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feat: adding enable_access_logging parameter to Endpoint.deploy() method, minor edit to batch_predict() docstring
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‎.release-please-manifest.json‎

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{
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".": "1.25.0"
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".": "1.24.1"
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}

‎CHANGELOG.md‎

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# Changelog
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## [1.25.0](https://github.com/googleapis/python-aiplatform/compare/v1.24.1...v1.25.0) (2023-05-09)
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### Features
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* Add support for Large Language Models ([866c6aa](https://github.com/googleapis/python-aiplatform/commit/866c6aaf72b9a7a5f6155665f574cc11cf8075f4))
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* Add default TensorBoard support. ([fa7d3a0](https://github.com/googleapis/python-aiplatform/commit/fa7d3a0e3cd5040eb4ab1c3b0df4e494dc84bac3))
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* Add support for find_neighbors/read_index_datapoints in matching engine public endpoint ([e3a87f0](https://github.com/googleapis/python-aiplatform/commit/e3a87f04abf013341fe4f655b96405e27228ffdb))
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* Added the new root `vertexai` package ([fbd03b1](https://github.com/googleapis/python-aiplatform/commit/fbd03b15e9b71cbeeaebc868745a36c892b55c8f))
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### Bug Fixes
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* EntityType RPC update returns the updated EntityType - not an LRO. ([8f9c714](https://github.com/googleapis/python-aiplatform/commit/8f9c7144c152e105924d87abb30aa734af376486))
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* Fix default AutoML Forecasting transformations list. ([77b89c0](https://github.com/googleapis/python-aiplatform/commit/77b89c0151ce3647b8fac8f4e8b6a7f7c07a1192))
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* Fix type hints for `Prediction.predictions`. ([56518f1](https://github.com/googleapis/python-aiplatform/commit/56518f166215761354aba43d78301a11d198daf5))
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* Removed parameter Resume, due to causing confusion and errors. ([c82e0b5](https://github.com/googleapis/python-aiplatform/commit/c82e0b5fb74fe9ba15f9d0f14a441349499ee257))
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## [1.24.1](https://github.com/googleapis/python-aiplatform/compare/v1.24.0...v1.24.1) (2023-04-21)
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‎google/cloud/aiplatform/gapic_version.py‎

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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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__version__ = "1.25.0" # {x-release-please-version}
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__version__ = "1.24.1" # {x-release-please-version}

