mirror of
https://github.com/clearml/clearml-docs
synced 2025-06-26 18:17:44 +00:00
Change terminology (#1028)
This commit is contained in:
@@ -31,11 +31,11 @@ You can view all the task details in the [WebApp](../webapp/webapp_overview.md).
|
||||
|
||||
See an example of CatBoost and ClearML in action [here](../guides/frameworks/catboost/catboost.md).
|
||||
|
||||

|
||||

|
||||
|
||||
## Automatic Logging Control
|
||||
By default, when ClearML is integrated into your CatBoost script, it captures models, and
|
||||
scalars. But, you may want to have more control over what your experiment logs.
|
||||
scalars. But, you may want to have more control over what your task logs.
|
||||
|
||||
To control a task's framework logging, use the `auto_connect_frameworks` parameter of [`Task.init()`](../references/sdk/task.md#taskinit).
|
||||
Completely disable all automatic logging by setting the parameter to `False`. For finer grained control of logged
|
||||
@@ -75,10 +75,10 @@ See more information about explicitly logging information to a ClearML Task:
|
||||
See [Explicit Reporting Tutorial](../guides/reporting/explicit_reporting.md).
|
||||
|
||||
## Remote Execution
|
||||
ClearML logs all the information required to reproduce an experiment on a different machine (installed packages,
|
||||
ClearML logs all the information required to reproduce a task on a different machine (installed packages,
|
||||
uncommitted changes etc.). The [ClearML Agent](../clearml_agent.md) listens to designated queues and when a task is enqueued,
|
||||
the agent pulls it, recreates its execution environment, and runs it, reporting its scalars, plots, etc. to the
|
||||
experiment manager.
|
||||
task manager.
|
||||
|
||||
Deploy a ClearML Agent onto any machine (e.g. a cloud VM, a local GPU machine, your own laptop) by simply running the
|
||||
following command on it:
|
||||
@@ -98,7 +98,7 @@ and shuts down instances as needed, according to a resource budget that you set.
|
||||
Use ClearML's web interface to edit task details, like configuration parameters or input models, then execute the task
|
||||
with the new configuration on a remote machine:
|
||||
|
||||
* Clone the experiment
|
||||
* Clone the task
|
||||
* Edit the hyperparameters and/or other details
|
||||
* Enqueue the task
|
||||
|
||||
|
||||
Reference in New Issue
Block a user