clearml-docs/docs/clearml_agent/clearml_agent_build.md

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

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.