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@ -40,7 +40,7 @@ of the optimization results in table and graph forms.
|`--pool-period-min`|The time between two consecutive polls (minutes).|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--total-max-jobs`|The total maximum jobs for the optimization process. The default value is `None` for unlimited.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--min-iteration-per-job`|The minimum iterations (of the objective metric) per single job.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--max-iteration-per-job`|The maximum iterations (of the objective metric) per single job. When maximum iterations is exceeded, the job is aborted.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--max-iteration-per-job`|The maximum iterations (of the objective metric) per single job. When iteration maximum is exceeded, the job is aborted.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--save-top-k-tasks-only`| Keep only the top \<k\> performing tasks, and archive the rest of the experiments. Input `-1` to keep all tasks. Default: `10`.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--time-limit-per-job`|Maximum execution time per single job in minutes. When time limit is exceeded, the job is aborted. Default: no time limit.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|

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@ -45,7 +45,7 @@ to automatically sync local configurations with a remote session.
## How it Works
ClearML allows to leverage a resource (e.g. GPU or CPU machine) by utilizing the [ClearML Agent](../clearml_agent.md).
ClearML allows you to leverage a resource (e.g. GPU or CPU machine) by utilizing the [ClearML Agent](../clearml_agent.md).
A ClearML Agent runs on a target machine, and ClearML Session instructs it to execute the Jupyter / VS Code
server to develop remotely.
After entering a `clearml-session` command with all specifications:

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@ -248,7 +248,7 @@ task_filter={
See [`Task.get_tasks`](../references/sdk/task.md#taskget_tasks) for all `task_filter` options.
### Tag Filters
The tags field supports advanced queries through combining tag names and operators into a list.
The `tags` field supports advanced queries through combining tag names and operators into a list.
The supported operators are:
* `not`
@ -438,7 +438,7 @@ To ensure task reproducibility, ClearML controls the deterministic behaviors of
packages by setting a fixed initial seed.
ClearML uses `1337` as the default initial seed. To set a different value for your task, use the [`Task.set_random_seed`](../references/sdk/task.md#taskset_random_seed)
class method and provide the new seed value, before initializing the task.
class method and provide the new seed value, **before initializing the task**.
You can disable the deterministic behavior entirely by passing `Task.set_random_seed(None)`.

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@ -106,7 +106,7 @@ The host URLs for the ClearML Server are required:
* ClearML Server API server
* ClearML Server file server
These may be localhost, the domain, or a sub-domain of the domain.
These may be localhost, the domain, or a subdomain of the domain.
**To add ClearML settings to an existing ClearML configuration file:**

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@ -34,7 +34,7 @@ ClearML Server also comes with a [services agent](../clearml_agent.md#services-m
## Deployment
The ClearML Server can be deployed in any of the formats listed below. Once deployed, configure the server for web login
authentication, sub-domains, and load balancers, and use any of its many configuration settings.
authentication, subdomains, and load balancers, and use any of its many configuration settings.
**To deploy your own ClearML Server:**
@ -46,7 +46,7 @@ authentication, sub-domains, and load balancers, and use any of its many configu
[Windows 10](clearml_server_win.md)
* [Kubernetes using Helm](clearml_server_kubernetes_helm.md)
1. Optionally, [configure ClearML Server](clearml_server_config.md) for additional features, including sub-domains and load balancers,
1. Optionally, [configure ClearML Server](clearml_server_config.md) for additional features, including subdomains and load balancers,
web login authentication, and the non-responsive task watchdog.
1. [Configure ClearML for ClearML Server](clearml_config_for_clearml_server.md)

