clearml-docs/docs/clearml_agent/clearml_agent_execute.md

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

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

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id (mandatory)

• The ID of the Task to build.

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clone

• Clone the Task specified by id, and then execute that cloned Task.

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cpu-only

• Disable GPU access for the daemon, only use CPU in either docker or virtual environment.

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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.

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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.

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git-pass

• Git password for repository access.

---

git-user

• Git username for repository access.

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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.

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log-file

• The log file for Task execution output (stdout / stderr) to a text file.

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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