clearml-docs/docs/guides/clearml-task/clearml_task_tutorial.md

title
ClearML Task Tutorial

In this tutorial, you will use clearml-task to execute a script on a remote or local machine, from a remote repository and your local machine.

Prerequisites

• clearml Python package installed

• clearml-agent running on at least one machine (to execute the experiment), configured to listen to default queue

Executing Code from a Remote Repository

clearml-task --project keras_examples --name remote_test --repo https://github.com/allegroai/events.git --branch master --script /webinar-0620/keras_mnist.py --args batch_size=64 epochs=1 --queue default

This sets the following arguments:

• --project keras_examples --name remote_test - The project and experiment names
• --repo https://github.com/allegroai/events.git - The repository's URL. By default, clearml-task uses the latest commit from the master branch
• --branch master - The repository branch
• --script /webinar-0620/keras_mnist.py - The script to be executed
• --args batch_size=64 epochs=1 - Arguments passed to the script. This uses the argparse object to get CLI parameters
• --queue default - Selected queue to send the experiment to

:::note Adding Requirements clearml-task automatically finds the requirements.txt file in remote repositories. If a remote repo does not have such a file, make sure to either add one with all the required Python packages, or add the --packages "<package_name>" option to the command (for example: --packages "tqdm>=2.1" "scikit-learn"). :::

Now clearml-task does all the heavy-lifting!

1. It creates a new Task on the ClearML Server.
2. clearml-task enqueues the task in the selected execution queue, where a ClearML Agent assigned to that queue executes the task.

Your output should look something like this:

New task created id=2f96ee95b05d4693b360d0fcbb26b727
Task id=2f96ee95b05d4693b360d0fcbb26b727 sent for execution on queue default
Execution log at: https://app.clear.ml/projects/552d5399112d47029c146d5248570295/experiments/2f96ee95b05d4693b360d0fcbb26b727/output/log

Executing a Local Script

For this example, use a local version of this script.

1. Clone the allegroai/events repository
2. Go to the root folder of the cloned repository
3. Run the following command:

clearml-task --project keras --name local_test --script webinar-0620/keras_mnist.py --branch master --requirements webinar-0620/requirements.txt --args epochs=1 --queue default

This sets the following arguments:

• --project keras --name local_test - The project and experiment names
• --script /webinar-0620/keras_mnist.py - The local script to be executed
• -requirements webinar-0620/requirements.txt - The local python package requirements file
• --args batch_size=64 epochs=1 - Arguments passed to the script. This uses the argparse object to capture CLI parameters
• --queue default - Selected queue to send the experiment to

clearml-task creates a task according to the input parameters, and sends the task to the default queue for execution.