource, added method _sync_gca_resource in AiPlatformResourceNoun class; removed job_type, updated status method with _sync_gca_resource in _Job class

* fix: added return type and lint issues

* fix: merge conflict issue with models.py

* fix: F401 'abc' imported but unused

* chore: merge main into dev (#154)

* test: Dataset integration tests (#126)

* Add dataset.metadata.text to schemas

* Add first integation tests, Dataset class

* Make teardown work if test fails, update asserts

* Change test folder name, enable system tests

* Hide test_base, test_end_to_end for Kokoro CI bug

* Add GCP Project env var to Kokoro presubmit cfg

* Restore presubmit cfg, drop --quiet in unit tests

* Restore test_base, test_end_to_end to find timeout

* Skip tests depending on persistent resources

* Use auth default creds for system tests

* Drop unused import os

* feat: specialized dataset classes, fix: datasets refactor (#153)

* feat: Refactored Dataset by removing intermediate layers

* Added image_dataset and tabular_dataset subclass

* Moved metadata_schema_uri responsibility to subclass to enable forecasting

* Moved validation logic for tabular into Dataset._create_tabular

* Added validation in image_dataset and fixed bounding_box schema error

* Removed import_config

* Fixed metadata_schema_uri

* Fixed import and subclasses

* Added EmptyNontabularDatasource

* change import_metadata to ioformat

* added datasources.py

* added support of multiple gcs_sources

* fix: default (empty) dataset_metadata need to be set to {}, not None

* 1) imported datasources 2) added _support_metadata_schema_uris and _support_import_schema_classes 3) added getter and setter/validation for resource_metadata_schema_uri, metadata_schema_uri, and import_schema_uri 4) fixed request_metadata, data_item_labels 5) encapsulated dataset_metadata, and import_data_configs 6) added datasource configuration logic

* added image_dataset.py and tabular_dataset.py

* fix: refactor - create datasets modeule

* fix: cleanup __init__.py

* fix: data_item_labels

* fix: docstring

* fix:
- changed NonTabularDatasource.dataset_metadata default to None
- updated NonTabularDatasource docstring
- changed gcs_source type hint with Union
- changed _create_and_import to _create_encapsulated with datasource
- removed subclass.__init__ and irrelevant parameters in create

* fix: import the module instead of the classes for datasources

* fix: removed all validation for import_schema_uri

* fix: set parameter default to immutable

* fix: replaced Datasource / DatasourceImportable abstract class instead of a concrete type

* fix: added examples for gcs_source

* fix:
- remove Sequence from utils.py
- refactor datasources.py to _datasources.py
- change docstring format to arg_name (arg_type): convention
- change and include the type signature _supported_metadata_schema_uris
- change _validate_metadata_schema_uri
- refactor _create_encapsulated to _create_and_import
- refactor to module level imports
- add tests for ImageDataset and TabularDataset

* fix: remove all labels

* fix: remove Optional in docstring, add example for bq_source

* test: add import_data raise for tabular dataset test

* fix: refactor datasource creation with create_datasource

* fix: lint

Co-authored-by: Ivan Cheung <[email protected]>

* feat: Add AutoML Image Training Job class (#152)

* Add AutoMLImageTrainingJob, tests, constants

* Address reviewer comments

* feat: Add custom container support (#164)

* chore: merge main into dev (#162)

* fix: suppress no project id warning (#160)

* fix: suppress no project id warning

* fix: temporary suppress logging.WARNING and set credentials as google.auth.default credentials

* fix: move default credentials config to credentials property

* fix: add property setter for credentials to avoid everytime reset

* fix: Fixed wrong key value for multilabel (#168)

Co-authored-by: Ivan Cheung <[email protected]>

* feat: Add delete methods, add list_models and undeploy_all for Endpoint class (#165)

* Endpoint list_models, delete, undeploy_all WIP

* Finish delete + undeploy methods, tests

* Add global pool teardowns for test timeout issue

* Address reviewer comments, add async support

* fix: Fixed bug causing training failure for object detection (#171)

Co-authored-by: Ivan Cheung <[email protected]>

* fix: Support intermediary BQ Table for Custom Training (#166)

* chore: add AutoMLImageTrainingJob to aiplatform namespace (#173)

* fix: Unblock build (#174)

* fix: default credentials config related test failures (#167)

* fix: suppress no project id warning

* fix: temporary suppress logging.WARNING and set credentials as google.auth.default credentials

* fix: move default credentials config to credentials property

* fix: add property setter for credentials to avoid everytime reset

* fix: tests for set credentials to default when default not provided

* fix: change credentials with initializer default when not provided in AiPlatformResourceNoun

* fix: use credential mock in tests

* fix: lint

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

* Fix: pass bq_destination to input data config when using training script (#181)

* fix: pass bigquery destination

* fix: add tests and formatting

Co-authored-by: Ivan Cheung <[email protected]>
Co-authored-by: Ivan Cheung <[email protected]>
Co-authored-by: Morgan Du <[email protected]>
Co-authored-by: Vinny Senthil <[email protected]>