ClearML/clearml-docs
1
0
Fork 0
mirror of https://github.com/clearml/clearml-docs synced 2025-04-10 16:06:22 +00:00
Code Issues Actions 1 Packages Projects Releases Wiki Activity

Reformat ClearML Agent reference (#461)

Browse Source
This commit is contained in:
pollfly 2023-01-31 14:48:17 +02:00 committed by GitHub
parent 40e0cca543
commit c591af2a91
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
12 changed files with 160 additions and 545 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

8
docs/clearml_agent.md
View File

@ -1,5 +1,5 @@
---
title: ClearML Agent Overview
title: ClearML Agent
---
**ClearML Agent** is a virtual environment and execution manager for DL / ML solutions on GPU machines. It integrates with the **ClearML Python Package** and ClearML Server to provide a full AI cluster solution. <br/>
@ -649,3 +649,9 @@ Or, force workers on for a queue using the REST API:
```bash
curl --user <key>:<secret> --header "Content-Type: application/json" --data '{"queue":"<queue_id>","tags":["force_workers:on"]}' http://<api-server-hostname-or-ip>:8008/queues.update
```
## References
* See [ClearML Agent CLI](clearml_agent/clearml_agent_ref.md) for a reference for `clearml-agent`'s CLI commands.
* See [ClearML Agent Environment Variables](clearml_agent/clearml_agent_env_var.md) for a list of environment variables
to configure ClearML Agent

141
docs/clearml_agent/clearml_agent_build.md
View File

@ -1,141 +0,0 @@
---
title: build
---
This reference page provides detailed information about ClearML Agent's `build` subcommand, which you can use to create
a worker environment without executing the experiment.
## Syntax
```bash
clearml-agent build [-h] --id TASK_ID [--target TARGET]
[--install-globally]
[--docker [DOCKER [DOCKER ...]]] [--force-docker]
[--python-version PYTHON_VERSION]
[--entry-point {reuse_task,clone_task}] [-O]
[--git-user GIT_USER] [--git-pass GIT_PASS]
[--log-level {DEBUG,INFO,WARN,WARNING,ERROR,CRITICAL}]
[--gpus GPUS] [--cpu-only]
```
## Arguments
---
**`id`**
(*mandatory*)
* Build a worker environment for this Task ID.
---
**`cpu-only`**
* Disable GPU access for the Docker container.
---
**`docker`**
* Docker mode. A Docker container that a worker will execute at launch.
To specify the image name and optional arguments, either:
* Use `--docker <image_name> <args>` on the command line, or
* Use `--docker` on the command line, and specify the image name and arguments in the configuration file.
Environment variable settings for Dockers:
* `CLEARML_DOCKER_SKIP_GPUS_FLAG` - Ignore the `gpus` flag inside the Docker container. This also allows you to execute **ClearML Agent** using Docker versions earlier than 19.03.
* `NVIDIA_VISIBLE_DEVICES` - Limit GPU visibility for the Docker container.
* `CLEARML_AGENT_GIT_USER` and `CLEARML_AGENT_GIT_PASS` - Pass these credentials to the Docker container at execution.
To limit GPU visibility for Docker, set the `NVIDIA_VISIBLE_DEVICES` environment variable.
---
**`entry-point`**
* Used in conjunction with `--docker`, indicates how to run the Task specified by `task-id` on Docker startup.
The `entry-point` options are:
* `reuse` - Overwrite the existing Task data.
* `clone_task` - Clone the Task, and execute the cloned Task.
---
**`force-docker`**
* Force using the agent-specified docker image (either explicitly in the `--docker` argument or using the agent's
default docker image). If provided, the agent will not use any docker container information stored in the task itself
(default `False`)
---
**`git-pass`**
* Git password for repository access.
---
**`git-user`**
* Git username for repository access.
---
**`gpus`**
* Specify the active GPUs for the Docker containers to use. These are the same GPUs set in the `NVIDIA_VISIBLE_DEVICES` environment variable.
For example:
* `--gpus 0`
* `--gpu 0,1,2`
* `--gpus all`
---
**`h`, `help`**
* Get help for this command.
---
**`install-globally`**
* Install the required Python packages before creating the virtual environment. Use `agent.package_manager.system_site_packages` to control the installation of the system packages. When `--docker` is used, `install-globally` is always true.
---
**`log-level`**
* SDK log level. The values are:
* `DEBUG`
* `INFO`
* `WARN`
* `WARNING`
* `ERROR`
* `CRITICAL`
---
**`python-version`**
* Virtual environment Python version to use.
---
**`O`**
* Compile optimized pyc code (see python documentation). Repeat for more optimization.
---
**`target`**
* The target folder for the virtual environment and source code that will be used at launch.