‎google/cloud/aiplatform/models.py‎

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@@ -753,6 +753,7 @@ def deploy(
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deploy_request_timeout: Optional[float] = None,
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autoscaling_target_cpu_utilization: Optional[int] = None,
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autoscaling_target_accelerator_duty_cycle: Optional[int] = None,
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enable_access_logging=False,
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) -> None:
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"""Deploys a Model to the Endpoint.
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Target Accelerator Duty Cycle.
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Must also set accelerator_type and accelerator_count if specified.
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A default value of 60 will be used if not specified.
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enable_access_logging (bool):
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Whether to enable endpoint access logging. Defaults to False.
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"""
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self._sync_gca_resource_if_skipped()
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deploy_request_timeout=deploy_request_timeout,
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autoscaling_target_cpu_utilization=autoscaling_target_cpu_utilization,
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autoscaling_target_accelerator_duty_cycle=autoscaling_target_accelerator_duty_cycle,
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enable_access_logging=enable_access_logging,
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)
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@base.optional_sync()
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deploy_request_timeout: Optional[float] = None,
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autoscaling_target_cpu_utilization: Optional[int] = None,
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autoscaling_target_accelerator_duty_cycle: Optional[int] = None,
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enable_access_logging=False,
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) -> None:
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"""Deploys a Model to the Endpoint.
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Target Accelerator Duty Cycle.
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Must also set accelerator_type and accelerator_count if specified.
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A default value of 60 will be used if not specified.
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enable_access_logging (bool):
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Whether to enable endpoint access logging. Defaults to False.
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"""
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_LOGGER.log_action_start_against_resource(
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f"Deploying Model {model.resource_name} to", "", self
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deploy_request_timeout=deploy_request_timeout,
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autoscaling_target_cpu_utilization=autoscaling_target_cpu_utilization,
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autoscaling_target_accelerator_duty_cycle=autoscaling_target_accelerator_duty_cycle,
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enable_access_logging=enable_access_logging,
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)
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_LOGGER.log_action_completed_against_resource("model", "deployed", self)
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deploy_request_timeout: Optional[float] = None,
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autoscaling_target_cpu_utilization: Optional[int] = None,
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autoscaling_target_accelerator_duty_cycle: Optional[int] = None,
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enable_access_logging=False,
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) -> None:
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"""Helper method to deploy model to endpoint.
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Optional. Target Accelerator Duty Cycle.
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Must also set accelerator_type and accelerator_count if specified.
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A default value of 60 will be used if not specified.
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enable_access_logging (bool):
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Whether to enable endpoint access logging. Defaults to False.
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Raises:
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ValueError: If only `accelerator_type` or `accelerator_count` is specified.
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model=model.versioned_resource_name,
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display_name=deployed_model_display_name,
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service_account=service_account,
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enable_access_logging=enable_access_logging,
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)
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supports_automatic_resources = (
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deploy_request_timeout: Optional[float] = None,
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autoscaling_target_cpu_utilization: Optional[int] = None,
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autoscaling_target_accelerator_duty_cycle: Optional[int] = None,
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enable_access_logging=False,
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) -> Union[Endpoint, PrivateEndpoint]:
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"""Deploys model to endpoint. Endpoint will be created if unspecified.
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Optional. Target Accelerator Duty Cycle.
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Must also set accelerator_type and accelerator_count if specified.
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A default value of 60 will be used if not specified.
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enable_access_logging (bool):
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Whether to enable endpoint access logging. Defaults to False.
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Returns:
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endpoint (Union[Endpoint, PrivateEndpoint]):
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deploy_request_timeout=deploy_request_timeout,
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autoscaling_target_cpu_utilization=autoscaling_target_cpu_utilization,
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autoscaling_target_accelerator_duty_cycle=autoscaling_target_accelerator_duty_cycle,
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enable_access_logging=enable_access_logging,
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)
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@base.optional_sync(return_input_arg="endpoint", bind_future_to_self=False)
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deploy_request_timeout: Optional[float] = None,
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autoscaling_target_cpu_utilization: Optional[int] = None,
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autoscaling_target_accelerator_duty_cycle: Optional[int] = None,
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enable_access_logging=False,
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) -> Union[Endpoint, PrivateEndpoint]:
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"""Deploys model to endpoint. Endpoint will be created if unspecified.
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Optional. Target Accelerator Duty Cycle.
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Must also set accelerator_type and accelerator_count if specified.
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A default value of 60 will be used if not specified.
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enable_access_logging (bool):
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Whether to enable endpoint access logging. Defaults to False.
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Returns:
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endpoint (Union[Endpoint, PrivateEndpoint]):
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deploy_request_timeout=deploy_request_timeout,
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autoscaling_target_cpu_utilization=autoscaling_target_cpu_utilization,
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autoscaling_target_accelerator_duty_cycle=autoscaling_target_accelerator_duty_cycle,
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enable_access_logging=enable_access_logging,
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)
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_LOGGER.log_action_completed_against_resource("model", "deployed", endpoint)
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When only the project is specified, the Dataset and Table is created.
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When the full table reference is specified, the Dataset must exist and
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table must not exist. Accepted forms: ``bq://projectId`` or
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``bq://projectId.bqDatasetId`` or
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``bq://projectId.bqDatasetId.bqTableId``. If no Dataset is specified,
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``bq://projectId.bqDatasetId``. If no Dataset is specified,
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a new one is created with the name
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``prediction_<model-display-name>_<job-create-time>``
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where the table name is made BigQuery-dataset-name compatible

‎google/cloud/aiplatform/v1/schema/predict/instance/gapic_version.py‎

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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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__version__ = "1.25.0" # {x-release-please-version}
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__version__ = "1.24.1" # {x-release-please-version}

‎google/cloud/aiplatform/v1/schema/predict/instance_v1/gapic_version.py‎

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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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__version__ = "1.25.0" # {x-release-please-version}
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__version__ = "1.24.1" # {x-release-please-version}

‎google/cloud/aiplatform/v1/schema/predict/params/gapic_version.py‎

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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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__version__ = "1.25.0" # {x-release-please-version}
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__version__ = "1.24.1" # {x-release-please-version}

‎google/cloud/aiplatform/v1/schema/predict/params_v1/gapic_version.py‎

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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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__version__ = "1.25.0" # {x-release-please-version}
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__version__ = "1.24.1" # {x-release-please-version}

‎google/cloud/aiplatform/v1/schema/predict/prediction/gapic_version.py‎

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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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__version__ = "1.25.0" # {x-release-please-version}
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__version__ = "1.24.1" # {x-release-please-version}

‎google/cloud/aiplatform/v1/schema/predict/prediction_v1/gapic_version.py‎

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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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__version__ = "1.25.0" # {x-release-please-version}
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__version__ = "1.24.1" # {x-release-please-version}

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