ClearML/clearml-docs
1
0
Fork 0
mirror of https://github.com/clearml/clearml-docs synced 2025-06-26 18:17:44 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity

Restructure docs for platform components and use case clarity (#1048)

Browse Source
This commit is contained in:
Noam Wasersprung
2025-02-23 17:33:55 +02:00
committed by GitHub
parent 535e08efa8
commit 567af28632
128 changed files with 4370 additions and 1404 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
docs/apps/clearml_param_search.md
View File

@@ -34,7 +34,7 @@ of the optimization results in table and graph forms.
|`--objective-metric-sign`| Optimization target, whether to maximize or minimize the value of the objective metric specified. Possible values: "min", "max", "min_global", "max_global". For more information, see [Optimization Objective](#optimization-objective). |<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--objective-metric-title`| Objective metric title to maximize/minimize (e.g. 'validation').|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--optimization-time-limit`|The maximum time (minutes) for the optimization to run. The default is `None`, indicating no time limit.|<img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" />|
|`--optimizer-class`|The optimizer to use. Possible values are: OptimizerOptuna (default), OptimizerBOHB, GridSearch, RandomSearch. For more information, see [Supported Optimizers](../fundamentals/hpo.md#supported-optimizers). |<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--optimizer-class`|The optimizer to use. Possible values are: OptimizerOptuna (default), OptimizerBOHB, GridSearch, RandomSearch. For more information, see [Supported Optimizers](../hpo.md#supported-optimizers). |<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--params-search`|Parameters space for optimization. See more information in [Specifying the Parameter Space](#specifying-the-parameter-space). |<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--params-override`|Additional parameters of the base task to override for this parameter search. Use the following JSON format for each parameter: `{"name": "param_name", "value": <new_value>}`. Windows users, see [JSON format note](#json_note).|<img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" />|
|`--pool-period-min`|The time between two consecutive polls (minutes).|<img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" />|

4
docs/apps/clearml_session.md
View File

@@ -23,7 +23,7 @@ VS Code remote sessions use ports 8878 and 8898 respectively.
## Prerequisites
* `clearml` installed and configured. See [Getting Started](../getting_started/ds/ds_first_steps.md) for details.
* `clearml` installed and configured. See [ClearML Setup](../clearml_sdk/clearml_sdk_setup) for details.
* At least one `clearml-agent` running on a remote host. See [installation](../clearml_agent/clearml_agent_setup.md#installation) for details.
* An SSH client installed on your machine. To verify, open your terminal and execute `ssh`. If you did not receive an
error, you are good to go.
@@ -142,7 +142,7 @@ sessions:
maxServices: 20
```
For more information, see [Kubernetes](../clearml_agent/clearml_agent_deployment.md#kubernetes).
For more information, see [Kubernetes](../clearml_agent/clearml_agent_deployment_k8s.md).
### Installing Requirements

2
docs/apps/clearml_task.md
View File

@@ -11,7 +11,7 @@ line arguments, Python module dependencies, and a requirements.txt file!
## What Is ClearML Task For?
* Launching off-the-shelf code on a remote machine with dedicated resources (e.g. GPU)
* Running [hyperparameter optimization](../fundamentals/hpo.md) on a codebase that is still not in ClearML
* Running [hyperparameter optimization](../hpo.md) on a codebase that is still not in ClearML
* Creating a pipeline from an assortment of scripts, that you need to turn into ClearML tasks
* Running some code on a remote machine, either using an on-prem cluster or on the cloud