12
docs/clearml_agent/clearml_agent_config.md
View File

@ -1,12 +0,0 @@
---
title: config
---
This reference page provides detailed information about ClearML Agent's `config` subcommand, which you can use to
list your ClearML Agent configuration.
## Syntax
```
clearml-agent config [-h]
```

223
docs/clearml_agent/clearml_agent_daemon.md
View File

@ -1,223 +0,0 @@
---
title: daemon
---
This reference page provides detailed information about ClearML Agent's `daemon` subcommand, which you can use to
run a worker, optionally in a Docker container, listening to a queue.
## Syntax
```bash
clearml-agent daemon [-h] [--foreground] [--queue QUEUES [QUEUES ...]] [--order-fairness]
[--standalone-mode] [--services-mode [SERVICES_MODE]]
[--child-report-tags CHILD_REPORT_TAGS [CHILD_REPORT_TAGS ...]]
[--create-queue] [--detached] [--stop] [--dynamic-gpus]
[--uptime [UPTIME [UPTIME ...]]] [--downtime [DOWNTIME [DOWNTIME ...]]]
[--status] [--use-owner-token] [-O]
[--git-user GIT_USER] [--git-pass GIT_PASS]
[--log-level {DEBUG,INFO,WARN,WARNING,ERROR,CRITICAL}]
[--gpus GPUS] [--cpu-only]
[--docker [DOCKER [DOCKER ...]]] [--force-current-version]
```
## Arguments
---
**`child-report-tags`**
List of tags to send with the status reports from the worker that executes a task.
---
**`cpu-only`**
* If running in Docker mode (see the `docker` option), disable GPU access for the Docker container or virtual environment.
---
**`create-queue`**
* If the queue name provided does not exist in the server, create and use it.
---
**`detached`**
* Run agent in the background. The `clearml-agent` command returns immediately.
---
**`docker`**
* Run in Docker mode. Execute the Task inside a Docker container.
To specify the image name and optional arguments, either:
* use `--docker <image_name> <args>` on the command line, or
* use `--docker` on the command line, and specify the image name and arguments in the configuration file.
Environment variable settings for Dockers:
* `CLEARML_DOCKER_SKIP_GPUS_FLAG` - Ignore the `gpus` flag inside the Docker container. This also allows you to execute **ClearML Agent** using Docker versions earlier than 19.03.
* `NVIDIA_VISIBLE_DEVICES` - Limit GPU visibility for the Docker container.
* `ClearML_AGENT_GIT_USER` and `ClearML_AGENT_GIT_PASS` - Pass these credentials to the Docker container at execution.
---
**`downtime`**
* Specify downtime for clearml-agent in `<hours> <days>` format.
For example, use `09-13 TUE` to set Tuesday's downtime to 09-13.
:::info
* This feature is available under the ClearML Enterprise plan
* Make sure to have only one of uptime / downtime configuration and not both.
:::
---
**`dynamic-gpus`**
* Allow to dynamically allocate gpus based on queue properties, configure with `--queue <queue_name>=<num_gpus>`.
For example: `--dynamic-gpus --queue dual_gpus=2 single_gpu=1`
:::info Enterprise Feature
This feature is available under the ClearML Enterprise plan
:::
---
**`force-current-version`**
* To use your current version of **ClearML Agent** when running in Docker mode (the `docker` argument is specified),
instead of the latest **ClearML Agent** version which is automatically installed, specify `force-current-version`.
For example, if your current **ClearML Agent** version is `0.13.1`, but the latest version of **ClearML Agent** is
`0.13.3`, use `--force-current-version` and your Task will execute in the Docker container with **ClearML Agent** version `0.13.1`.
---
**`foreground`**
* Pipe full log to stdout/stderr. Do not use this option if running in background.
---
**`git-pass`**
* Git password for repository access.
---
**`git-user`**
* Git username for repository access.
---
**`gpus`**
* If running in Docker mode (see the `docker` option), specify the active GPUs for the Docker containers to use.
These are the same GPUs set in the `NVIDIA_VISIBLE_DEVICES` environment variable.
For example:
* `--gpus 0`
* `--gpu 0,1,2`
* `--gpus all`
---
**`h`, `help`**
* Get help for this command.
---
**`log-level`**
* SDK log level. The values are:
* `DEBUG`
* `INFO`
* `WARN`
* `WARNING`
* `ERROR`
* `CRITICAL`
---
**`O`**
* Compile optimized pyc code (see python documentation). Repeat for more optimization.
---
**`order-fairness`**
* Pull from each queue in a round-robin order, instead of priority order.
---
**`queue`**
* Specify the queues which the worker is listening to. The values can be any combination of:
* One or more queue IDs.
* One or more queue names.
* `default` indicating the default queue.
---
**`services-mode`** <a class="tr_top_negative" name="services_mode"></a>
* Launch multiple long-term docker services. Spin multiple, simultaneous Tasks, each in its own Docker container, on the same machine. Each Task will be registered
as a new node in the system, providing tracking and transparency capabilities. Start up and shutdown of each Docker is
verified. Use in CPU mode (`--cpu-only`), only.
* To limit the number of simultaneous tasks run in services mode, pass the maximum number immediately after the
`--services-mode` option (e.g. `--services-mode 5`)
---
**`standalone-mode`**
* Do not use any network connects. This assumes all requirements are pre-installed.
---
**`status`**
* Print the worker's schedule (uptime properties, server's runtime properties and listening queues)
---
**`stop`**
* Terminate a running ClearML Agent, if other arguments are the same. If no additional arguments are provided, agents are
terminated in lexicographical order.
---
**`uptime`**
* Specify uptime for clearml-agent in `<hours> <days>` format. for example, use `17-20 TUE` to set Tuesday's
uptime to 17-20
:::info
* This feature is available under the ClearML Enterprise plan
* Make sure to have only one of uptime / downtime configuration and not both.
:::
---
**`use-owner-token`**
Generate and use the task owner's token for the execution of the task.

