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pollfly
2022-05-19 09:59:10 +03:00
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parent 1b010a79b0
commit f377b140e9
25 changed files with 102 additions and 99 deletions
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docs/guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt.md
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@@ -68,7 +68,7 @@ def job_complete_callback(
## Initialize the Optimization Task
Initialize the Task, which will be stored in **ClearML Server** when the code runs. After the code runs at least once, it
Initialize the Task, which will be stored in ClearML Server when the code runs. After the code runs at least once, it
can be [reproduced](../../../webapp/webapp_exp_reproducing.md) and [tuned](../../../webapp/webapp_exp_tuning.md).
We set the Task type to optimizer, and create a new experiment (and Task object) each time the optimizer runs (`reuse_last_task_id=False`).
@@ -92,7 +92,7 @@ Create an arguments dictionary that contains the ID of the Task to optimize, and
optimizer will run as a service, see [Running as a service](#running-as-a-service).
In this example, an experiment named **Keras HP optimization base** is being optimized. The experiment must have run at
least once so that it is stored in **ClearML Server**, and, therefore, can be cloned.
least once so that it is stored in ClearML Server, and, therefore, can be cloned.
Since the arguments dictionary is connected to the Task, after the code runs once, the `template_task_id` can be changed
to optimize a different experiment.