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16
docs/fundamentals/hpo.md
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@ -121,14 +121,14 @@ optimization.
## Optimizer Execution Options
The `HyperParameterOptimizer` provides options to launch the optimization tasks locally or through a ClearML [queue](agents_and_queues.md#what-is-a-queue).
Start a `HyperParameterOptimizer` instance using either [`HyperParameterOptimizer.start`](../references/sdk/hpo_optimization_hyperparameteroptimizer.md#start)
or [`HyperParameterOptimizer.start_locally`](../references/sdk/hpo_optimization_hyperparameteroptimizer.md#start_locally).
Both methods run the optimizer controller locally. The `start` method launches the base task clones through a queue
specified when instantiating the controller, while `start_locally` runs the tasks locally.
Start a `HyperParameterOptimizer` instance using either [`HyperParameterOptimizer.start()`](../references/sdk/hpo_optimization_hyperparameteroptimizer.md#start)
or [`HyperParameterOptimizer.start_locally()`](../references/sdk/hpo_optimization_hyperparameteroptimizer.md#start_locally).
Both methods run the optimizer controller locally. `start()` launches the base task clones through a queue
specified when instantiating the controller, while `start_locally()` runs the tasks locally.
:::tip Remote Execution
You can also launch the optimizer controller through a queue by using the [`Task.execute_remotely`](../references/sdk/task.md#execute_remotely)
method before starting the optimizer.
You can also launch the optimizer controller through a queue by using [`Task.execute_remotely()`](../references/sdk/task.md#execute_remotely)
before starting the optimizer.
:::
@ -147,5 +147,9 @@ ClearML also provides `clearml-param-search`, a CLI utility for managing the hyp
## UI Application
:::info Pro Plan Offering
The ClearML HPO App is available under the ClearML Pro plan
:::
ClearML provides the [Hyperparameter Optimization GUI application](../webapp/applications/apps_hpo.md) for launching and
managing the hyperparameter optimization process.

9
docs/release_notes/ver_1_12.md
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@ -12,17 +12,16 @@ the instructions [here](https://github.com/allegroai/clearml/tree/master/docs/er
:::
**New Features**
* Add `include_archive` parameter to `Dataset.list_datasets()`: include archived datasets in list [ClearML GitHub issue #1069](https://github.com/allegroai/clearml/issues/1069)
* Add `include_archive` parameter to `Dataset.list_datasets()`: include archived datasets in list [ClearML GitHub issue #1067](https://github.com/allegroai/clearml/issues/1067)
* Add support to specify the multipart chunk size and threshold using the `aws.boto3.multipart_chunksize` and
`aws.boto3.multipart_threshold` configuration options in the clearml.conf [ClearML GitHub issue #1059](https://github.com/allegroai/clearml/issues/1059)
`aws.boto3.multipart_threshold` configuration options in the clearml.conf [ClearML GitHub issue #1058](https://github.com/allegroai/clearml/issues/1058)
* Add `PipelineController.get_pipeline()` for retrieving previously run pipelines.
**Bug Fixes**
* Fix `continue_last_task=0` is ignored in pipelines run with `retry_on_failure` [ClearML GitHub issue #1054](https://github.com/allegroai/clearml/issues/1054)
* Fix AWS driver issues: [ClearML GitHub issue #1000](https://github.com/allegroai/clearml/issues/1000)
* Fix AWS driver issues: [ClearML GitHub PR #1000](https://github.com/allegroai/clearml/pull/1000)
* Fix credential authentication failure when attempting to use token
* Fix instantiation within VPC without AvailabilityZones
* Fix Error accessing GCP artifacts when using special characters in task name [ClearML GitHub issue #1051](https://github.com/allegroai/clearml/issues/1051)
* Fix `continue_last_task=0` is ignored in pipelines run with `retry_on_failure` [ClearML GitHub issue #1054](https://github.com/allegroai/clearml/issues/1054)
* Fix `Task.connect_configuration()` doesn't handle dictionaries with special characters
* Fix pipeline steps created with `PipelineDecorator` aren't cached
* Fix `Task.get_by_name()` doesn't return the most recent task when multiple tasks have same name