5
docs/clearml_agent/clearml_agent_env_var.md
View File

@ -1,11 +1,12 @@
---
title: Environment Variables
title: ClearML Agent Environment Variables
---
This page lists the available environment variables for configuring ClearML Agent.
:::info
ClearML's environment variables override the clearml.conf file, SDK, and [configuration vault](../webapp/webapp_profile.md#configuration-vault),
ClearML's environment variables override the [clearml.conf file](../configs/clearml_conf.md), SDK, and
[configuration vault](../webapp/webapp_profile.md#configuration-vault),
but can be overridden by command-line arguments.
:::

130
docs/clearml_agent/clearml_agent_execute.md
View File

@ -1,130 +0,0 @@
---
title: execute
---
This reference page provides detailed information about ClearML Agent's `execute` subcommand, which you can use to
build and execute an experiment without a queue.
## Syntax
```bash
clearml-agent execute [-h] --id TASK_ID [--log-file LOG_FILE] [--disable-monitoring]
[--full-monitoring] [--require-queue]
[--standalone-mode] [--docker [DOCKER [DOCKER ...]]] [--clone]
[-O] [--git-user GIT_USER] [--git-pass GIT_PASS]
[--log-level {DEBUG,INFO,WARN,WARNING,ERROR,CRITICAL}]
[--gpus GPUS] [--cpu-only]
```
## Arguments
---
**`id`** (*mandatory*)
* The ID of the Task to build.
---
**`clone`**
* Clone the Task specified by `id`, and then execute that cloned Task.
---
**`cpu-only`**
* Disable GPU access for the daemon, only use CPU in either docker or virtual environment.
---
**`docker`**
* Run in Docker mode. Execute the Task inside a Docker container.
To specify the image name and optional arguments, either:
* use `--docker <image_name> <args>` on the command line, or
* use `--docker` on the command line, and specify the default image name and arguments in the configuration file.
Environment variable settings for Dockers containers:
* `ClearML_DOCKER_SKIP_GPUS_FLAG` - Ignore the `gpus` flag inside the Docker container. This also allows you to execute **ClearML Agent** using Docker versions earlier than 19.03.
* `NVIDIA_VISIBLE_DEVICES` - Limit GPU visibility for the Docker container.
* `ClearML_AGENT_GIT_USER` and `ClearML_AGENT_GIT_PASS` - Pass these credentials to the Docker container at execution.
---
**`disable-monitoring`**
* Disable logging and monitoring, except for stdout.
---
**`full-monitoring`**
* Create a full log, including the environment setup log, Task log, and monitoring, as well as stdout.
---
**`git-pass`**
* Git password for repository access.
---
**`git-user`**
* Git username for repository access.
---
**`gpus`**
* Specify active GPUs for the daemon to use (docker / virtual environment), Equivalent to setting
`NVIDIA_VISIBLE_DEVICES`. Examples: `--gpus 0` or `--gpu 0,1,2` or `--gpus all`
---
**`h`, `help`**
* Get help for this command.
---
**`log-file`**
* The log file for Task execution output (stdout / stderr) to a text file.
---
**`log-level`**
* SDK log level. The values are:
* `DEBUG`
* `INFO`
* `WARN`
* `WARNING`
* `ERROR`
* `CRITICAL`
---
**`O`**
* Compile optimized pyc code (see python documentation). Repeat for more optimization.
---
**`require-queue`**
* If the specified task is not queued (in any Queue), the execution will fail. (Used for 3rd party scheduler
integration, e.g. K8s, SLURM, etc.)
---
**`standalone-mode`**
* Do not use any network connects, assume everything is pre-installed