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@ -8,7 +8,7 @@ This documentation page applies to deploying your own open source ClearML Server
This page describes the ClearML Server [deployment](#clearml-server-deployment-configuration) and [feature](#clearml-server-feature-configurations) configurations. Namely, it contains instructions on how to configure ClearML Server for:
* [Sub-domains and load balancers](#sub-domains-and-load-balancers) - An AWS load balancing example
* [Subdomains and load balancers](#subdomains-and-load-balancers) - An AWS load balancing example
* [Opening Elasticsearch, MongoDB, and Redis for External Access](#opening-elasticsearch-mongodb-and-redis-for-external-access)
* [Web login authentication](#web-login-authentication) - Create and manage users and passwords
* [Using hashed passwords](#using-hashed-passwords) - Option to use hashed passwords instead of plain-text passwords
@ -23,7 +23,7 @@ Using the latest version of ClearML Server is recommended.
## ClearML Server Deployment Configuration
ClearML Server supports two deployment configurations: single IP (domain) and sub-domains.
ClearML Server supports two deployment configurations: single IP (domain) and subdomains.
### Single IP (Domain) Configuration
@ -33,23 +33,23 @@ Single IP (domain) with the following open ports:
* API service on port `8008`
* File storage service on port `8081`
### Sub-domain Configuration
### Subdomain Configuration
Sub-domain configuration with default http/s ports (`80` or `443`):
Subdomain configuration with default http/s ports (`80` or `443`):
* Web application on sub-domain: `app.*.*`
* API service on sub-domain: `api.*.*`
* File storage service on sub-domain: `files.*.*`
* Web application on subdomain: `app.*.*`
* API service on subdomain: `api.*.*`
* File storage service on subdomain: `files.*.*`
When [configuring sub-domains](#sub-domains-and-load-balancers) for ClearML Server, they will map to the ClearML Server's
When [configuring subdomains](#subdomains-and-load-balancers) for ClearML Server, they will map to the ClearML Server's
internally configured ports for the Dockers. As a result, ClearML Server Dockers remain accessible if, for example,
some type of port forwarding is implemented.
:::important
``app``, ``api``, and ``files`` as the sub-domain labels must be used.
``app``, ``api``, and ``files`` as the subdomain labels must be used.
:::
For example, a domain is called `mydomain.com`, and a sub-domain named `clearml.mydomain.com` is created, use the following:
For example, a domain is called `mydomain.com`, and a subdomain named `clearml.mydomain.com` is created, use the following:
* `app.clearml.mydomain.com` (web server)
* `api.clearml.mydomain.com` (API server)
@ -156,7 +156,7 @@ the default secret for the system's apiserver component can be overridden by set
### Sub-domains and Load Balancers
### Subdomains and Load Balancers
The following example, which is based on AWS load balancing, demonstrates the configuration:

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@ -85,7 +85,7 @@ title: FAQ
**ClearML Server Configuration**
* [How do I configure ClearML Server for sub-domains and load balancers?](#sub-domains)
* [How do I configure ClearML Server for subdomains and load balancers?](#subdomains)
* [Can I add web login authentication to ClearML Server?](#web-auth)
* [Can I modify a non-responsive task settings?](#watchdog)
@ -868,9 +868,9 @@ If you are using SELinux, run the following command (see this [discussion](https
## ClearML Server Configuration
**How do I configure ClearML Server for sub-domains and load balancers?** <a id="sub-domains"></a>
**How do I configure ClearML Server for subdomains and load balancers?** <a id="subdomains"></a>
For detailed instructions, see [Configuring Sub-domains and load balancers](deploying_clearml/clearml_server_config.md#sub-domains-and-load-balancers)
For detailed instructions, see [Configuring Subdomains and load balancers](deploying_clearml/clearml_server_config.md#subdomains-and-load-balancers)
on the "Configuring Your Own ClearML Server" page.
<br/>

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@ -106,7 +106,7 @@ Configurations can be viewed in web UI experiment pages, in the **CONFIGURATION*
The configuration panel is split into three sections according to type:
- **User Properties** - Modifiable section that can be edited post-execution.
- **Hyperparameters** - Individual parameters for configuration
- **Configuration Objects** - Usually configuration files (Json / YAML) or Python objects.
- **Configuration Objects** - Usually configuration files (JSON / YAML) or Python objects.
These sections are further broken down into sub-sections based on how the parameters were logged (General / Args / TF_Define / Environment).

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@ -16,7 +16,7 @@ A Logger object is used to do the following:
ClearML supports four types of reports:
- Text - Mostly captured automatically from stdout and stderr but can be logged manually.
- Scalars - Time series data. X-axis is always a sequential number, usually iterations but can be epochs or others.
- Plots - General graphs and diagrams, such as histograms, confusion matrices line plots, and custom plotly charts.
- Plots - General graphs and diagrams, such as histograms, confusion matrices, line plots, and custom plotly charts.
- Debug Samples - Images, audio, and videos. Can be reported per iteration.
![image](../img/fundamentals_logger_results.png)

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@ -52,7 +52,7 @@ To view all projects in the system, use the `Task` class method `get_projects`:
project_list = Task.get_projects()
```
This returns a list of project sorted by last update time.
This returns a list of projects sorted by last update time.
### More Actions