10
docs/clearml_agent/clearml_agent_list.md
View File

@ -1,10 +0,0 @@
---
title: list
---
This reference page provides detailed information about ClearML Agent's `list` subcommand, which you can use to list
information about all active workers.
## Syntax
clearml-agent list [-h]

146
docs/clearml_agent/clearml_agent_ref.md
View File

@ -1,13 +1,141 @@
---
title: ClearML Agent Reference
title: ClearML Agent CLI
---
The following reference pages provide detailed information about using ClearML Agent:
The following page provides a reference to `clearml-agent`'s CLI commands:
* [build](#build) - Create a worker environment without executing an experiment.
* [config](#config) - List your ClearML Agent configuration data.
* [daemon](#daemon) - Run a worker daemon listening to a queue for Tasks (experiments) to execute.
* [execute](#execute) - Execute an experiment, locally without a queue.
* [list](#list) - List the current workers.
## build
Create a worker environment without executing the experiment.
```bash
clearml-agent build [-h] --id TASK_ID [--target TARGET]
[--install-globally]
[--docker [DOCKER [DOCKER ...]]] [--force-docker]
[--python-version PYTHON_VERSION]
[--entry-point {reuse_task,clone_task}] [-O]
[--git-user GIT_USER] [--git-pass GIT_PASS]
[--log-level {DEBUG,INFO,WARN,WARNING,ERROR,CRITICAL}]
[--gpus GPUS] [--cpu-only]
```
### Parameters
|Name | Description| Optional |
|---|----|---|
|`--id`| Build a worker environment for this Task ID.|<img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" />|
|`--cpu-only`| Disable GPU access for the Docker container.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--docker`| Run agent in Docker mode. Specify Docker container that a worker will execute at launch. To specify the image name and optional arguments, use one of the following: <ul><li>`--docker <image_name> <args>` on the command line</li><li>`--docker` on the command line, and specify the default image name and arguments in the configuration file.</li></ul> Environment variable settings for Docker containers: <ul><li>`CLEARML_DOCKER_SKIP_GPUS_FLAG` - Ignore the `--gpus` flag inside the Docker container. This also allows you to execute ClearML Agent using Docker versions earlier than 19.03.</li><li>`NVIDIA_VISIBLE_DEVICES` - Limit GPU visibility for the Docker container.</li><li> `CLEARML_AGENT_GIT_USER` and `CLEARML_AGENT_GIT_PASS` - Pass these credentials to the Docker container at execution.</li></ul> To limit GPU visibility for Docker, set the `NVIDIA_VISIBLE_DEVICES` environment variable.| <img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--entry-point`| Used in conjunction with `--docker`, indicates how to run the Task specified by `--task-id` on Docker startup. The `--entry-point` options are: <ul><li>`reuse` - Overwrite the existing Task data.</li><li>`clone_task` - Clone the Task, and execute the cloned Task.</li></ul>|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--force-docker`| Force using the agent-specified docker image (either explicitly in the `--docker` argument or using the agent's default docker image). If provided, the agent will not use any docker container information stored in the task itself (default `False`)|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--git-pass`| Git password for repository access.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--git-user`| Git username for repository access.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--gpus`| Specify the active GPUs for the Docker containers to use. These are the same GPUs set in the `NVIDIA_VISIBLE_DEVICES` environment variable. For example: <ul><li>`--gpus 0`</li><li>`--gpu 0,1,2`</li><li>`--gpus all`</li></ul>|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`-h`, `--help`| Get help for this command.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--install-globally`| Install the required Python packages before creating the virtual environment. Use `agent.package_manager.system_site_packages` to control the installation of the system packages. When `--docker` is used, `--install-globally` is always true.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--log-level`| SDK log level. The values are:<ul><li>`DEBUG`</li><li>`INFO`</li><li>`WARN`</li><li>`WARNING`</li><li>`ERROR`</li><li>`CRITICAL`</li></ul>|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--python-version`| Virtual environment Python version to use.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`-O`| Compile optimized pyc code (see python documentation). Repeat for more optimization.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--target`| The target folder for the virtual environment and source code that will be used at launch.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
## config
List your ClearML Agent configuration.
```
clearml-agent config [-h]
```
## daemon
Run a worker, optionally in a Docker container, listening to a queue.
```bash
clearml-agent daemon [-h] [--foreground] [--queue QUEUES [QUEUES ...]] [--order-fairness]
[--standalone-mode] [--services-mode [SERVICES_MODE]]
[--child-report-tags CHILD_REPORT_TAGS [CHILD_REPORT_TAGS ...]]
[--create-queue] [--detached] [--stop] [--dynamic-gpus]
[--uptime [UPTIME [UPTIME ...]]] [--downtime [DOWNTIME [DOWNTIME ...]]]
[--status] [--use-owner-token] [-O]
[--git-user GIT_USER] [--git-pass GIT_PASS]
[--log-level {DEBUG,INFO,WARN,WARNING,ERROR,CRITICAL}]
[--gpus GPUS] [--cpu-only]
[--docker [DOCKER [DOCKER ...]]] [--force-current-version]
```
### Parameters
|Name | Description| Optional |
|---|----|---|
|`--child-report-tags`| List of tags to send with the status reports from the worker that executes a task.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--cpu-only`| If running in Docker mode (see the `--docker` option), disable GPU access for the Docker container or virtual environment.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--create-queue`| If the queue name provided with `--queue` does not exist in the server, create it on-the-fly and use it.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--detached`| Run agent in the background. The `clearml-agent` command returns immediately.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--docker`| Run in Docker mode. Execute the Task inside a Docker container. To specify the image name and optional arguments, either: <ul><li> Use `--docker <image_name> <args>` on the command line, or </li><li>Use `--docker` on the command line, and specify the default image name and arguments in the configuration file.</li></ul> Environment variable settings for Docker containers: <ul><li>`CLEARML_DOCKER_SKIP_GPUS_FLAG` - Ignore the `--gpus` flag inside the Docker container. This also allows you to execute ClearML Agent using Docker versions earlier than 19.03.</li><li>`NVIDIA_VISIBLE_DEVICES` - Limit GPU visibility for the Docker container.</li><li> `CLEARML_AGENT_GIT_USER` and `CLEARML_AGENT_GIT_PASS` - Pass these credentials to the Docker container at execution.</li></ul>|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--downtime`| Specify downtime for clearml-agent in `<hours> <days>` format. For example, use `09-13 TUE` to set Tuesday's downtime to 09-13. <br/><br/>NOTE: <ul><li>This feature is available under the ClearML Enterprise plan</li><li>Make sure to have only one of uptime / downtime configuration and not both.</li></ul> |<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--dynamic-gpus`| Allow to dynamically allocate GPUs based on queue properties, configure with `--queue <queue_name>=<num_gpus>`. For example: `--dynamic-gpus --queue dual_gpus=2 single_gpu=1` <br/><br/>NOTE: This feature is available under the ClearML Enterprise plan|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--force-current-version`| To use your current version of ClearML Agent when running in Docker mode (the `--docker` argument is specified), instead of the latest ClearML Agent version which is automatically installed, specify `force-current-version`. <br/><br/> For example, if your current ClearML Agent version is `0.13.1`, but the latest version of ClearML Agent is `0.13.3`, use `--force-current-version` and your Task will execute in the Docker container with ClearML Agent version `0.13.1`.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--foreground`| Pipe full log to stdout/stderr. Do not use this option if running in background.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--git-pass`| Git password for repository access.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--git-user`| Git username for repository access|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--gpus`| If running in Docker mode (see the `--docker` option), specify the active GPUs for the Docker containers to use. These are the same GPUs set in the `NVIDIA_VISIBLE_DEVICES` environment variable. For example: <ul><li>`--gpus 0`</li><li>`--gpu 0,1,2`</li><li>`--gpus all`</li></ul>|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`-h`, `--help`| Get help for this command.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--log-level`| SDK log level. The values are:<ul><li>`DEBUG`</li><li>`INFO`</li><li>`WARN`</li><li>`WARNING`</li><li>`ERROR`</li><li>`CRITICAL`</li></ul>|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`-O`| Compile optimized pyc code (see python documentation). Repeat for more optimization.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--order-fairness`| Pull from each queue in a round-robin order, instead of priority order.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--queue`| Specify the queues which the worker is listening to. The values can be any combination of:<ul><li>One or more queue IDs</li><li>One or more queue names</li><li>`default` indicating the default queue</li></ul>|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--services-mode`| Launch multiple long-term docker services. Spin multiple, simultaneous Tasks, each in its own Docker container, on the same machine. Each Task will be registered as a new node in the system, providing tracking and transparency capabilities. Start up and shutdown of each Docker is verified. Use in CPU mode (`--cpu-only`) only. <br/> To limit the number of simultaneous tasks run in services mode, pass the maximum number immediately after the `--services-mode` option (e.g. `--services-mode 5`)|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--standalone-mode`| Do not use any network connects. This assumes all requirements are pre-installed.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--status`| Print the worker's schedule (uptime properties, server's runtime properties and listening queues)|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--stop`| Terminate a running ClearML Agent, if other arguments are the same. If no additional arguments are provided, agents are terminated in lexicographical order.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--uptime`| Specify uptime for clearml-agent in `<hours> <days>` format. For example, use `17-20 TUE` to set Tuesday's uptime to 17-20. <br/><br/>NOTES<ul><li>This feature is available under the ClearML Enterprise plan </li><li>Make sure to have only one of uptime / downtime configuration and not both.</li></ul>|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--use-owner-token`| Generate and use the task owner's token for the execution of the task.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
## execute
Build and execute an experiment without a queue.
```bash
clearml-agent execute [-h] --id TASK_ID [--log-file LOG_FILE] [--disable-monitoring]
[--full-monitoring] [--require-queue]
[--standalone-mode] [--docker [DOCKER [DOCKER ...]]] [--clone]
[-O] [--git-user GIT_USER] [--git-pass GIT_PASS]
[--log-level {DEBUG,INFO,WARN,WARNING,ERROR,CRITICAL}]
[--gpus GPUS] [--cpu-only]
```
### Parameters
|Name | Description| Optional |
|---|----|---|
|`--id`| The ID of the Task to build|<img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" />|
|`--clone`| Clone the Task specified by `--id`, and then execute that cloned Task.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--cpu-only`| Disable GPU access for the daemon, only use CPU in either docker or virtual environment.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--docker`| Run in Docker mode. Execute the Task inside a Docker container. To specify the image name and optional arguments, use one of the following: <ul><li>`--docker <image_name> <args>` on the command line</li><li>`--docker` on the command line, and specify the default image name and arguments in the configuration file.</li></ul> Environment variable settings for Dockers containers: <ul><li>`CLEARML_DOCKER_SKIP_GPUS_FLAG` - Ignore the `--gpus` flag inside the Docker container. This also allows you to execute ClearML Agent using Docker versions earlier than 19.03.</li><li>`NVIDIA_VISIBLE_DEVICES` - Limit GPU visibility for the Docker container.</li><li> `CLEARML_AGENT_GIT_USER` and `CLEARML_AGENT_GIT_PASS` - Pass these credentials to the Docker container at execution.</li></ul>| <img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--disable-monitoring`| Disable logging and monitoring, except for stdout.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--full-monitoring`| Create a full log, including the environment setup log, Task log, and monitoring, as well as stdout.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--git-pass`| Git password for repository access.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--git-user`| Git username for repository access.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--gpus`| Specify active GPUs for the daemon to use (docker / virtual environment), Equivalent to setting `NVIDIA_VISIBLE_DEVICES`. For example: <ul><li>`--gpus 0`</li><li>`--gpu 0,1,2`</li><li>`--gpus all`</li></ul>|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`-h`, `--help`| Get help for this command.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--log-file`| The log file for Task execution output (stdout / stderr) to a text file.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--log-level`| SDK log level. The values are:<ul><li>`DEBUG`</li><li>`INFO`</li><li>`WARN`</li><li>`WARNING`</li><li>`ERROR`</li><li>`CRITICAL`</li></ul>|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`-O`| Compile optimized pyc code (see python documentation). Repeat for more optimization.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--require-queue`| If the specified task is not queued (in any queue), the execution will fail. (Used for 3rd party scheduler integration, e.g. K8s, SLURM, etc.)|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--standalone-mode`| Do not use any network connects, assume everything is pre-installed|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
## list
List information about all active workers.
```bash
clearml-agent list [-h]
```
* `clearml-agent` CLI commands:
* [build](clearml_agent_build.md) - Create a worker environment, without executing an experiment.
* [config](clearml_agent_config.md) - List your ClearML Agent configuration.
* [daemon](clearml_agent_daemon.md) - Run a worker daemon listening to a queue for Task (experiments) to execute.
* [execute](clearml_agent_execute.md) - Execute an experiment, locally without a queue.
* [list](clearml_agent_list.md) - List the current workers.
* [Environment variables](clearml_agent_env_var.md)

2
docs/guides/clearml_agent/executable_exp_containers.md
View File

@ -2,7 +2,7 @@
title: Executable Experiment Containers
---
This tutorial demonstrates using [`clearml-agent`](../../clearml_agent.md)’s [`build`](../../clearml_agent/clearml_agent_build.md)
This tutorial demonstrates using [`clearml-agent`](../../clearml_agent.md)’s [`build`](../../clearml_agent/clearml_agent__ref#build)
command to package an experiment into an executable container. In this example, you will build a Docker image that, when
run, will automatically execute the [keras_tensorboard.py](https://github.com/allegroai/clearml/blob/master/examples/frameworks/keras/keras_tensorboard.py)
script.

2
docs/guides/clearml_agent/exp_environment_containers.md
View File

@ -2,7 +2,7 @@
title: Experiment Environment Containers
---
This tutorial demonstrates using [`clearml-agent`](../../clearml_agent.md)’s [`build`](../../clearml_agent/clearml_agent_build.md)
This tutorial demonstrates using [`clearml-agent`](../../clearml_agent.md)’s [`build`](../../clearml_agent/clearml_agent_ref.md#build)
command to build a Docker container replicating the execution environment of an existing task. ClearML Agents can make
use of such containers to execute tasks without having to set up their environment every time.

9
docusaurus.config.js
View File

@ -79,13 +79,18 @@ module.exports = {
to: '/docs/references/sdk/task',
},
{
label: 'Hyper-Datasets',
to: '/docs/references/hyperdataset',
label: 'ClearML Agent',
to: '/docs/clearml_agent/clearml_agent_ref',
},
{
label: 'Server API',
to: '/docs/references/api',
},
{
label: 'Hyper-Datasets',
to: '/docs/references/hyperdataset',
},
{
label: 'Release Notes',
to: '/docs/release_notes/ver_1_9',

17
sidebars.js
View File

@ -36,19 +36,7 @@ module.exports = {
{'ClearML Fundamentals': ['fundamentals/projects', 'fundamentals/task', 'fundamentals/hyperparameters', 'fundamentals/artifacts', 'fundamentals/logger', 'fundamentals/agents_and_queues',
'fundamentals/hpo']},
{'ClearML SDK': ['clearml_sdk/clearml_sdk', 'clearml_sdk/task_sdk', 'clearml_sdk/model_sdk', 'clearml_sdk/apiclient_sdk']},
{'ClearML Agent':
[
'clearml_agent',
{'Reference':
[
'clearml_agent/clearml_agent_ref', 'clearml_agent/clearml_agent_build',
'clearml_agent/clearml_agent_config', 'clearml_agent/clearml_agent_daemon',
'clearml_agent/clearml_agent_execute', 'clearml_agent/clearml_agent_list',
'clearml_agent/clearml_agent_env_var'
]
}
]
},
'clearml_agent',
{'ClearML Pipelines':['pipelines/pipelines',
{"Building Pipelines":
['pipelines/pipelines_sdk_tasks', 'pipelines/pipelines_sdk_function_decorators']
@ -208,6 +196,9 @@ module.exports = {
'references/sdk/hpo_parameters_parameterset',
]},
],
clearmlAgentSidebar: [
'clearml_agent/clearml_agent_ref', 'clearml_agent/clearml_agent_env_var'
],
hyperdatasetsSidebar: [
'hyperdatasets/overview',
{'Frames': [